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Lad, Aditya
86a09b146b Remove MiGraphX from 3.8 2020-09-25 10:05:32 -07:00
Lad, Aditya
d1f9aa98a3 hipfort addition to 3.8 2020-09-22 11:38:23 -07:00
Lad, Aditya
42fa0e0765 Remove version_history.md file. Since we are currently maintaining it on external documentation. 2020-09-21 16:04:25 -07:00
Lad, Aditya
e89903ed3a ROCm release 3.8 2020-09-21 15:58:09 -07:00
Roopa Malavally
ba2e1f0109 ROCm v3.8 Release Notes (#1226)
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Roopa Malavally
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Roopa Malavally
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Roopa Malavally
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Roopa Malavally
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Roopa Malavally
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Roopa Malavally
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Lad, Aditya
67f7748999 ROCm 3.7 : Default.xml 2020-08-20 20:27:43 -04:00
Roopa Malavally
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Roopa Malavally
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Roopa Malavally
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Roopa Malavally
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Roopa Malavally
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Roopa Malavally
e3017948a9 Delete AMD_ROCm_Release_Notes_v3.5.1.pdf 2020-06-19 17:02:21 -07:00
Roopa Malavally
09643c4a90 Update README.md 2020-06-19 16:48:56 -07:00
Lad, Aditya
8c835d14fc Manifest files : ROCm 3.5.1 2020-06-19 19:44:07 -04:00
Roopa Malavally
25dea0df9f Update README.md 2020-06-19 16:39:17 -07:00
Roopa Malavally
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Roopa Malavally
cc37d13828 Update README.md 2020-06-03 12:43:24 -07:00
Lad, Aditya
63ed31781d rocSOLVER tag update 2020-06-03 14:04:42 -04:00
Roopa Malavally
5502ce3c41 Update README.md 2020-06-02 20:43:44 -07:00
Lad, Aditya
2adb254db3 ROCm 3.5 Manifest File 2020-06-02 20:14:25 -04:00
Roopa Malavally
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Roopa Malavally
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Roopa Malavally
4eddbb0f2f AMD ROCm Release Notes v3.5.0 (#1123)
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Roopa Malavally
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Aditya Lad
d6ebde1c2b Merge pull request #1066 from adilad/master
ROCm release 3.3 Manifest File
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Lad, Aditya
c270440e1d ROCm release 3.3 Manifest File 2020-04-01 18:41:52 -04:00
Aditya Lad
87212e992e Merge pull request #1065 from Rmalavally/master
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Roopa Malavally
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Roopa Malavally
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# AMD ROCm Release Notes v3.1.0
# AMD ROCm Release Notes v3.8.0
This page describes the features, fixed issues, and information about downloading and installing the ROCm software.
It also covers known issues and deprecated features in the ROCm v3.1 release.
It also covers known issues in this release.
- [What Is ROCm?](#What-Is-ROCm)
* [ROCm Components](#ROCm-Components)
- [Supported Operating Systems and Documentation Updates](#Supported-Operating-Systems-and-Documentation-Updates)
* [Supported Operating Systems](#Supported-Operating-Systems)
* [Important ROCm Links](#Important-ROCm-Links)
* [AMD ROCm Documentation Updates](#AMD-ROCm-Documentation-Updates)
- [What\'s New in This Release](#Whats-New-in-This-Release)
* [Change in ROCm Installation Directory Structure](#Change-in-ROCm-Installation-Directory-Structure)
* [Reliability, Accessibility, and Serviceability Support for Vega7nm](#Reliability-Accessibility-and-Serviceability-Support-for-Vega7nm)
* [SLURM Support for AMD GPU](#SLURM-Support-for-AMD-GPU)
* [Hipfort-Interface for GPU Kernel Libraries](#Hipfort-Interface-for-GPU-Kernel-Libraries)
* [ROCm Data Center Tool](#ROCm-Data-Center-Tool)
* [Error-Correcting Code Fields in ROCm Data Center Tool](#Error-Correcting-Code-Fields-in-ROCm-Data-Center-Tool)
* [Static Linking Libraries](#Static-Linking-Libraries)
- [Fixed Defects](#Fixed-Defects)
- [Known Issues](#Known-Issues)
* [MIVision MIGraphX Installation](#MIVision-MIGraphX-Installation)
* [Using TensorFlow](#Using-TensorFlow)
* [HIP Compiler Dependency Issue](#HIP-Compiler-Dependency-Issue)
* [Error Running ROC Profiler](#Error-Running-ROC-Profiler)
- [Deploying ROCm](#Deploying-ROCm)
* [Ubuntu](#Ubuntu)
* [CentOS RHEL v7](#CentOS-RHEL-v7)
* [SLES 15 Service Pack 1](#SLES-15-Service-Pack-1)
- [Getting the ROCm Source Code](#Getting-the-ROCm-Source-Code)
- [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)
## What Is ROCm?
ROCm is designed to be a universal platform for gpu-accelerated computing. This modular design allows hardware vendors to build drivers that support the ROCm framework. ROCm is also designed to integrate multiple programming languages and makes it easy to add support for other languages.
