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Author SHA1 Message Date
zhang2amd
a1884e46fe Update manifest to v5.4 release. 2022-11-30 12:35:07 -08:00
zhang2amd
419f1a9560 Merge pull request #1870 from RadeonOpenCompute/Rmalavally-patch-8
Update README.md
2022-11-30 12:34:09 -08:00
Saad Rahim
a9c87c8b13 Adding stakeholders to CODEOWNERS file (#1823) 2022-11-30 13:22:26 -07:00
Roopa Malavally
002cca3756 Update README.md 2022-11-30 11:39:15 -08:00
zhang2amd
48ded5bc01 Update readme to fix typo, v5.3.3 release. 2022-11-17 14:24:32 -08:00
zhang2amd
ee989c21f9 Update manifest to v5.3.3 release 2022-11-17 14:15:27 -08:00
zhang2amd
b638a620ac Merge pull request #1858 from RadeonOpenCompute/Rmalavally-patch-5
Update README.md
2022-11-17 14:14:30 -08:00
Roopa Malavally
36a57f1389 Update README.md 2022-11-17 13:36:08 -08:00
Saad Rahim
c92f5af561 Adding MIT License file (#1845) 2022-11-15 12:54:14 -07:00
zhang2amd
09001c933b Update manifest file to v5.3.2 release. 2022-11-09 17:32:00 -08:00
zhang2amd
b7c9943ff7 Merge pull request #1855 from RadeonOpenCompute/Rmalavally-patch-5
Update README.md
2022-11-09 17:29:56 -08:00
Roopa Malavally
25a52ec827 Update README.md 2022-11-09 17:16:04 -08:00
zhang2amd
b14834e5a1 Merge pull request #1818 from RadeonOpenCompute/Rmalavally-patch-3
Update README.md
2022-10-04 10:19:57 -07:00
zhang2amd
368178d758 Update manifest to release 5.3.0 2022-09-30 16:20:26 -07:00
Roopa Malavally
a047d37bfe Update README.md 2022-09-30 16:09:00 -07:00
Saad Rahim
7536ef0196 Fixing Ubuntu 22 to Ubuntu 20 (#1792) 2022-08-19 14:21:53 -06:00
Saad Rahim
5241caf779 Final edits to documentation (#1791) 2022-08-18 17:26:47 -06:00
Saad Rahim
1ae99c5e4b Updates to release notes, changelog and manifest for ROCm 5.2.3 (#1788) 2022-08-18 14:37:04 -06:00
Saad Rahim
f034733da2 Adding a CODEOWNERS file (#1771) 2022-07-29 14:26:53 -06:00
Saad Rahim
d4879fdec4 Removing unused files (#1772) 2022-07-22 13:37:21 +01:00
Roopa Malavally
60957c84b7 Update README.md 2022-07-21 17:47:33 -07:00
zhozha
3859eef2a9 Update manifest to 5.2.1 release 2022-07-21 16:28:50 -07:00
zhozha
4915438362 Update manifest for ROCm 5.2 release, remove old docs 2022-06-28 18:32:04 -07:00
Roopa Malavally
c4ce059e12 Update README.md 2022-06-28 18:13:03 -07:00
Ronan Keryell
ca4d4597ba Add release note section (#1740)
* Remove spurious trailing spaces

* Move all the release notes into a global release note section
2022-05-25 22:06:01 -06:00
zhozha
418e8bfda6 Update manifest to 5.1.3 release 2022-05-20 15:58:17 -07:00
Roopa Malavally
82477df454 Update README.md 2022-05-20 15:37:38 -07:00
zhang2amd
075562b1f2 Update manifest to 5.1.1 release 2022-04-08 17:30:20 -07:00
Roopa Malavally
74d067032e Update README.md 2022-04-08 17:08:51 -07:00
zhang2amd
526846dc7e Update manifest to 5.1 release 2022-03-30 18:44:16 -07:00
Roopa Malavally
a47030ca10 Update README.md 2022-03-30 18:19:14 -07:00
zhang2amd
fac29ca466 Update default.xml for ROCm 5.0.2 release 2022-03-04 15:28:19 -08:00
Roopa Malavally
986ba19e80 Update README.md 2022-03-04 15:13:47 -08:00
Roopa Malavally
e00f7f6d59 Update README.md 2022-03-04 15:12:54 -08:00
Roopa Malavally
cac8ecf2bc Update README.md 2022-02-23 21:23:18 -08:00
Roopa Malavally
2653e081e2 Delete Hardware_and_Software_Support.md 2022-02-23 21:22:43 -08:00
Roopa Malavally
34eb2a85f3 Update Hardware_and_Software_Support.md 2022-02-23 18:30:44 -08:00
Roopa Malavally
164129954e Create Hardware_and_Software_Support.md 2022-02-23 18:29:53 -08:00
zhang2amd
eaf8e74802 Update default.xml for ROCm 5.0.1 release 2022-02-16 16:58:29 -08:00
Roopa Malavally
403c81a83e Update README.md 2022-02-16 16:54:40 -08:00
Cory Bloor
ced195c62c Cleanup README.md formatting (#1674)
* Cleanup README.md formatting

Fixed code formatting, broken URLs and changelog table.

* Update README.md

Fixup rocm-smi --showtopoaccess.
2022-02-13 08:24:02 -08:00
Roopa Malavally
3486206b09 Add files via upload 2022-02-10 16:12:04 -08:00
Roopa Malavally
c379917e1c Delete ROCm_Release_Notes_v5.0.pdf 2022-02-10 16:11:51 -08:00
Roopa Malavally
0a60a3b256 Add files via upload 2022-02-10 09:57:04 -08:00
Roopa Malavally
99a3476a5e Delete ROCm_Installation_Guide v5.0.pdf 2022-02-10 09:56:43 -08:00
Roopa Malavally
ad3a774274 Delete ROCm_Installation_Guide_v5.0.pdf 2022-02-10 08:43:38 -08:00
Roopa Malavally
5bb9c86fb6 Add files via upload 2022-02-10 08:43:17 -08:00
zhang2amd
0a0b750e0e Update default.xml for ROCm 5.0 release 2022-02-09 21:11:15 -08:00
Roopa Malavally
c6ec9d7b55 Update README.md 2022-02-09 21:09:07 -08:00
Roopa Malavally
a1eac48dea AMD ROCm Release v5.0 (#1670)
* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Add files via upload

* converting md tables

* Update README.md

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* more changes to table

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* latest changes with alignment

* Update README.md

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* Update README.md

* tables made till system interface

Co-authored-by: anubhavamd <92926185+anubhavamd@users.noreply.github.com>
2022-02-09 21:07:33 -08:00
Roopa Malavally
94f4488904 Delete ROCm_SMI_Manual_4.5.pdf 2022-02-09 17:53:09 -08:00
Roopa Malavally
afc1a33ad7 Delete ROCDebugger_User_Guide.pdf 2022-02-09 17:52:22 -08:00
Roopa Malavally
9b6fb663c9 Delete ROCDebugger_API_Guide.pdf 2022-02-09 17:52:12 -08:00
Roopa Malavally
7d78a111b4 Delete RDC_API_Manual_4.5.pdf 2022-02-09 17:51:58 -08:00
Roopa Malavally
f04316efdb Delete AMD_ROCm_DataCenter_Tool_User_Guide_v4.5.pdf 2022-02-09 17:51:47 -08:00
Roopa Malavally
0083f955a7 Delete AMD_HIP_Supported_CUDA_API_Reference_Guide.pdf 2022-02-09 17:51:35 -08:00
Roopa Malavally
237e662486 Delete AMD_HIP_Programming_Guide.pdf 2022-02-09 17:51:27 -08:00
Roopa Malavally
475711bb7d Delete AMD_Compiler_Reference_Guide_v4.5.pdf 2022-02-09 17:51:17 -08:00
Roopa Malavally
dc2b00f43d Delete AMD-HIP-API-4.5.pdf 2022-02-09 17:51:09 -08:00
Roopa Malavally
c0cd1b72ce Delete AMD Instinct™High Performance Computing and Tuning Guide.pdf 2022-02-09 17:51:02 -08:00
zhozha
95493f625c Update default.xml for ROCm 4.5.2 release 2021-12-10 16:40:11 -08:00
Roopa Malavally
c3f91afb26 Update README.md 2021-12-10 16:29:05 -08:00
Roopa Malavally
d827b836b2 Update README.md 2021-12-10 16:24:06 -08:00
Roopa Malavally
99d5fb03e0 Add files via upload 2021-12-10 16:23:34 -08:00
Roopa Malavally
1f6c308006 Delete AMD_HIP_Programming_Guide.pdf 2021-12-10 16:23:21 -08:00
Roopa Malavally
bb3aa02a86 Update README.md 2021-12-10 15:47:14 -08:00
Roopa Malavally
9b82c422d0 Update README.md 2021-11-23 11:08:04 -08:00
Roopa Malavally
8eed074e8a Update README.md 2021-11-23 11:07:12 -08:00
Roopa Malavally
53db303dd3 Update README.md 2021-11-23 10:54:49 -08:00
Roopa Malavally
36ec27d9a4 Update README.md 2021-11-23 10:52:59 -08:00
Roopa Malavally
d78bb0121b Update README.md 2021-11-23 10:43:10 -08:00
Roopa Malavally
f72c130e06 Update README.md 2021-11-17 07:05:28 -08:00
zhang2amd
c058e7a1c9 Added hipamd and MIOpenTensile to manifest. 2021-11-09 07:57:31 -08:00
zhang2amd
0d12925fe9 Merge pull request #1602 from RadeonOpenCompute/zhang2amd-patch-1
Update manifest for ROCm 4.5 release.
2021-10-27 20:36:31 -07:00
zhang2amd
f088317e44 Update manifest for ROCm 4.5 release. 2021-10-27 20:35:20 -07:00
Roopa Malavally
ca8f60e96f Update README.md 2021-10-27 19:26:36 -07:00
Roopa Malavally
ba8c56abdc Update README.md 2021-10-27 19:24:34 -07:00
Roopa Malavally
18410afcd7 Add files via upload 2021-10-27 07:24:03 -07:00
Roopa Malavally
c637c2a964 Add files via upload 2021-10-26 19:00:15 -07:00
Roopa Malavally
5a56a31fac Delete AMD_HIP_Supported_CUDA_API_Reference_Guide.pdf 2021-10-26 18:59:59 -07:00
Roopa Malavally
82b35be1ee Add files via upload 2021-10-26 18:21:01 -07:00
Roopa Malavally
03fb0f863c Delete HIP-API-4.5.pdf 2021-10-26 17:28:58 -07:00
Roopa Malavally
c730ade1e3 Add files via upload 2021-10-26 17:28:44 -07:00
Roopa Malavally
164a386ed6 Add files via upload 2021-10-26 17:27:34 -07:00
Roopa Malavally
db517138f6 Add files via upload 2021-10-26 17:17:19 -07:00
Roopa Malavally
bc63e35725 Add files via upload 2021-10-26 16:49:33 -07:00
Roopa Malavally
c9a8556171 Add files via upload 2021-10-26 16:34:10 -07:00
Roopa Malavally
91f193a510 Delete AMD_ROCm_SMI_Guide_v4.3.pdf 2021-10-26 15:46:18 -07:00
Roopa Malavally
b2fac149b5 Delete AMD_ROCm_Release_Notes_v4.3.pdf 2021-10-26 15:46:04 -07:00
Roopa Malavally
1d23bb0ec6 Delete AMD_ROCm_Release_Notes_v4.3.1.pdf 2021-10-26 15:45:49 -07:00
Roopa Malavally
fedfa50634 Delete AMD_ROCm_DataCenter_Tool_User_Guide_v4.3.pdf 2021-10-26 15:45:37 -07:00
Roopa Malavally
51ea894667 Delete AMD_ROCDebugger_User_Guide.pdf 2021-10-26 15:45:26 -07:00
Roopa Malavally
63b0e6d273 Delete AMD_ROCDebugger_API.pdf 2021-10-26 15:45:14 -07:00
Roopa Malavally
f1383c5d16 Delete AMD_RDC_API_Guide_v4.3.pdf 2021-10-26 15:45:02 -07:00
Roopa Malavally
f3ec7b4720 Delete AMD_HIP_Supported_CUDA_API_Reference_Guide_v4.3.pdf 2021-10-26 15:44:52 -07:00
Roopa Malavally
9492fc9b0d Delete AMD_HIP_Programming_Guide_v4.3.pdf 2021-10-26 15:44:37 -07:00
Roopa Malavally
c103fe233f Delete AMD_HIP_API_Guide_v4.3.pdf 2021-10-26 15:44:23 -07:00
Roopa Malavally
63c16a229e Delete AMD_Compiler_Reference_Guide_v4.3.pdf 2021-10-26 15:44:08 -07:00
Paul Menzel
18aa89804f README: Replace screenshots of tables with Markdown table (#1593)
The screenshots are from tables with text, which are not easily searchable,
are bigger in size than needed – increasing load times – and are in a
resolution, causing them to be blurry on HiDPI displays.  Therefore, use a
Markdown table instead solving all the issues above, and delete the images
from the repository.

The SLES service pack version differs in the two screenshots: SP2 vs SP3.
Go for *SP3*.

Resolves: https://github.com/RadeonOpenCompute/ROCm/issues/1591
2021-10-15 06:27:44 -07:00
Roopa Malavally
65a4524834 Update README.md 2021-09-18 12:36:44 -07:00
Roopa Malavally
b04ab30e81 Delete AMD_ROCm_v2.10_Release_Notes.pdf 2021-09-15 19:40:10 -07:00
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Changelog
------------------
# AMD ROCm™ Releases
## AMD ROCm™ V5.2 Release
AMD ROCm v5.2 is now released. The release documentation is available at https://docs.amd.com.
## AMD ROCm™ V5.1.3 Release
AMD ROCm v5.1.3 is now released. The release documentation is available at https://docs.amd.com.
## AMD ROCm™ V5.1.1 Release
AMD ROCm v5.1.1 is now released. The release documentation is available at https://docs.amd.com.
## AMD ROCm™ V5.1 Release
AMD ROCm v5.1 is now released. The release documentation is available at https://docs.amd.com.
## AMD ROCm™ v5.0.2 Release Notes
### Fixed Defects in This Release
The following defects are fixed in the ROCm v5.0.2 release.
#### Issue with hostcall Facility in HIP Runtime
In ROCm v5.0, when using the “assert()” call in a HIP kernel, the compiler may sometimes fail to emit kernel metadata related to the hostcall facility, which results in incomplete initialization of the hostcall facility in the HIP runtime. This can cause the HIP kernel to crash when it attempts to execute the “assert()” call.
The root cause was an incorrect check in the compiler to determine whether the hostcall facility is required by the kernel. This is fixed in the ROCm v5.0.2 release.
The resolution includes a compiler change, which emits the required metadata by default, unless the compiler can prove that the hostcall facility is not required by the kernel. This ensures that the “assert()” call never fails.
**Note**: This fix may lead to breakage in some OpenMP offload use cases, which use print inside a target region and result in an abort in device code. The issue will be fixed in a future release.
#### Compatibility Matrix Updates to ROCm Deep Learning Guide
The compatibility matrix in the AMD Deep Learning Guide is updated for ROCm v5.0.2.
For more information and documentation updates, refer to https://docs.amd.com.
## AMD ROCm™ v5.0.1 Release Notes
### Deprecations and Warnings
#### Refactor of HIPCC/HIPCONFIG
In prior ROCm releases, by default, the hipcc/hipconfig Perl scripts were used to identify and set target compiler options, target platform, compiler, and runtime appropriately.
In ROCm v5.0.1, hipcc.bin and hipconfig.bin have been added as the compiled binary implementations of the hipcc and hipconfig. These new binaries are currently a work-in-progress, considered, and marked as experimental. ROCm plans to fully transition to hipcc.bin and hipconfig.bin in the a future ROCm release. The existing hipcc and hipconfig Perl scripts are renamed to hipcc.pl and hipconfig.pl respectively. New top-level hipcc and hipconfig Perl scripts are created, which can switch between the Perl script or the compiled binary based on the environment variable HIPCC_USE_PERL_SCRIPT.
In ROCm 5.0.1, by default, this environment variable is set to use hipcc and hipconfig through the Perl scripts.
Subsequently, Perl scripts will no longer be available in ROCm in a future release.
### ROCM DOCUMENTATION UPDATES FOR ROCM 5.0.1
* ROCm Downloads Guide
* ROCm Installation Guide
* ROCm Release Notes
For more information, see https://docs.amd.com.
## AMD ROCm™ v5.0 Release Notes
# ROCm Installation Updates
This document describes the features, fixed issues, and information about downloading and installing the AMD ROCm™ software.
It also covers known issues and deprecations in this release.
## Notice for Open-source and Closed-source ROCm Repositories in Future Releases
To make a distinction between open-source and closed-source components, all ROCm repositories will consist of sub-folders in future releases.
- All open-source components will be placed in the `base-url/<rocm-ver>/main` sub-folder
- All closed-source components will reside in the `base-url/<rocm-ver>/proprietary` sub-folder
## List of Supported Operating Systems
The AMD ROCm platform supports the following operating systems:
| **OS-Version (64-bit)** | **Kernel Versions** |
| --- | --- |
| CentOS 8.3 | 4.18.0-193.el8 |
| CentOS 7.9 | 3.10.0-1127 |
| RHEL 8.5 | 4.18.0-348.7.1.el8\_5.x86\_64 |
| RHEL 8.4 | 4.18.0-305.el8.x86\_64 |
| RHEL 7.9 | 3.10.0-1160.6.1.el7 |
| SLES 15 SP3 | 5.3.18-59.16-default |
| Ubuntu 20.04.3 | 5.8.0 LTS / 5.11 HWE |
| Ubuntu 18.04.5 [5.4 HWE kernel] | 5.4.0-71-generic |
### Support for RHEL v8.5
This release extends support for RHEL v8.5.
### Supported GPUs
#### Radeon Pro V620 and W6800 Workstation GPUs
This release extends ROCm support for Radeon Pro V620 and W6800 Workstation GPUs.
- SRIOV virtualization support for Radeon Pro V620
- KVM Hypervisor (1VF support only) on Ubuntu Host OS with Ubuntu, CentOs, and RHEL Guest
- Support for ROCm-SMI in an SRIOV environment. For more details, refer to the ROCm SMI API documentation.
**Note:** Radeon Pro v620 is not supported on SLES.
## ROCm Installation Updates for ROCm v5.0
This release has the following ROCm installation enhancements.
### Support for Kernel Mode Driver
In this release, users can install the kernel-mode driver using the Installer method. Some of the ROCm-specific use cases that the installer currently supports are:
- OpenCL (ROCr/KFD based) runtime
- HIP runtimes
- ROCm libraries and applications
- ROCm Compiler and device libraries
- ROCr runtime and thunk
- Kernel-mode driver
### Support for Multi-version ROCm Installation and Uninstallation
Users now can install multiple ROCm releases simultaneously on a system using the newly introduced installer script and package manager install mechanism.
Users can also uninstall multi-version ROCm releases using the `amdgpu-uninstall` script and package manager.
### Support for Updating Information on Local Repositories
In this release, the `amdgpu-install` script automates the process of updating local repository information before proceeding to ROCm installation.
### Support for Release Upgrades
Users can now upgrade the existing ROCm installation to specific or latest ROCm releases.
For more details, refer to the AMD ROCm Installation Guide v5.0.
# AMD ROCm V5.0 Documentation Updates
## New AMD ROCm Information Portal ROCm v4.5 and Above
Beginning ROCm release v5.0, AMD ROCm documentation has a new portal at https://docs.amd.com. This portal consists of ROCm documentation v4.5 and above.
For documentation prior to ROCm v4.5, you may continue to access https://rocmdocs.amd.com.
## Documentation Updates for ROCm 5.0
### Deployment Tools
#### ROCm Data Center Tool Documentation Updates
- ROCm Data Center Tool User Guide
- ROCm Data Center Tool API Guide
#### ROCm System Management Interface Updates
- System Management Interface Guide
- System Management Interface API Guide
#### ROCm Command Line Interface Updates
- Command Line Interface Guide
### Machine Learning/AI Documentation Updates
- Deep Learning Guide
- MIGraphX API Guide
- MIOpen API Guide
- MIVisionX API Guide
### ROCm Libraries Documentation Updates
- hipSOLVER User Guide
- RCCL User Guide
- rocALUTION User Guide
- rocBLAS User Guide
- rocFFT User Guide
- rocRAND User Guide
- rocSOLVER User Guide
- rocSPARSE User Guide
- rocThrust User Guide
### Compilers and Tools
#### ROCDebugger Documentation Updates
- ROCDebugger User Guide
- ROCDebugger API Guide
#### ROCTracer
- ROCTracer User Guide
- ROCTracer API Guide
#### Compilers
- AMD Instinct High Performance Computing and Tuning Guide
- AMD Compiler Reference Guide
#### HIPify Documentation
- HIPify User Guide
- HIP Supported CUDA API Reference Guide
#### ROCm Debug Agent
- ROCm Debug Agent Guide
- System Level Debug Guide
- ROCm Validation Suite
### Programming Models Documentation
#### HIP Documentation
- HIP Programming Guide
- HIP API Guide
- HIP FAQ Guide
#### OpenMP Documentation
- OpenMP Support Guide
### ROCm Glossary
- ROCm Glossary Terms and Definitions
## AMD ROCm Legacy Documentation Links ROCm v4.3 and Prior
- For AMD ROCm documentation, see
https://rocmdocs.amd.com/en/latest/
- For installation instructions on supported platforms, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
- For AMD ROCm binary structure, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Software-Stack-for-AMD-GPU.html
- For AMD ROCm release history, see
https://rocmdocs.amd.com/en/latest/Current_Release_Notes/ROCm-Version-History.html
# What's New in This Release
## HIP Enhancements
The ROCm v5.0 release consists of the following HIP enhancements.
### HIP Installation Guide Updates
The HIP Installation Guide is updated to include building HIP from source on the NVIDIA platform.
Refer to the HIP Installation Guide v5.0 for more details.
### Managed Memory Allocation
Managed memory, including the `__managed__` keyword, is now supported in the HIP combined host/device compilation. Through unified memory allocation, managed memory allows data to be shared and accessible to both the CPU and GPU using a single pointer. The allocation is managed by the AMD GPU driver using the Linux Heterogeneous Memory Management (HMM) mechanism. The user can call managed memory API hipMallocManaged to allocate a large chunk of HMM memory, execute kernels on a device, and fetch data between the host and device as needed.
**Note:** In a HIP application, it is recommended to do a capability check before calling the managed memory APIs. For example,
```c
int managed_memory = 0;
HIPCHECK(hipDeviceGetAttribute(&managed_memory, hipDeviceAttributeManagedMemory, p_gpuDevice));
if (!managed_memory) {
printf ("info: managed memory access not supported on the device %d\n Skipped\n", p_gpuDevice);
} else {
HIPCHECK(hipSetDevice(p_gpuDevice));
HIPCHECK(hipMallocManaged(&Hmm, N * sizeof(T)));
. . .
}
```
**Note:** The managed memory capability check may not be necessary; however, if HMM is not supported, managed malloc will fall back to using system memory. Other managed memory API calls will, then, have
Refer to the HIP API documentation for more details on managed memory APIs.
For the application, see [hipMallocManaged.cpp](https://github.com/ROCm-Developer-Tools/HIP/blob/rocm-4.5.x/tests/src/runtimeApi/memory/hipMallocManaged.cpp)
## New Environment Variable
The following new environment variable is added in this release:
| **Environment Variable** | **Value** | **Description** |
| --- | --- | --- |
| **HSA\_COOP\_CU\_COUNT** | 0 or 1 (default is 0) | Some processors support more compute units than can reliably be used in a cooperative dispatch. Setting the environment variable HSA\_COOP\_CU\_COUNT to 1 will cause ROCr to return the correct CU count for cooperative groups through the HSA\_AMD\_AGENT\_INFO\_COOPERATIVE\_COMPUTE\_UNIT\_COUNT attribute of hsa\_agent\_get\_info(). Setting HSA\_COOP\_CU\_COUNT to other values, or leaving it unset, will cause ROCr to return the same CU count for the attributes HSA\_AMD\_AGENT\_INFO\_COOPERATIVE\_COMPUTE\_UNIT\_COUNT and HSA\_AMD\_AGENT\_INFO\_COMPUTE\_UNIT\_COUNT. Future ROCm releases will make HSA\_COOP\_CU\_COUNT=1 the default.
|
## ROCm Math and Communication Libraries
| **Library** | **Changes** |
| --- | --- |
| **rocBLAS** | **Added** <ul><li>Added rocblas\_get\_version\_string\_size convenience function</li><li>Added rocblas\_xtrmm\_outofplace, an out-of-place version of rocblas\_xtrmm</li><li>Added hpl and trig initialization for gemm\_ex to rocblas-bench</li><li>Added source code gemm. It can be used as an alternative to Tensile for debugging and development</li><li>Added option `ROCM_MATHLIBS_API_USE_HIP_COMPLEX` to opt-in to use hipFloatComplex and hipDoubleComplex</li></ul> **Optimizations** <ul><li>Improved performance of non-batched and batched single-precision GER for size m > 1024. Performance enhanced by 5-10% measured on a MI100 (gfx908) GPU.</li><li>Improved performance of non-batched and batched HER for all sizes and data types. Performance enhanced by 2-17% measured on a MI100 (gfx908) GPU.</li></ul> **Changed** <ul><li>Instantiate templated rocBLAS functions to reduce size of librocblas.so</li><li>Removed static library dependency on msgpack</li><li>Removed boost dependencies for clients</li></ul> **Fixed** <ul><li>Option to install script to build only rocBLAS clients with a pre-built rocBLAS library</li><li>Correctly set output of nrm2\_batched\_ex and nrm2\_strided\_batched\_ex when given bad input</li><li>Fix for dgmm with side == rocblas\_side\_left and a negative incx</li><li>Fixed out-of-bounds read for small trsm</li><li>Fixed numerical checking for tbmv\_strided\_batched</li></ul> |
| | |
| **hipBLAS** | **Added** <ul><li>Added rocSOLVER functions to hipblas-bench</li><li>Added option `ROCM_MATHLIBS_API_USE_HIP_COMPLEX` to opt-in to use hipFloatComplex and hipDoubleComplex</li><li>Added compilation warning for future trmm changes</li><li>Added documentation to hipblas.h</li><li>Added option to forgo pivoting for getrf and getri when ipiv is nullptr</li><li>Added code coverage option</li></ul> **Fixed** <ul><li>Fixed use of incorrect `HIP_PATH` when building from source.</li><li>Fixed windows packaging</li><li>Allowing negative increments in hipblas-bench</li><li>Removed boost dependency</li></ul> |
| | |
| **rocFFT** | **Changed** <ul><li>Enabled runtime compilation of single FFT kernels > length 1024.</li><li>Re-aligned split device library into 4 roughly equal libraries.</li><li>Implemented the FuseShim framework to replace the original OptimizePlan</li><li>Implemented the generic buffer-assignment framework. The buffer assignment is no longer performed by each node. A generic algorithm is designed to test and pick the best assignment path. With the help of FuseShim, more kernel-fusions are achieved.</li><li>Do not read the imaginary part of the DC and Nyquist modes for even-length complex-to-real transforms.</li></ul> **Optimizations** <ul><li>Optimized twiddle-conjugation; complex-to-complex inverse transforms have similar performance to foward transforms now.</li><li>Improved performance of single-kernel small 2D transforms.</li></ul> |
| | |
| **hipFFT** | **Fixed** <ul><li>Fixed incorrect reporting of rocFFT version.</li></ul> **Changed** <ul><li>Unconditionally enabled callback functionality. On the CUDA backend, callbacks only run correctly when hipFFT is built as a static library, and is linked against the static cuFFT library.</li></ul> |
| | |
| **rocSPARSE** | **Added** <ul><li>csrmv, coomv, ellmv, hybmv for (conjugate) transposed matricescsrmv for symmetric matrices</li></ul> **Changed** <ul><li>spmm\_ex is now deprecated and will be removed in the next major release</li></ul> **Improved** <ul><li>Optimization for gtsv</li></ul> |
| | |
| **hipSPARSE** | **Added** <ul><li>Added (conjugate) transpose support for csrmv, hybmv and spmv routines</li></ul> |
| | |
| **rocALUTION** | **Changed** <ul><li>Removed deprecated GlobalPairwiseAMG class, please use PairwiseAMG instead.</li></ul> **Improved** <ul><li>Improved documentation</li></ul> |
| | |
| **rocTHRUST** | **Updates** <ul><li>Updated to match upstream Thrust 1.13.0</li><li>Updated to match upstream Thrust 1.14.0</li><li>Added async scan</li></ul> **Changed** <ul><li>Scan algorithms: inclusive\_scan now uses the input-type as accumulator-type, exclusive\_scan uses initial-value-type. This particularly changes behaviour of small-size input types with large-size output types (e.g. short input, int output). And low-res input with high-res output (e.g. float input, double output)</li></ul> |
| | |
| **rocSOLVER** | **Added** <ul><li>Symmetric matrix factorizations: <ul><li>LASYF</li><li>SYTF2, SYTRF (with batched and strided\_batched versions)</li></ul><li>Added rocsolver\_get\_version\_string\_size to help with version string queries</li><li>Added rocblas\_layer\_mode\_ex and the ability to print kernel calls in the trace and profile logs</li><li>Expanded batched and strided\_batched sample programs.</li></ul> **Optimizations** <ul><li>Improved general performance of LU factorization</li><li>Increased parallelism of specialized kernels when compiling from source, reducing build times on multi-core systems.</li></ul> **Changed** <ul><li>The rocsolver-test client now prints the rocSOLVER version used to run the tests, rather than the version used to build them</li><li>The rocsolver-bench client now prints the rocSOLVER version used in the benchmark</li></ul> **Fixed** <ul><li>Added missing stdint.h include to rocsolver.h</li></ul> |
| | |
| **hipSOLVER** | **Added** <ul><li>Added SYTRF functions: hipsolverSsytrf\_bufferSize, hipsolverDsytrf\_bufferSize, hipsolverCsytrf\_bufferSize, hipsolverZsytrf\_bufferSize, hipsolverSsytrf, hipsolverDsytrf, hipsolverCsytrf, hipsolverZsytrf</li></ul> **Fixed** <ul><li>Fixed use of incorrect `HIP_PATH` when building from source</li></ul> |
| | |
| **RCCL** | **Added** <ul><li>Compatibility with NCCL 2.10.3</li></ul> **Known issues** <ul><li>Managed memory is not currently supported for clique-based kernels</li></ul> |
| | |
| **hipCUB** | **Fixed** <ul><li>Added missing includes to hipcub.hpp</li></ul> **Added** <ul><li>Bfloat16 support to test cases (device\_reduce & device\_radix\_sort)</li><li>Device merge sort</li><li>Block merge sort</li><li>API update to CUB 1.14.0</li></ul> **Changed** <ul><li>The SetupNVCC.cmake automatic target selector select all of the capabalities of all available card for NVIDIA backend.</li></ul> |
| | |
| **rocPRIM** | **Fixed** <ul><li>Enable bfloat16 tests and reduce threshold for bfloat16</li><li>Fix device scan limit\_size feature</li><li>Non-optimized builds no longer trigger local memory limit errors</li></ul> **Added** <ul><li>Scan size limit feature</li><li>Reduce size limit feature</li><li>Transform size limit feature</li><li>Add block\_load\_striped and block\_store\_striped</li><li>Add gather\_to\_blocked to gather values from other threads into a blocked arrangement</li><li>The block sizes for device merge sorts initial block sort and its merge steps are now separate in its kernel config (the block sort step supports multiple items per thread)</li></ul> **Changed** <ul><li>size\_limit for scan, reduce and transform can now be set in the config struct instead of a parameter</li><li>device\_scan and device\_segmented\_scan: inclusive\_scan now uses the input-type as accumulator-type, exclusive\_scan uses initial-value-type. This particularly changes behaviour of small-size input types with large-size output types (e.g. short input, int output) and low-res input with high-res output (e.g. float input, double output)</li><li>Revert old Fiji workaround, because the issue was solved at compiler side</li><li>Update README cmake minimum version number</li><li>Block sort support multiple items per thread. Currently only powers of two block sizes, and items per threads are supported and only for full blocks</li><li>Bumped the minimum required version of CMake to 3.16</li></ul> **Known issues** <ul><li>Unit tests may soft hang on MI200 when running in hipMallocManaged mode.</li><li>device\_segmented\_radix\_sort, device\_scan unit tests failing for HIP on WindowsReduceEmptyInput cause random failure with bfloat16</li><li>Managed memory is not currently supported for clique-based kernels</li></ul> |
## System Management Interface
### Clock Throttling for GPU Events
This feature lists GPU events as they occur in real-time and can be used with _kfdtest_ to produce _vm\_fault_ events for testing.
The command can be called with either &quot; `-e` or `--showevents` like this:
-e [EVENT [EVENT ...]], --showevents [EVENT [EVENT ...]] Show event list
Where `EVENT` is any list combination of `VM_FAULT`, `THERMAL_THROTTLE`, or `GPU_RESET` and is NOT case sensitive.
**Note:** If no event arguments are passed, all events will be watched by default.
#### CLI Commands
```
$ rocm-smi --showevents vm_fault thermal_throttle gpu_reset
======================= ROCm System Management Interface =======================
================================= Show Events ==================================
press 'q' or 'ctrl + c' to quit
DEVICE TIME TYPE DESCRIPTION
============================= End of ROCm SMI Log ==============================
```
(Run kfdtest in another window to test for vm\_fault events.)
**Note:** Unlike other rocm-smi CLI commands, this command does not quit unless specified by the user. Users may press either `q` or `ctrl + c` to quit.
### Display XGMI Bandwidth Between Nodes
The _rsmi\_minmax\_bandwidth\_get_ API reads the HW Topology file and displays bandwidth (min-max) between any two NUMA nodes in a matrix format.
The Command Line Interface (CLI) command can be called as follows:
```
$ rocm-smi --shownodesbw
======================= ROCm System Management Interface =======================
================================== Bandwidth ===================================
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7
GPU0 N/A 50000-200000 50000-50000 0-0 0-0 0-0 50000-100000 0-0
GPU1 50000-200000 N/A 0-0 50000-50000 0-0 50000-50000 0-0 0-0
GPU2 50000-50000 0-0 N/A 50000-200000 50000-100000 0-0 0-0 0-0
GPU3 0-0 50000-50000 50000-200000 N/A 0-0 0-0 0-0 50000-50000
GPU4 0-0 0-0 50000-100000 0-0 N/A 50000-200000 50000-50000 0-0
GPU5 0-0 50000-50000 0-0 0-0 50000-200000 N/A 0-0 50000-50000
GPU6 50000-100000 0-0 0-0 0-0 50000-50000 0-0 N/A 50000-200000
GPU7 0-0 0-0 0-0 50000-50000 0-0 50000-50000 50000-200000 N/A
Format: min-max; Units: mps
============================= End of ROCm SMI Log ==============================
```
The sample output above shows the maximum theoretical xgmi bandwidth between 2 numa nodes,
**Note:** "0-0" min-max bandwidth indicates devices are not connected directly.
### P2P Connection Status
The _rsmi\_is\_p2p\_accessible_ API returns "True" if P2P can be implemented between two nodes, and returns "False" if P2P cannot be implemented between the two nodes.
The Command Line Interface command can be called as follows:
rocm-smi --showtopoaccess
Sample Output:
```
$ rocm-smi --showtopoaccess
======================= ROCm System Management Interface =======================
===================== Link accessibility between two GPUs ======================
GPU0 GPU1
GPU0 True True
GPU1 True True
============================= End of ROCm SMI Log ==============================
```
# Breaking Changes
## Runtime Breaking Change
Re-ordering of the enumerated type in hip\_runtime\_api.h to better match NV. See below for the difference in enumerated types.
ROCm software will be affected if any of the defined enums listed below are used in the code. Applications built with ROCm v5.0 enumerated types will work with a ROCm 4.5.2 driver. However, an undefined behavior error will occur with a ROCm v4.5.2 application that uses these enumerated types with a ROCm 5.0 runtime.
```c
typedef enum hipDeviceAttribute_t {
hipDeviceAttributeMaxThreadsPerBlock, // Maximum number of threads per block.
hipDeviceAttributeMaxBlockDimX, // Maximum x-dimension of a block.
hipDeviceAttributeMaxBlockDimY, // Maximum y-dimension of a block.
hipDeviceAttributeMaxBlockDimZ, // Maximum z-dimension of a block.
hipDeviceAttributeMaxGridDimX, // Maximum x-dimension of a grid.
hipDeviceAttributeMaxGridDimY, // Maximum y-dimension of a grid.
hipDeviceAttributeMaxGridDimZ, // Maximum z-dimension of a grid.
hipDeviceAttributeMaxSharedMemoryPerBlock, // Maximum shared memory available per block in bytes.
hipDeviceAttributeTotalConstantMemory, // Constant memory size in bytes.
hipDeviceAttributeWarpSize, // Warp size in threads.
hipDeviceAttributeMaxRegistersPerBlock, // Maximum number of 32-bit registers available to a
// thread block. This number is shared by all thread
// blocks simultaneously resident on a
// multiprocessor.
hipDeviceAttributeClockRate, // Peak clock frequency in kilohertz.
hipDeviceAttributeMemoryClockRate, // Peak memory clock frequency in kilohertz.
hipDeviceAttributeMemoryBusWidth, // Global memory bus width in bits.
hipDeviceAttributeMultiprocessorCount, // Number of multiprocessors on the device.
hipDeviceAttributeComputeMode, // Compute mode that device is currently in.
hipDeviceAttributeL2CacheSize, // Size of L2 cache in bytes. 0 if the device doesn't have L2
// cache.
hipDeviceAttributeMaxThreadsPerMultiProcessor, // Maximum resident threads per
// multiprocessor.
hipDeviceAttributeComputeCapabilityMajor, // Major compute capability version number.
hipDeviceAttributeComputeCapabilityMinor, // Minor compute capability version number.
hipDeviceAttributeConcurrentKernels, // Device can possibly execute multiple kernels
// concurrently.
hipDeviceAttributePciBusId, // PCI Bus ID.
hipDeviceAttributePciDeviceId, // PCI Device ID.
hipDeviceAttributeMaxSharedMemoryPerMultiprocessor, // Maximum Shared Memory Per
// Multiprocessor.
hipDeviceAttributeIsMultiGpuBoard, // Multiple GPU devices.
hipDeviceAttributeIntegrated, // iGPU
hipDeviceAttributeCooperativeLaunch, // Support cooperative launch
hipDeviceAttributeCooperativeMultiDeviceLaunch, // Support cooperative launch on multiple devices
hipDeviceAttributeMaxTexture1DWidth, // Maximum number of elements in 1D images
hipDeviceAttributeMaxTexture2DWidth, // Maximum dimension width of 2D images in image elements
hipDeviceAttributeMaxTexture2DHeight, // Maximum dimension height of 2D images in image elements
hipDeviceAttributeMaxTexture3DWidth, // Maximum dimension width of 3D images in image elements
hipDeviceAttributeMaxTexture3DHeight, // Maximum dimensions height of 3D images in image elements
hipDeviceAttributeMaxTexture3DDepth, // Maximum dimensions depth of 3D images in image elements
hipDeviceAttributeCudaCompatibleBegin = 0,
hipDeviceAttributeHdpMemFlushCntl, // Address of the HDP\_MEM\_COHERENCY\_FLUSH\_CNTL register
hipDeviceAttributeHdpRegFlushCntl, // Address of the HDP\_REG\_COHERENCY\_FLUSH\_CNTL register
hipDeviceAttributeEccEnabled = hipDeviceAttributeCudaCompatibleBegin, // Whether ECC support is enabled.
hipDeviceAttributeAccessPolicyMaxWindowSize, // Cuda only. The maximum size of the window policy in bytes.
hipDeviceAttributeAsyncEngineCount, // Cuda only. Asynchronous engines number.
hipDeviceAttributeCanMapHostMemory, // Whether host memory can be mapped into device address space
hipDeviceAttributeCanUseHostPointerForRegisteredMem, // Cuda only. Device can access host registered memory
// at the same virtual address as the CPU
hipDeviceAttributeClockRate, // Peak clock frequency in kilohertz.
hipDeviceAttributeComputeMode, // Compute mode that device is currently in.
hipDeviceAttributeComputePreemptionSupported, // Cuda only. Device supports Compute Preemption.
hipDeviceAttributeConcurrentKernels, // Device can possibly execute multiple kernels concurrently.
hipDeviceAttributeConcurrentManagedAccess, // Device can coherently access managed memory concurrently with the CPU
hipDeviceAttributeCooperativeLaunch, // Support cooperative launch
hipDeviceAttributeCooperativeMultiDeviceLaunch, // Support cooperative launch on multiple devices
hipDeviceAttributeDeviceOverlap, // Cuda only. Device can concurrently copy memory and execute a kernel.
// Deprecated. Use instead asyncEngineCount.
hipDeviceAttributeDirectManagedMemAccessFromHost, // Host can directly access managed memory on
// the device without migration
hipDeviceAttributeGlobalL1CacheSupported, // Cuda only. Device supports caching globals in L1
hipDeviceAttributeHostNativeAtomicSupported, // Cuda only. Link between the device and the host supports native atomic operations
hipDeviceAttributeIntegrated, // Device is integrated GPU
hipDeviceAttributeIsMultiGpuBoard, // Multiple GPU devices.
hipDeviceAttributeKernelExecTimeout, // Run time limit for kernels executed on the device
hipDeviceAttributeL2CacheSize, // Size of L2 cache in bytes. 0 if the device doesn&#39;t have L2 cache.
hipDeviceAttributeLocalL1CacheSupported, // caching locals in L1 is supported
hipDeviceAttributeLuid, // Cuda only. 8-byte locally unique identifier in 8 bytes. Undefined on TCC and non-Windows platforms
hipDeviceAttributeLuidDeviceNodeMask, // Cuda only. Luid device node mask. Undefined on TCC and non-Windows platforms
hipDeviceAttributeComputeCapabilityMajor, // Major compute capability version number.
hipDeviceAttributeManagedMemory, // Device supports allocating managed memory on this system
hipDeviceAttributeMaxBlocksPerMultiProcessor, // Cuda only. Max block size per multiprocessor
hipDeviceAttributeMaxBlockDimX, // Max block size in width.
hipDeviceAttributeMaxBlockDimY, // Max block size in height.
hipDeviceAttributeMaxBlockDimZ, // Max block size in depth.
hipDeviceAttributeMaxGridDimX, // Max grid size in width.
hipDeviceAttributeMaxGridDimY, // Max grid size in height.
hipDeviceAttributeMaxGridDimZ, // Max grid size in depth.
hipDeviceAttributeMaxSurface1D, // Maximum size of 1D surface.
hipDeviceAttributeMaxSurface1DLayered, // Cuda only. Maximum dimensions of 1D layered surface.
hipDeviceAttributeMaxSurface2D, // Maximum dimension (width, height) of 2D surface.
hipDeviceAttributeMaxSurface2DLayered, // Cuda only. Maximum dimensions of 2D layered surface.
hipDeviceAttributeMaxSurface3D, // Maximum dimension (width, height, depth) of 3D surface.
hipDeviceAttributeMaxSurfaceCubemap, // Cuda only. Maximum dimensions of Cubemap surface.
hipDeviceAttributeMaxSurfaceCubemapLayered, // Cuda only. Maximum dimension of Cubemap layered surface.
hipDeviceAttributeMaxTexture1DWidth, // Maximum size of 1D texture.
hipDeviceAttributeMaxTexture1DLayered, // Cuda only. Maximum dimensions of 1D layered texture.
hipDeviceAttributeMaxTexture1DLinear, // Maximum number of elements allocatable in a 1D linear texture.
// Use cudaDeviceGetTexture1DLinearMaxWidth() instead on Cuda.
hipDeviceAttributeMaxTexture1DMipmap, // Cuda only. Maximum size of 1D mipmapped texture.
hipDeviceAttributeMaxTexture2DWidth, // Maximum dimension width of 2D texture.
hipDeviceAttributeMaxTexture2DHeight, // Maximum dimension hight of 2D texture.
hipDeviceAttributeMaxTexture2DGather, // Cuda only. Maximum dimensions of 2D texture if gather operations performed.
hipDeviceAttributeMaxTexture2DLayered, // Cuda only. Maximum dimensions of 2D layered texture.
hipDeviceAttributeMaxTexture2DLinear, // Cuda only. Maximum dimensions (width, height, pitch) of 2D textures bound to pitched memory.
hipDeviceAttributeMaxTexture2DMipmap, // Cuda only. Maximum dimensions of 2D mipmapped texture.
hipDeviceAttributeMaxTexture3DWidth, // Maximum dimension width of 3D texture.
hipDeviceAttributeMaxTexture3DHeight, // Maximum dimension height of 3D texture.
hipDeviceAttributeMaxTexture3DDepth, // Maximum dimension depth of 3D texture.
hipDeviceAttributeMaxTexture3DAlt, // Cuda only. Maximum dimensions of alternate 3D texture.
hipDeviceAttributeMaxTextureCubemap, // Cuda only. Maximum dimensions of Cubemap texture
hipDeviceAttributeMaxTextureCubemapLayered, // Cuda only. Maximum dimensions of Cubemap layered texture.
hipDeviceAttributeMaxThreadsDim, // Maximum dimension of a block
hipDeviceAttributeMaxThreadsPerBlock, // Maximum number of threads per block.
hipDeviceAttributeMaxThreadsPerMultiProcessor, // Maximum resident threads per multiprocessor.
hipDeviceAttributeMaxPitch, // Maximum pitch in bytes allowed by memory copies
hipDeviceAttributeMemoryBusWidth, // Global memory bus width in bits.
hipDeviceAttributeMemoryClockRate, // Peak memory clock frequency in kilohertz.
hipDeviceAttributeComputeCapabilityMinor, // Minor compute capability version number.
hipDeviceAttributeMultiGpuBoardGroupID, // Cuda only. Unique ID of device group on the same multi-GPU board
hipDeviceAttributeMultiprocessorCount, // Number of multiprocessors on the device.
hipDeviceAttributeName, // Device name.
hipDeviceAttributePageableMemoryAccess, // Device supports coherently accessing pageable memory
// without calling hipHostRegister on it
hipDeviceAttributePageableMemoryAccessUsesHostPageTables, // Device accesses pageable memory via the host&#39;s page tables
hipDeviceAttributePciBusId, // PCI Bus ID.
hipDeviceAttributePciDeviceId, // PCI Device ID.
hipDeviceAttributePciDomainID, // PCI Domain ID.
hipDeviceAttributePersistingL2CacheMaxSize, // Cuda11 only. Maximum l2 persisting lines capacity in bytes
hipDeviceAttributeMaxRegistersPerBlock, // 32-bit registers available to a thread block. This number is shared
// by all thread blocks simultaneously resident on a multiprocessor.
hipDeviceAttributeMaxRegistersPerMultiprocessor, // 32-bit registers available per block.
hipDeviceAttributeReservedSharedMemPerBlock, // Cuda11 only. Shared memory reserved by CUDA driver per block.
hipDeviceAttributeMaxSharedMemoryPerBlock, // Maximum shared memory available per block in bytes.
hipDeviceAttributeSharedMemPerBlockOptin, // Cuda only. Maximum shared memory per block usable by special opt in.
hipDeviceAttributeSharedMemPerMultiprocessor, // Cuda only. Shared memory available per multiprocessor.
hipDeviceAttributeSingleToDoublePrecisionPerfRatio, // Cuda only. Performance ratio of single precision to double precision.
hipDeviceAttributeStreamPrioritiesSupported, // Cuda only. Whether to support stream priorities.
hipDeviceAttributeSurfaceAlignment, // Cuda only. Alignment requirement for surfaces
hipDeviceAttributeTccDriver, // Cuda only. Whether device is a Tesla device using TCC driver
hipDeviceAttributeTextureAlignment, // Alignment requirement for textures
hipDeviceAttributeTexturePitchAlignment, // Pitch alignment requirement for 2D texture references bound to pitched memory;
hipDeviceAttributeTotalConstantMemory, // Constant memory size in bytes.
hipDeviceAttributeTotalGlobalMem, // Global memory available on devicice.
hipDeviceAttributeUnifiedAddressing, // Cuda only. An unified address space shared with the host.
hipDeviceAttributeUuid, // Cuda only. Unique ID in 16 byte.
hipDeviceAttributeWarpSize, // Warp size in threads.
hipDeviceAttributeMaxPitch, // Maximum pitch in bytes allowed by memory copies
hipDeviceAttributeTextureAlignment, //Alignment requirement for textures
hipDeviceAttributeTexturePitchAlignment, //Pitch alignment requirement for 2D texture references bound to pitched memory;
hipDeviceAttributeKernelExecTimeout, //Run time limit for kernels executed on the device
hipDeviceAttributeCanMapHostMemory, //Device can map host memory into device address space
hipDeviceAttributeEccEnabled, //Device has ECC support enabled
hipDeviceAttributeCudaCompatibleEnd = 9999,
hipDeviceAttributeAmdSpecificBegin = 10000,
hipDeviceAttributeCooperativeMultiDeviceUnmatchedFunc, // Supports cooperative launch on multiple
// devices with unmatched functions
hipDeviceAttributeCooperativeMultiDeviceUnmatchedGridDim, // Supports cooperative launch on multiple
// devices with unmatched grid dimensions
hipDeviceAttributeCooperativeMultiDeviceUnmatchedBlockDim, // Supports cooperative launch on multiple
// devices with unmatched block dimensions
hipDeviceAttributeCooperativeMultiDeviceUnmatchedSharedMem, // Supports cooperative launch on multiple
// devices with unmatched shared memories
hipDeviceAttributeAsicRevision, // Revision of the GPU in this device
hipDeviceAttributeManagedMemory, // Device supports allocating managed memory on this system
hipDeviceAttributeDirectManagedMemAccessFromHost, // Host can directly access managed memory on
// the device without migration
hipDeviceAttributeConcurrentManagedAccess, // Device can coherently access managed memory
// concurrently with the CPU
hipDeviceAttributePageableMemoryAccess, // Device supports coherently accessing pageable memory
// without calling hipHostRegister on it
hipDeviceAttributePageableMemoryAccessUsesHostPageTables, // Device accesses pageable memory via
// the host's page tables
hipDeviceAttributeCanUseStreamWaitValue // '1' if Device supports hipStreamWaitValue32() and
// hipStreamWaitValue64(), '0' otherwise.
hipDeviceAttributeClockInstructionRate = hipDeviceAttributeAmdSpecificBegin, // Frequency in khz of the timer used by the device-side "clock"
hipDeviceAttributeArch, // Device architecture
hipDeviceAttributeMaxSharedMemoryPerMultiprocessor, // Maximum Shared Memory PerMultiprocessor.
hipDeviceAttributeGcnArch, // Device gcn architecture
hipDeviceAttributeGcnArchName, // Device gcnArch name in 256 bytes
hipDeviceAttributeHdpMemFlushCntl, // Address of the HDP_MEM_COHERENCY_FLUSH_CNTL register
hipDeviceAttributeHdpRegFlushCntl, // Address of the HDP_REG_COHERENCY_FLUSH_CNTL register
hipDeviceAttributeCooperativeMultiDeviceUnmatchedFunc, // Supports cooperative launch on multiple
// devices with unmatched functions
hipDeviceAttributeCooperativeMultiDeviceUnmatchedGridDim, // Supports cooperative launch on multiple
// devices with unmatched grid dimensions
hipDeviceAttributeCooperativeMultiDeviceUnmatchedBlockDim, // Supports cooperative launch on multiple
// devices with unmatched block dimensions
hipDeviceAttributeCooperativeMultiDeviceUnmatchedSharedMem, // Supports cooperative launch on multiple
// devices with unmatched shared memories
hipDeviceAttributeIsLargeBar, // Whether it is LargeBar
hipDeviceAttributeAsicRevision, // Revision of the GPU in this device
hipDeviceAttributeCanUseStreamWaitValue, // '1' if Device supports hipStreamWaitValue32() and
// hipStreamWaitValue64() , '0' otherwise.
hipDeviceAttributeAmdSpecificEnd = 19999,
hipDeviceAttributeVendorSpecificBegin = 20000, // Extended attributes for vendors
} hipDeviceAttribute_t;
```
# Known Issues in This Release
## Incorrect dGPU Behavior When Using AMDVBFlash Tool
The AMDVBFlash tool, used for flashing the VBIOS image to dGPU, does not communicate with the ROM Controller specifically when the driver is present. This is because the driver, as part of its runtime power management feature, puts the dGPU to a sleep state.
As a workaround, users can run `amdgpu.runpm=0`, which temporarily disables the runtime power management feature from the driver and dynamically changes some power control-related sysfs files.
## Issue with START Timestamp in ROCProfiler
Users may encounter an issue with the enabled timestamp functionality for monitoring one or multiple counters. ROCProfiler outputs the following four timestamps for each kernel:
- Dispatch
- Start
- End
- Complete
**Issue**
This defect is related to the Start timestamp functionality, which incorrectly shows an earlier time than the Dispatch timestamp.
To reproduce the issue,
1. Enable timing using the `--timestamp on` flag.
2. Use the `-i` option with the input filename that contains the name of the counter(s) to monitor.
3. Run the program.
4. Check the output result file.
**Current behavior**
BeginNS is lower than DispatchNS, which is incorrect.
**Expected behavior**
The correct order is:
_Dispatch < Start < End < Complete_
Users cannot use ROCProfiler to measure the time spent on each kernel because of the incorrect timestamp with counter collection enabled.
**Recommended Workaround**
Users are recommended to collect kernel execution timestamps without monitoring counters, as follows:
1. Enable timing using the `--timestamp on` flag, and run the application.
2. Rerun the application using the `-i` option with the input filename that contains the name of the counter(s) to monitor, and save this to a different output file using the `-o` flag.
3. Check the output result file from step 1.
4. The order of timestamps correctly displays as:
_DispathNS < BeginNS < EndNS < CompleteNS_
1. Users can find the values of the collected counters in the output file generated in step 2.
## Radeon Pro V620 and W6800 Workstation GPUs
### No Support for SMI and ROCDebugger on SRIOV
System Management Interface (SMI) and ROCDebugger are not supported in the SRIOV environment on any GPU. For more information, refer to the Systems Management Interface documentation.
# Deprecations and Warnings in This Release
## ROCm Libraries Changes Deprecations and Deprecation Removal
- The hipfft.h header is now provided only by the hipfft package. Up to ROCm 5.0, users would get hipfft.h in the rocfft package too.
- The GlobalPairwiseAMG class is now entirely removed, users should use the PairwiseAMG class instead.
- The rocsparse\_spmm signature in 5.0 was changed to match that of rocsparse\_spmm\_ex. In 5.0, rocsparse\_spmm\_ex is still present, but deprecated. Signature diff for rocsparse\_spmm
### _rocsparse\_spmm_ in 5.0
```c
rocsparse_status rocsparse_spmm(rocsparse_handle handle,
rocsparse_operation trans_A,
rocsparse_operation trans_B,
const void* alpha,
const rocsparse_spmat_descr mat_A,
const rocsparse_dnmat_descr mat_B,
const void* beta,
const rocsparse_dnmat_descr mat_C,
rocsparse_datatype compute_type,
rocsparse_spmm_alg alg,
rocsparse_spmm_stage stage,
size_t* buffer_size,
void* temp_buffer);
```
### _rocsparse\_spmm_ in 4.0
```c
rocsparse_status rocsparse_spmm(rocsparse_handle handle,
rocsparse_operation trans_A,
rocsparse_operation trans_B,
const void* alpha,
const rocsparse_spmat_descr mat_A,
const rocsparse_dnmat_descr mat_B,
const void* beta,
const rocsparse_dnmat_descr mat_C,
rocsparse_datatype compute_type,
rocsparse_spmm_alg alg,
size_t* buffer_size,
void* temp_buffer);
```
## HIP API Deprecations and Warnings
### Warning - Arithmetic Operators of HIP Complex and Vector Types
In this release, arithmetic operators of HIP complex and vector types are deprecated.
- As alternatives to arithmetic operators of HIP complex types, users can use arithmetic operators of std::complex types.
- As alternatives to arithmetic operators of HIP vector types, users can use the operators of the native clang vector type associated with the data member of HIP vector types.
During the deprecation, two macros `__HIP_ENABLE_COMPLEX_OPERATORS` and `__HIP_ENABLE_VECTOR_OPERATORS` are provided to allow users to conditionally enable arithmetic operators of HIP complex or vector types.
Note, the two macros are mutually exclusive and, by default, set to off.
The arithmetic operators of HIP complex and vector types will be removed in a future release.
Refer to the HIP API Guide for more information.
### Refactor of HIPCC/HIPCONFIG
In prior ROCm releases, by default, the hipcc/hipconfig Perl scripts were used to identify and set target compiler options, target platform, compiler, and runtime appropriately.
In ROCm v5.0, hipcc.bin and hipconfig.bin have been added as the compiled binary implementations of the hipcc and hipconfig. These new binaries are currently a work-in-progress, considered, and marked as experimental. ROCm plans to fully transition to hipcc.bin and hipconfig.bin in the a future ROCm release. The existing hipcc and hipconfig Perl scripts are renamed to hipcc.pl and hipconfig.pl respectively. New top-level hipcc and hipconfig Perl scripts are created, which can switch between the Perl script or the compiled binary based on the environment variable `HIPCC_USE_PERL_SCRIPT`.
In ROCm 5.0, by default, this environment variable is set to use hipcc and hipconfig through the Perl scripts.
Subsequently, Perl scripts will no longer be available in ROCm in a future release.
## Warning - Compiler-Generated Code Object Version 4 Deprecation
Support for loading compiler-generated code object version 4 will be deprecated in a future release with no release announcement and replaced with code object 5 as the default version.
The current default is code object version 4.
## Warning - MIOpenTensile Deprecation
MIOpenTensile will be deprecated in a future release.
Archived Documentation
----------------------
Older rocm documentation is archived at https://rocmdocs.amd.com.
# Disclaimer
The information presented in this document is for informational purposes only and may contain technical inaccuracies, omissions, and typographical errors. The information contained herein is subject to change and may be rendered inaccurate for many reasons, including but not limited to product and roadmap changes, component and motherboard versionchanges, new model and/or product releases, product differences between differing manufacturers, software changes, BIOS flashes, firmware upgrades, or the like. Any computer system has risks of security vulnerabilities that cannot be completely prevented or mitigated.AMD assumes no obligation to update or otherwise correct or revise this information. However, AMD reserves the right to revise this information and to make changes from time to time to the content hereof without obligation of AMD to notify any person of such revisions or changes.THIS INFORMATION IS PROVIDED AS IS.” AMD MAKES NO REPRESENTATIONS OR WARRANTIES WITH RESPECT TO THE CONTENTS HEREOF AND ASSUMES NO RESPONSIBILITY FOR ANY INACCURACIES, ERRORS, OR OMISSIONS THAT MAY APPEAR IN THIS INFORMATION. AMD SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT WILL AMD BE LIABLE TO ANY PERSON FOR ANY RELIANCE, DIRECT, INDIRECT, SPECIAL, OR OTHER CONSEQUENTIAL DAMAGES ARISING FROM THE USE OF ANY INFORMATION CONTAINED HEREIN, EVEN IF AMD IS EXPRESSLY ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.AMD, the AMD Arrow logo, and combinations thereof are trademarks of Advanced Micro Devices, Inc.Other product names used in this publication are for identification purposes only and may be trademarks of their respective companies.
©[2021]Advanced Micro Devices, Inc.All rights reserved.
## Third-party Disclaimer
Third-party content is licensed to you directly by the third party that owns the content and is not licensed to you by AMD. ALL LINKED THIRD-PARTY CONTENT IS PROVIDED “AS IS” WITHOUT A WARRANTY OF ANY KIND. USE OF SUCH THIRD-PARTY CONTENT IS DONE AT YOUR SOLE DISCRETION AND UNDER NO CIRCUMSTANCES WILL AMD BE LIABLE TO YOU FOR ANY THIRD-PARTY CONTENT. YOU ASSUME ALL RISK AND ARE SOLELY RESPONSIBLE FOR ANY DAMAGES THAT MAY ARISE FROM YOUR USE OF THIRD-PARTY CONTENT.

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MIT License
Copyright (c) 2022 Advanced Micro Devices, Inc. All rights reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
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# ROCm™ Repository Updates
This repository contains the manifest file for ROCm™ releases, changelogs, and release information. The file default.xml contains information for all repositories and the associated commit used to build the current ROCm release.
# AMD ROCm™ v4.3.1 Point Release Notes
The default.xml file uses the repo Manifest format.
This document describes the features, fixed issues, and information about downloading and installing the AMD ROCm™ software.
# ROCm v5.4 Release Notes
ROCm v5.4 is now released. For ROCm v5.4 documentation, refer to https://docs.amd.com.
It also covers known issues in this release.
# ROCm v5.3.3 Release Notes
ROCm v5.3.3 is now released. For ROCm v5.3.3 documentation, refer to https://docs.amd.com.
## List of Supported Operating Systems
# ROCm v5.3.2 Release Notes
ROCm v5.3.2 is now released. For ROCm v5.3.2 documentation, refer to https://docs.amd.com.
The AMD ROCm platform supports the following operating systems:
# ROCm v5.3 Release Notes
ROCm v5.3 is now released. For ROCm v5.3 documentation, refer to https://docs.amd.com.
![Screenshot](https://github.com/RadeonOpenCompute/ROCm/blob/master/images/SuppEnv.PNG)
# ROCm v5.2.3 Release Notes
The ROCm v5.2.3 patch release is now available. The details are listed below. Highlights of this release include enhancements in RCCL version compatibility and minor bug fixes in the HIP Runtime.
Additionally, ROCm releases will return to use of the [ROCm](https://github.com/RadeonOpenCompute/ROCm) repository for version-controlled release notes henceforth.
## What\'s New in This Release
**NOTE**: This release of ROCm is validated with the AMDGPU release v22.20.1.
The ROCm v4.3.1 release consists of the following enhancements:
All users of the ROCm v5.2.1 release and below are encouraged to upgrade. Refer to https://docs.amd.com for documentation associated with this release.
### Support for RHEL V8.4
This release extends support for RHEL v8.4.
## Introducing Preview Support for Ubuntu 20.04.5 HWE
### Support for SLES V15 Service Pack 3
Refer to the following article for information on the preview support for Ubuntu 20.04.5 HWE.
This release extends support for SLES v15 SP3.
https://www.amd.com/en/support/kb/release-notes/rn-amdgpu-unified-linux-22-20
### Pass Manager Update
In the AMD ROCm 4.3.1 release, the ROCm compiler uses the legacy pass manager, by default, to provide a better performance experience with some workloads.
## Changes in This Release
Previously, in ROCm v4.3, the default choice for the ROCm compiler was the new pass manager.
### Ubuntu 18.04 End of Life
For more information about legacy and new pass managers, see http://llvm.org.
Support for Ubuntu 18.04 ends in this release. Future releases of ROCm will not provide prebuilt packages for Ubuntu 18.04.
## Known Issues in This Release
### HIP and Other Runtimes
### General Userspace and Application Freeze on MI25
#### HIP Runtime
For some workloads on MI25, general user space and application freeze are observed, and the GPU resets intermittently. Note, the freeze may take hours to reproduce.
##### Fixes
This issue is under active investigation, and no workarounds are available currently.
- A bug was discovered in the HIP graph capture implementation in the ROCm v5.2.0 release. If the same kernel is called twice (with different argument values) in a graph capture, the implementation only kept the argument values for the second kernel call.
### hipRTC - File Not Found Error
- A bug was introduced in the hiprtc implementation in the ROCm v5.2.0 release. This bug caused the *hiprtcGetLoweredName* call to fail for named expressions with whitespace in it.
hipRTC may fail, and users may encounter the following error:
**Example:** The named expression ```my_sqrt<complex<double>>``` passed but ```my_sqrt<complex<double>>``` failed.
<built-in>:1:10: fatal error: '__clang_hip_runtime_wrapper.h' file not found
#include "__clang_hip_runtime_wrapper.h"
### ROCm Libraries
#### RCCL
#### Suggested Workarounds
* Set LLVM_PATH in the environment to <path to ROCm llvm>/llvm. Note, if ROCm is installed at the default location, then LLVM_PATH must be set to /opt/rocm/llvm.
* Add “-I <path to ROCm>/llvm/lib/clang/13.0.0/include/” to compiler options in the call to hiprtcCompileProgram (). Note, this workaround requires the following changes in the code:
// set NUM_OPTIONS to one more than the number of options that was previously required
const char* options[NUM_OPTIONS];
// fill other options[] here
std::string sarg = "-I/opt/rocm/llvm/lib/clang/13.0.0/include/";
options[NUM_OPTIONS - 1] = sarg.c_str();
hiprtcResult compileResult{hiprtcCompileProgram(prog, NUM_OPTIONS, options)};"
# AMD ROCm™ v4.3 Release Notes
This document describes the features, fixed issues, and information about downloading and installing the AMD ROCm™ software. It also covers known issues and deprecations in this release.
- [Supported Operating Systems and Documentation Updates](#Supported-Operating-Systems-and-Documentation-Updates)
* [Supported Operating Systems](#Supported-Operating-Systems)
* [ROCm Installation Updates](#ROCm-Installation-Updates)
* [AMD ROCm Documentation Updates](#AMD-ROCm-Documentation-Updates)
- [What\'s New in This Release](#Whats-New-in-This-Release)
* [HIP Enhancements](#HIP-Enhancements)
* [ROCm Data Center Tool](#ROCm-Data-Center-Tool)
* [ROCm Math and Communication Libraries](#ROCm-Math-and-Communication-Libraries)
* [ROCProfiler Enhancements](#ROCProfiler-Enhancements)
- [Known Issues in This Release](#Known-Issues-in-This-Release)
- [Hardware and Software Support](#Hardware-and-Software-Support)
- [Machine Learning and High Performance Computing Software Stack for AMD GPU](#Machine-Learning-and-High-Performance-Computing-Software-Stack-for-AMD-GPU)
* [ROCm Binary Package Structure](#ROCm-Binary-Package-Structure)
* [ROCm Platform Packages](#ROCm-Platform-Packages)
## ROCm Installation Updates
### Supported Operating Systems
The AMD ROCm platform is designed to support the following operating systems:
![Screenshot](https://github.com/RadeonOpenCompute/ROCm/blob/master/images/OSKernelupdated.PNG)
### Fresh Installation of AMD ROCM V4.3 Recommended
Complete uninstallation of previous ROCm versions is required before installing a new version of ROCm. **An upgrade from previous releases to AMD ROCm v4.3 is not supported**. For more information, refer to the AMD ROCm Installation Guide at
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
**Note**: AMD ROCm release v3.3 or prior releases are not fully compatible with AMD ROCm v3.5 and higher versions. You must perform a fresh ROCm installation if you want to upgrade from AMD ROCm v3.3 or older to 3.5 or higher versions and vice-versa.
**Note**: *render* group is required only for Ubuntu v20.04. For all other ROCm supported operating systems, continue to use video group.
* For ROCm v3.5 and releases thereafter, the clinfo path is changed to /opt/rocm/opencl/bin/clinfo.
* For ROCm v3.3 and older releases, the clinfo path remains /opt/rocm/opencl/bin/x86_64/clinfo.
## ROCm Multi-Version Installation Update
With the AMD ROCm v4.3 release, the following ROCm multi-version installation changes apply:
The meta packages rocm-dkms<version> are now deprecated for multi-version ROCm installs. For example, rocm-dkms3.7.0, rocm-dkms3.8.0.
* Multi-version installation of ROCm should be performed by installing rocm-dev<version> using each of the desired ROCm versions. For example, rocm-dev3.7.0, rocm-dev3.8.0, rocm-dev3.9.0.
* The rock-dkms loadable kernel modules should be installed using a single rock-dkms package.
* ROCm v3.9 and above will not set any ldconfig entries for ROCm libraries for multi-version installation. Users must set LD_LIBRARY_PATH to load the ROCm library version of choice.
**NOTE**: The single version installation of the ROCm stack remains the same. The rocm-dkms package can be used for single version installs and is not deprecated at this time.
## Support for Enviornment Modules
Environment modules are now supported. This enhancement in the ROCm v4.3 release enables users to switch between ROCm v4.2 and ROCm v4.3 easily and efficiently.
For more information about installing environment modules, refer to
https://modules.readthedocs.io/en/latest/
# AMD ROCm Documentation Updates
## AMD ROCm Installation Guide
The AMD ROCm Installation Guide in this release includes:
* Supported Environments
* Installation Instructions
* HIP Installation Instructions
For more information, refer to the ROCm documentation website at:
https://rocmdocs.amd.com/en/latest/
## AMD ROCm - HIP Documentation Updates
* HIP Programming Guide v4.3
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_HIP_Programming_Guide_v4.3.pdf
* HIP API Guide v4.3
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_HIP_API_Guide_v4.3.pdf
* HIP-Supported CUDA API Reference Guide v4.3
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_HIP_Supported_CUDA_API_Reference_Guide_v4.3.pdf
* **NEW** - AMD ROCm Compiler Reference Guide v4.3
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_Compiler_Reference_Guide_v4.3.pdf
* HIP FAQ
https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-FAQ.html#hip-faq
## ROCm Data Center User and API Guide
* ROCm Data Center Tool User Guide
- Prometheus (Grafana) Integration with Automatic Node Detection
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_DataCenter_Tool_User_Guide_v4.3.pdf
* ROCm Data Center Tool API Guide
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_RDC_API_Guide_v4.3.pdf
## ROCm SMI API Documentation Updates
* ROCm SMI API Guide
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_SMI_Guide_v4.3.pdf
## ROC Debugger User and API Guide
* ROC Debugger User Guide
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCDebugger_User_Guide.pdf
* Debugger API Guide
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCDebugger_API.pdf
## General AMD ROCm Documentation Links
Access the following links for more information:
* For AMD ROCm documentation, see
https://rocmdocs.amd.com/en/latest/
* For installation instructions on supped platforms, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
* For AMD ROCm binary structure, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Software-Stack-for-AMD-GPU.html
* For AMD ROCm Release History, see
https://rocmdocs.amd.com/en/latest/Current_Release_Notes/ROCm-Version-History.html
# What\'s New in This Release
## HIP Enhancements
### HIP Versioning Update
The HIP version definition is updated from the ROCm v4.2 release as follows:
##### Added
- Compatibility with NCCL 2.12.10
- Packages for test and benchmark executables on all supported OSes using CPack
- Adding custom signal handler - opt-in with RCCL_ENABLE_SIGNALHANDLER=1
- Additional details provided if Binary File Descriptor library (BFD) is pre-installed.
- Adding experimental support for using multiple ranks per device
- Requires using a new interface to create communicator (ncclCommInitRankMulti),
refer to the interface documentation for details.
- To avoid potential deadlocks, user might have to set an environment variables increasing
the number of hardware queues. For example,
```
HIP_VERSION=HIP_VERSION_MAJOR * 10000000 + HIP_VERSION_MINOR * 100000 +
HIP_VERSION_PATCH)
```
The HIP version can be queried from a HIP API call
```
hipRuntimeGetVersion(&runtimeVersion);
```
**Note**: The version returned will be greater than the version in previous ROCm releases.
### Support for Managed Memory Allocation
HIP now supports and automatically manages Heterogeneous Memory Management (HMM) allocation. The HIP application performs a capability check before making the managed memory API call hipMallocManaged.
**Note**: The _managed_ keyword is unsupported currently.
export GPU_MAX_HW_QUEUES=16
```
int managed_memory = 0;
HIPCHECK(hipDeviceGetAttribute(&managed_memory,
hipDeviceAttributeManagedMemory,p_gpuDevice));
if (!managed_memory ) {
printf ("info: managed memory access not supported on the device %d\n Skipped\n", p_gpuDevice);
}
else {
HIPCHECK(hipSetDevice(p_gpuDevice));
HIPCHECK(hipMallocManaged(&Hmm, N * sizeof(T)));
. . .
}
```
- Adding support for reusing ports in NET/IB channels
- Opt-in with NCCL_IB_SOCK_CLIENT_PORT_REUSE=1 and NCCL_IB_SOCK_SERVER_PORT_REUSE=1
- When "Call to bind failed: Address already in use" error happens in large-scale AlltoAll
(for example, >=64 MI200 nodes), users are suggested to opt-in either one or both of the options to resolve the massive port usage issue
- Avoid using NCCL_IB_SOCK_SERVER_PORT_REUSE when NCCL_NCHANNELS_PER_NET_PEER is tuned >1
### Kernel Enqueue Serialization
##### Removed
- Removed experimental clique-based kernels
Developers can control kernel command serialization from the host using the following environment variable,
AMD_SERIALIZE_KERNEL
* AMD_SERIALIZE_KERNEL = 1, Wait for completion before enqueue,
### Development Tools
No notable changes in this release for development tools, including the compiler, profiler, and debugger.
* AMD_SERIALIZE_KERNEL = 2, Wait for completion after enqueue,
* AMD_SERIALIZE_KERNEL = 3, Both.
This environment variable setting enables HIP runtime to wait for GPU idle before/after any GPU command.
### NUMA-aware Host Memory Allocation
The Non-Uniform Memory Architecture (NUMA) policy determines how memory is allocated and selects a CPU closest to each GPU.
NUMA also measures the distance between the GPU and CPU devices. By default, each GPU selects a Numa CPU node that has the least NUMA distance between them; the host memory is automatically allocated closest to the memory pool of the NUMA node of the current GPU device.
Note, using the *hipSetDevice* API with a different GPU provides access to the host allocation. However, it may have a longer NUMA distance.
### New Atomic System Scope Atomic Operations
HIP now provides new APIs with _system as a suffix to support system scope atomic operations. For example, atomicAnd atomic is dedicated to the GPU device, and atomicAnd_system allows developers to extend the atomic operation to system scope from the GPU device to other CPUs and GPU devices in the system.
For more information, refer to the HIP Programming Guide at,
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_HIP_Programming_Guide_v4.3.pdf
### Indirect Function Call and C++ Virtual Functions
While the new release of the ROCm compiler supports indirect function calls and C++ virtual functions on a device, there are some known limitations and issues.
**Limitations**
* An address to a function is device specific. Note, a function address taken on the host can not be used on a device, and a function address taken on a device can not be used on the host. On a system with multiple devices, an address taken on one device can not be used on a different device.
* C++ virtual functions only work on the device where the object was constructed.
* Indirect call to a device function with function scope shared memory allocation is not supported. For example, LDS.
* Indirect call to a device function defined in a source file different than the calling function/kernel is only supported when compiling the entire program with -fgpu-rdc.
**Known Issues in This Release**
* Programs containing kernels with different launch bounds may crash when making an indirect function call. This issue is due to a compiler issue miscalculating the register budget for the callee function.
* Programs may not work correctly when making an indirect call to a function that uses more resources. For example, scratch memory, shared memory, registers made available by the caller.
* Compiling a program with objects with pure or deleted virtual functions on the device will result in a linker error. This issue is due to the missing implementation of some C++ runtime functions on the device.
* Constructing an object with virtual functions in private or shared memory may crash the program due to a compiler issue when generating code for the constructor.
## ROCm Data Center Tool
### Prometheus (Grafana) Integration with Automatic Node Detection
The ROCm Data Center (RDC) tool enables you to use Consul to discover the rdc_prometheus service automatically. Consul is “a service mesh solution providing a full-featured control plane with service discovery, configuration, and segmentation functionality.” For more information, refer to their website at https://www.consul.io/docs/intro.
The ROCm Data Center Tool uses Consul for health checks of RDCs integration with the Prometheus plug-in (rdc_prometheus), and these checks provide information on its efficiency.
Previously, when a new compute node was added, users had to change prometheus_targets.json to use Consul manually. Now, with the Consul agent integration, a new compute node can be discovered automatically.
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_DataCenter_Tool_User_Guide_v4.3.pdf
### Coarse Grain Utilization
This feature provides a counter that displays the coarse grain GPU usage information, as shown below.
Sample output
```
$ rocm_smi.py --showuse
============================== % time GPU is busy =============================
GPU[0] : GPU use (%): 0
GPU[0] : GFX Activity: 3401
```
### Add 64-bit Energy Accumulator In-band
This feature provides an average value of energy consumed over time in a free-flowing RAPL counter, a 64-bit Energy Accumulator.
Sample output
```
$ rocm_smi.py --showenergycounter
=============================== Consumed Energy ================================
GPU[0] : Energy counter: 2424868
GPU[0] : Accumulated Energy (uJ): 0.0
```
### Support for Continuous Clocks Values
ROCm SMI will support continuous clock values instead of the previous discrete levels. Moving forward the updated sysfs file will consist of only MIN and MAX values and the user can set the clock value in the given range.
Sample output:
```
$ rocm_smi.py --setsrange 551 1270
Do you accept these terms? [y/N] y
============================= Set Valid sclk Range=======
GPU[0] : Successfully set sclk from 551(MHz) to 1270(MHz)
GPU[1] : Successfully set sclk from 551(MHz) to 1270(MHz)
=========================================================================
$ rocm_smi.py --showsclkrange
============================ Show Valid sclk Range======
GPU[0] : Valid sclk range: 551Mhz - 1270Mhz
GPU[1] : Valid sclk range: 551Mhz - 1270Mhz
```
### Memory Utilization Counters
This feature provides a counter display memory utilization information as shown below.
Sample output
```
$ rocm_smi.py --showmemuse
========================== Current Memory Use ==============================
GPU[0] : GPU memory use (%): 0
GPU[0] : Memory Activity: 0
```
### Performance Determinism
ROCm SMI supports performance determinism as a unique mode of operation. Performance variations are minimal as this enhancement allows users to control the entry and exit to set a soft maximum (ceiling) for the GFX clock.
Sample output
```
$ rocm_smi.py --setperfdeterminism 650
cat pp_od_clk_voltage
GFXCLK:
0: 500Mhz
1: 650Mhz *
2: 1200Mhz
$ rocm_smi.py --resetperfdeterminism
```
**Note**: The idle clock will not take up higher clock values if no workload is running. After enabling determinism, users can run a GFX workload to set performance determinism to the desired clock value in the valid range.
* GFX clock could either be less than or equal to the max value set in this mode. GFX clock will be at the max clock set in this mode only when required by the running workload.
* VDDGFX will be higher by an offset (75mv or so based on PPTable) in the determinism mode.
### HBM Temperature Metric Per Stack
This feature will enable ROCm SMI to report all HBM temperature values as shown below.
Sample output
```
$ rocm_smi.py showtemp
================================= Temperature =================================
GPU[0] : Temperature (Sensor edge) (C): 29.0
GPU[0] : Temperature (Sensor junction) (C): 36.0
GPU[0] : Temperature (Sensor memory) (C): 45.0
GPU[0] : Temperature (Sensor HBM 0) (C): 43.0
GPU[0] : Temperature (Sensor HBM 1) (C): 42.0
GPU[0] : Temperature (Sensor HBM 2) (C): 44.0
GPU[0] : Temperature (Sensor HBM 3) (C): 45.0
```
## ROCm Math and Communication Libraries
### rocBLAS
**Optimizations**
* Improved performance of non-batched and batched rocblas_Xgemv for gfx908 when m <= 15000 and n <= 15000
* Improved performance of non-batched and batched rocblas_sgemv and rocblas_dgemv for gfx906 when m <= 6000 and n <= 6000
* Improved the overall performance of non-batched and batched rocblas_cgemv for gfx906
* Improved the overall performance of rocblas_Xtrsv
For more information, refer to
https://rocblas.readthedocs.io/en/master/
### rocRAND
**Enhancements**
* gfx90a support added
* gfx1030 support added
* gfx803 supported re-enabled
**Fixed**
* Memory leaks in Poisson tests has been fixed.
* Memory leaks when generator has been created but setting seed/offset/dimensions display an exception has been fixed.
For more information, refer to
https://rocrand.readthedocs.io/en/latest/
### rocSOLVER
**Enhancements**
Linear solvers for general non-square systems:
* GELS now supports underdetermined and transposed cases
* Inverse of triangular matrices
* TRTRI (with batched and strided_batched versions)
* Out-of-place general matrix inversion
* GETRI_OUTOFPLACE (with batched and strided_batched versions)
* Argument names for the benchmark client now match argument names from the public API
**Fixed Issues**
* Known issues with Thin-SVD. The problem was identified in the test specification, not in the thin-SVD implementation or the rocBLAS gemm_batched routines.
* Benchmark client longer crashes as a result of leading dimension or stride arguments not being provided on the command line.
**Optimizations**
* Improved general performance of matrix inversion (GETRI)
For more information, refer to
https://rocsolver.readthedocs.io/en/latest/
### rocSPARSE
**Enhancements**
* (batched) tridiagonal solver with and without pivoting
* dense matrix sparse vector multiplication (gemvi)
* support for gfx90a
* sampled dense-dense matrix multiplication (sddmm)
**Improvements**
* client matrix download mechanism
* boost dependency in clients removed
For more information, refer to
https://rocsparse.readthedocs.io/en/latest/usermanual.html#rocsparse-gebsrmv
### hipBLAS
**Enhancements**
* Added *hipblasStatusToString*
**Fixed**
* Added catch() blocks around API calls to prevent the leak of C++ exceptions
### rocFFT
**Changes**
* Re-split device code into single-precision, double-precision, and miscellaneous kernels.
**Fixed Issues**
* double-precision planar->planar transpose.
* 3D transforms with unusual strides, for SBCC-optimized sizes.
* Improved buffer placement logic.
For more information, refer to
https://rocfft.readthedocs.io/en/rocm-4.3.0/
### hipFFT
**Fixed Issues**
* CMAKE updates
* Added callback API in hipfftXt.h header.
### rocALUTION
**Enhancements**
* Support for gfx90a target
* Support for gfx1030 target
**Improvements**
* Install script
For more information, refer to
### rocTHRUST
**Enhancements**
* Updated to match upstream Thrust 1.11
* gfx90a support added
* gfx803 support re-enabled
hipCUB
Enhancements
* DiscardOutputIterator to backend header
## ROCProfiler Enhancements
### Tracing Multiple MPI Ranks
When tracing multiple MPI ranks in ROCm v4.3, users must use the form:
```
mpirun ... <mpi args> ... rocprof ... <rocprof args> ... application ... <application args>
```
**NOTE**: This feature differs from ROCm v4.2 (and lower), which used "rocprof ... mpirun ... application".
This change was made to enable ROCProfiler to handle process forking better and launching via mpirun (and related) executables.
From a user perspective, this new execution mode requires:
1. Generation of trace data per MPI (or process) rank.
2. Use of a new ["merge_traces.sh" utility script](https://github.com/ROCm-Developer-Tools/rocprofiler/blob/rocm-4.3.x/bin/merge_traces.sh) to combine traces from multiple processes into a unified trace for profiling.
For example, to accomplish step #1, ROCm provides a simple bash wrapper that demonstrates how to generate a unique output directory per process:
```
$ cat wrapper.sh
#! /usr/bin/env bash
if [[ -n ${OMPI_COMM_WORLD_RANK+z} ]]; then
# mpich
export MPI_RANK=${OMPI_COMM_WORLD_RANK}
elif [[ -n ${MV2_COMM_WORLD_RANK+z} ]]; then
# ompi
export MPI_RANK=${MV2_COMM_WORLD_RANK}
fi
args="$*"
pid="$$"
outdir="rank_${pid}_${MPI_RANK}"
outfile="results_${pid}_${MPI_RANK}.csv"
eval "rocprof -d ${outdir} -o ${outdir}/${outfile} $*"
```
This script:
* Determines the global MPI rank (implemented here for OpenMPI and MPICH only)
* Determines the process id of the MPI rank
* Generates a unique output directory using the two
To invoke this wrapper, use the following command:
```
mpirun <mpi args> ./wrapper.sh --hip-trace <application> <args>
```
This generates an output directory for each used MPI rank. For example,
```
$ ls -ld rank_* | awk {'print $5" "$9'}
4096 rank_513555_0
4096 rank_513556_1
```
Finally, these traces may be combined using the [merge traces script](https://github.com/ROCm-Developer-Tools/rocprofiler/blob/rocm-4.3.x/bin/merge_traces.sh). For example,
```
$ ./merge_traces.sh -h
Script for aggregating results from multiple rocprofiler out directries.
Full path: /opt/rocm/bin/merge_traces.sh
Usage:
merge_traces.sh -o <outputdir> [<inputdir>...]
```
Use the following input arguments to the merge_traces.sh script to control which traces are merged and where the resulting merged trace is saved.
* -o <*outputdir*> - output directory where the results are aggregated.
* <*inputdir*>... - space-separated list of rocprofiler directories. If not specified, CWD is used.
For example, if an output directory named "unified" was supplied to the `merge_traces.sh` script, the file 'unified/results.json' will be generated, and the contains trace data from both MPI ranks.
Known issue for ROCProfiler
Collecting several counter collection passes (multiple "pmc:" lines in an counter input file) is not supported in a single run.
The workaround is to break the multiline counter input file into multiple single-line counter input files and execute runs.
# Known Issues in This Release
The following are the known issues in this release.
## Upgrade to AMD ROCm v4.3 Not Supported
An upgrade from previous releases to AMD ROCm v4.2 is not supported. Complete uninstallation of previous ROCm versions is required before installing a new version of ROCm.
## _LAUNCH BOUNDS_Ignored During Kernel Launch
The HIP runtime returns the hipErrorLaunchFailure error code when an application tries to launch kernel with a block size larger than the launch bounds mentioned during compile time. If no launch bounds were specified during the compile time, the default value of 1024 is assumed. Refer to the HIP trace for more information about the failing kernel. A sample error in the trace is shown below:
Snippet of the HIP trace
```
:3:devprogram.cpp :2504: 2227377746776 us: Using Code Object V4.
:3:hip_module.cpp :361 : 2227377768546 us: 7670 : [7f7c6eddd180] ihipModuleLaunchKernel ( 0x0x16fe080, 2048, 1, 1, 1024, 1, 1, 0, stream:<null>, 0x7ffded8ad260, char array:<null>, event:0, event:0, 0, 0 )
:1:hip_module.cpp :254 : 2227377768572 us: Launch params (1024, 1, 1) are larger than launch bounds (64) for kernel _Z8MyKerneliPd
:3:hip_platform.cpp :667 : 2227377768577 us: 7670 : [7f7c6eddd180] ihipLaunchKernel: Returned hipErrorLaunchFailure :
:3:hip_module.cpp :493 : 2227377768581 us: 7670 : [7f7c6eddd180] hipLaunchKernel: Returned hipErrorLaunchFailure :
```
There is no known workaround at this time.
## PYCACHE Folder Exists After ROCM SMI Library Uninstallation
Users may observe that the /opt/rocm-x/bin/__pycache__ folder continues to exist even after the rocm_smi_lib uninstallation.
Workaround: Delete the /opt/rocm-x/bin/__pycache__ folder manually before uninstalling rocm_smi_lib.
# Deploying ROCm
AMD hosts both Debian and RPM repositories for the ROCm packages.
For more information on ROCM installation on all platforms, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
# Machine Learning and High Performance Computing Software Stack for AMD GPU
For an updated version of the software stack for AMD GPU, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#software-stack-for-amd-gpu
# Hardware and Software Support
ROCm is focused on using AMD GPUs to accelerate computational tasks such as machine learning, engineering workloads, and scientific computing.
In order to focus our development efforts on these domains of interest, ROCm supports a targeted set of hardware configurations which are detailed further in this section.
**Note:** The AMD ROCm™ open software platform is a compute stack for headless system deployments. GUI-based software applications are currently not supported.
#### Supported GPUs
Because the ROCm Platform has a focus on particular computational domains, we offer official support for a selection of AMD GPUs that are designed to offer good performance and price in these domains.
**Note:** The integrated GPUs of Ryzen are not officially supported targets for ROCm.
ROCm officially supports AMD GPUs that use following chips:
* GFX9 GPUs
- "Vega 10" chips, such as on the AMD Radeon RX Vega 64 and Radeon Instinct MI25
- "Vega 7nm" chips, such as on the Radeon Instinct MI50, Radeon Instinct MI60 or AMD Radeon VII, Radeon Pro VII
* CDNA GPUs
- MI100 chips such as on the AMD Instinct™ MI100
ROCm is a collection of software ranging from drivers and runtimes to libraries and developer tools.
Some of this software may work with more GPUs than the "officially supported" list above, though AMD does not make any official claims of support for these devices on the ROCm software platform.
The following list of GPUs are enabled in the ROCm software, though full support is not guaranteed:
* GFX8 GPUs
* "Polaris 11" chips, such as on the AMD Radeon RX 570 and Radeon Pro WX 4100
* "Polaris 12" chips, such as on the AMD Radeon RX 550 and Radeon RX 540
* GFX7 GPUs
* "Hawaii" chips, such as the AMD Radeon R9 390X and FirePro W9100
As described in the next section, GFX8 GPUs require PCI Express 3.0 (PCIe 3.0) with support for PCIe atomics. This requires both CPU and motherboard support. GFX9 GPUs require PCIe 3.0 with support for PCIe atomics by default, but they can operate in most cases without this capability.
The integrated GPUs in AMD APUs are not officially supported targets for ROCm.
As described [below](#limited-support), "Carrizo", "Bristol Ridge", and "Raven Ridge" APUs are enabled in our upstream drivers and the ROCm OpenCL runtime.
However, they are not enabled in the HIP runtime, and may not work due to motherboard or OEM hardware limitations.
As such, they are not yet officially supported targets for ROCm.
For a more detailed list of hardware support, please see [the following documentation](https://en.wikipedia.org/wiki/List_of_AMD_graphics_processing_units).
#### Supported CPUs
As described above, GFX8 GPUs require PCIe 3.0 with PCIe atomics in order to run ROCm.
In particular, the CPU and every active PCIe point between the CPU and GPU require support for PCIe 3.0 and PCIe atomics.
The CPU root must indicate PCIe AtomicOp Completion capabilities and any intermediate switch must indicate PCIe AtomicOp Routing capabilities.
Current CPUs which support PCIe Gen3 + PCIe Atomics are:
* AMD Ryzen CPUs
* The CPUs in AMD Ryzen APUs
* AMD Ryzen Threadripper CPUs
* AMD EPYC CPUs
* Intel Xeon E7 v3 or newer CPUs
* Intel Xeon E5 v3 or newer CPUs
* Intel Xeon E3 v3 or newer CPUs
* Intel Core i7 v4, Core i5 v4, Core i3 v4 or newer CPUs (i.e. Haswell family or newer)
* Some Ivy Bridge-E systems
Beginning with ROCm 1.8, GFX9 GPUs (such as Vega 10) no longer require PCIe atomics.
We have similarly opened up more options for number of PCIe lanes.
GFX9 GPUs can now be run on CPUs without PCIe atomics and on older PCIe generations, such as PCIe 2.0.
This is not supported on GPUs below GFX9, e.g. GFX8 cards in the Fiji and Polaris families.
If you are using any PCIe switches in your system, please note that PCIe Atomics are only supported on some switches, such as Broadcom PLX.
When you install your GPUs, make sure you install them in a PCIe 3.1.0 x16, x8, x4, or x1 slot attached either directly to the CPU's Root I/O controller or via a PCIe switch directly attached to the CPU's Root I/O controller.
In our experience, many issues stem from trying to use consumer motherboards which provide physical x16 connectors that are electrically connected as e.g. PCIe 2.0 x4, PCIe slots connected via the Southbridge PCIe I/O controller, or PCIe slots connected through a PCIe switch that does
not support PCIe atomics.
If you attempt to run ROCm on a system without proper PCIe atomic support, you may see an error in the kernel log (`dmesg`):
```
kfd: skipped device 1002:7300, PCI rejects atomics
```
Experimental support for our Hawaii (GFX7) GPUs (Radeon R9 290, R9 390, FirePro W9100, S9150, S9170)
does not require or take advantage of PCIe Atomics. However, we still recommend that you use a CPU
from the list provided above for compatibility purposes.
#### Not supported or limited support under ROCm
##### Limited support
* ROCm 4.x should support PCIe 2.0 enabled CPUs such as the AMD Opteron, Phenom, Phenom II, Athlon, Athlon X2, Athlon II and older Intel Xeon and Intel Core Architecture and Pentium CPUs. However, we have done very limited testing on these configurations, since our test farm has been catering to CPUs listed above. This is where we need community support. _If you find problems on such setups, please report these issues_.
* Thunderbolt 1, 2, and 3 enabled breakout boxes should now be able to work with ROCm. Thunderbolt 1 and 2 are PCIe 2.0 based, and thus are only supported with GPUs that do not require PCIe 3.1.0 atomics (e.g. Vega 10). However, we have done no testing on this configuration and would need community support due to limited access to this type of equipment.
* AMD "Carrizo" and "Bristol Ridge" APUs are enabled to run OpenCL, but do not yet support HIP or our libraries built on top of these compilers and runtimes.
* As of ROCm 2.1, "Carrizo" and "Bristol Ridge" require the use of upstream kernel drivers.
* In addition, various "Carrizo" and "Bristol Ridge" platforms may not work due to OEM and ODM choices when it comes to key configurations parameters such as inclusion of the required CRAT tables and IOMMU configuration parameters in the system BIOS.
* Before purchasing such a system for ROCm, please verify that the BIOS provides an option for enabling IOMMUv2 and that the system BIOS properly exposes the correct CRAT table. Inquire with your vendor about the latter.
* AMD "Raven Ridge" APUs are enabled to run OpenCL, but do not yet support HIP or our libraries built on top of these compilers and runtimes.
* As of ROCm 2.1, "Raven Ridge" requires the use of upstream kernel drivers.
* In addition, various "Raven Ridge" platforms may not work due to OEM and ODM choices when it comes to key configurations parameters such as inclusion of the required CRAT tables and IOMMU configuration parameters in the system BIOS.
* Before purchasing such a system for ROCm, please verify that the BIOS provides an option for enabling IOMMUv2 and that the system BIOS properly exposes the correct CRAT table. Inquire with your vendor about the latter.
##### Not supported
* "Tonga", "Iceland", "Vega M", and "Vega 12" GPUs are not supported.
* We do not support GFX8-class GPUs (Fiji, Polaris, etc.) on CPUs that do not have PCIe 3.0 with PCIe atomics.
* As such, we do not support AMD Carrizo and Kaveri APUs as hosts for such GPUs.
* Thunderbolt 1 and 2 enabled GPUs are not supported by GFX8 GPUs on ROCm. Thunderbolt 1 & 2 are based on PCIe 2.0.
In the default ROCm configuration, GFX8 and GFX9 GPUs require PCI Express 3.0 with PCIe atomics. The ROCm platform leverages these advanced capabilities to allow features such as user-level submission of work from the host to the GPU. This includes PCIe atomic Fetch and Add, Compare and Swap, Unconditional Swap, and AtomicOp Completion.
#### ROCm support in upstream Linux kernels
As of ROCm 1.9.0, the ROCm user-level software is compatible with the AMD drivers in certain upstream Linux kernels.
As such, users have the option of either using the ROCK kernel driver that are part of AMD's ROCm repositories or using the upstream driver and only installing ROCm user-level utilities from AMD's ROCm repositories.
These releases of the upstream Linux kernel support the following GPUs in ROCm:
* 4.17: Fiji, Polaris 10, Polaris 11
* 4.18: Fiji, Polaris 10, Polaris 11, Vega10
* 4.20: Fiji, Polaris 10, Polaris 11, Vega10, Vega 7nm
The upstream driver may be useful for running ROCm software on systems that are not compatible with the kernel driver available in AMD's repositories.
For users that have the option of using either AMD's or the upstreamed driver, there are various tradeoffs to take into consideration:
| | Using AMD's `rock-dkms` package | Using the upstream kernel driver |
| ---- | ------------------------------------------------------------| ----- |
| Pros | More GPU features, and they are enabled earlier | Includes the latest Linux kernel features |
| | Tested by AMD on supported distributions | May work on other distributions and with custom kernels |
| | Supported GPUs enabled regardless of kernel version | |
| | Includes the latest GPU firmware | |
| Cons | May not work on all Linux distributions or versions | Features and hardware support varies depending on kernel version |
| | Not currently supported on kernels newer than 5.4 | Limits GPU's usage of system memory to 3/8 of system memory (before 5.6). For 5.6 and beyond, both DKMS and upstream kernels allow use of 15/16 of system memory. |
| | | IPC and RDMA capabilities are not yet enabled |
| | | Not tested by AMD to the same level as `rock-dkms` package |
| | | Does not include most up-to-date firmware |
# Disclaimer
AMD®, the AMD Arrow logo, AMD Instinct™, Radeon™, ROCm® and combinations thereof are trademarks of Advanced Micro Devices, Inc.
Linux® is the registered trademark of Linus Torvalds in the U.S. and other countries.
PCIe® is a registered trademark of PCI-SIG Corporation. Other product names used in this publication are for identification purposes only and may be trademarks of their respective companies.
Google® is a registered trademark of Google LLC.
Ubuntu and the Ubuntu logo are registered trademarks of Canonical Ltd.
Other product names used in this publication are for identification purposes only and may be trademarks of their respective companies.
### Deployment and Management Tools
No notable changes in this release for deployment and management tools.
## Older ROCm™ Releases
For release information for older ROCm™ releases, refer to [CHANGELOG](CHANGELOG.md).

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@@ -1,7 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<manifest>
<remote name="roc-github"
fetch="http://github.com/RadeonOpenCompute/" />
fetch="https://github.com/RadeonOpenCompute/" />
<remote name="rocm-devtools"
fetch="https://github.com/ROCm-Developer-Tools/" />
<remote name="rocm-swplat"
@@ -12,7 +12,7 @@ fetch="https://github.com/GPUOpen-ProfessionalCompute-Libraries/" />
fetch="https://github.com/GPUOpen-Tools/" />
<remote name="KhronosGroup"
fetch="https://github.com/KhronosGroup/" />
<default revision="refs/tags/rocm-4.3.1"
<default revision="refs/tags/rocm-5.4.0"
remote="roc-github"
sync-c="true"
sync-j="4" />
@@ -30,9 +30,11 @@ fetch="https://github.com/KhronosGroup/" />
<project name="clang-ocl" />
<!--HIP Projects-->
<project name="HIP" remote="rocm-devtools" />
<project name="hipamd" remote="rocm-devtools" />
<project name="HIP-Examples" remote="rocm-devtools" />
<project name="ROCclr" remote="rocm-devtools" />
<project name="HIPIFY" remote="rocm-devtools" />
<project name="HIPCC" remote="rocm-devtools" />
<!-- The following projects are all associated with the AMDGPU LLVM compiler -->
<project name="llvm-project" />
<project name="ROCm-Device-Libs" />
@@ -46,7 +48,7 @@ fetch="https://github.com/KhronosGroup/" />
<project name="ROCgdb" remote="rocm-devtools" />
<project name="ROCdbgapi" remote="rocm-devtools" />
<!-- ROCm Libraries -->
<project name="rdc" remote="roc-github" />
<project name="rdc" />
<project name="rocBLAS" remote="rocm-swplat" />
<project name="Tensile" remote="rocm-swplat" />
<project name="hipBLAS" remote="rocm-swplat" />
@@ -55,6 +57,7 @@ fetch="https://github.com/KhronosGroup/" />
<project name="rocRAND" remote="rocm-swplat" />
<project name="rocSPARSE" remote="rocm-swplat" />
<project name="rocSOLVER" remote="rocm-swplat" />
<project name="hipSOLVER" remote="rocm-swplat" />
<project name="hipSPARSE" remote="rocm-swplat" />
<project name="rocALUTION" remote="rocm-swplat" />
<project name="MIOpenGEMM" remote="rocm-swplat" />
@@ -64,6 +67,7 @@ fetch="https://github.com/KhronosGroup/" />
<project name="rocThrust" remote="rocm-swplat" />
<project name="hipCUB" remote="rocm-swplat" />
<project name="rocPRIM" remote="rocm-swplat" />
<project name="rocWMMA" remote="rocm-swplat" />
<project name="hipfort" remote="rocm-swplat" />
<project name="AMDMIGraphX" remote="rocm-swplat" />
<project name="ROCmValidationSuite" remote="rocm-devtools" />

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