Note: You can also clone the source code for individual ROCm components from the GitHub repositories.
# Supported Operating Systems
## Support for Vega 7nm Workstation
### ROCm Components
The following components for the ROCm platform are released and available for the v3.1
release:
This release extends support to the Vega 7nm Workstation (Vega20 GL-XE) version.
• Drivers
## List of Supported Operating Systems
• Tools
The AMD ROCm platform is designed to support the following operating systems:
• Libraries
* Ubuntu 20.04 (5.4 and 5.6-oem) and 18.04.5 (Kernel 5.4)
* CentOS 7.8 & RHEL 7.8 (Kernel 3.10.0-1127) (Using devtoolset-7 runtime support)
* CentOS 8.2 & RHEL 8.2 (Kernel 4.18.0 ) (devtoolset is not required)
* SLES 15 SP1
• Source Code
## Fresh Installation of AMD ROCm v3.8 Recommended
A fresh and clean installation of AMD ROCm v3.8 is recommended. An upgrade from previous releases to AMD ROCm v3.8 is not supported.
You can access the latest supported version of drivers, tools, libraries, and source code for the ROCm platform at the following location:
https://github.com/RadeonOpenCompute/ROCm
For more information, refer to the AMD ROCm Installation Guide at:
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
### Supported Operating Systems
The ROCm v3.1.x platform is designed to support the following operating systems:
**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*.
* Ubuntu 16.04.6(Kernel 4.15) and 18.04.3(Kernel 5.3)
* For ROCm v3.5 and releases thereafter,the *clinfo* path is changed to - */opt/rocm/opencl/bin/clinfo*.
* CentOS v7.7 (Using devtoolset-7 runtime support)
* For ROCm v3.3 and older releases, the *clinfo* path remains unchanged - */opt/rocm/opencl/bin/x86_64/clinfo*.
* RHEL v7.7 (Using devtoolset-7 runtime support)
* SLES 15 SP1
# AMD ROCm Documentation Updates
## AMD ROCm Installation Guide
For details about deploying the ROCm v3.1.0.x on these operating systems, see the Deploying ROCm section later in the document.
The AMD ROCm Installation Guide in this release includes:
### Important ROCm Links
* Updated Supported Environments
* HIP Installation Instructions
* Tensorflow ROCm Port: Basic Installations on RHEL v8.2
Access the following links for more information on:
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
* ROCm documentation, see
https://rocm-documentation.readthedocs.io/en/latest/index.html
## AMD ROCm - HIP Documentation Updates
* ROCm binary structure, see
https://github.com/RadeonOpenCompute/ROCm/blob/master/README.md#rocm-binary-package-structure
* HIP Repository Information
* Common ROCm installation issues, see
https://rocm.github.io/install_issues.html
For more information, see
* Instructions to install PyTorch after ROCm is installed https://rocm-documentation.readthedocs.io/en/latest/Deep_learning/Deep-learning.html#pytorch
https://rocmdocs.amd.com/en/latest/Programming_Guides/Programming-Guides.html#hip-repository-information
Note: These instructions reference the rocm/pytorch:rocm3.0_ubuntu16.04_py2.7_pytorch image. However, you can substitute the Ubuntu 18.04 image listed at https://hub.docker.com/r/rocm/pytorch/tags
## ROCm Data Center Tool User Guide
* Error-Correction Codes Field and Output Documentation
## What\'s New in This Release
For more information, refer to the AMD ROCm Data Center User Guide at
### Change in ROCm Installation Directory Structure
A fresh installation of the ROCm toolkit installs the packages in the */opt/rocm-\<version>* folder.
Previously, ROCm toolkit packages were installed in the */opt/rocm* folder.
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_DataCenter_Tool_User_Guide.pdf
![ScreenShot](Versionchange1.png)
## General AMD ROCm Documentation Links
## Reliability, Accessibility, and Serviceability Support for Vega7nm
The Reliability, Accessibility, and Serviceability (RAS) support for Vega7nm is now available. The support includes:
Access the following links for more information:
* UMC RAS HBM ECC (uncorrectable error injection), page retirement, RAS recovery via GPU (BACO) reset
* GFX RAS GFX, MMHUB ECC (uncorrectable error injection), RAS recovery via GPU (BACO) reset
* PCIE RAS PCIE_BIF ECC (uncorrectable error injection), RAS recovery via GPU (BACO) reset
* For AMD ROCm documentation, see
## SLURM Support for AMD GPU
SLURM (Simple Linux Utility for Resource Management) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters. The latest version 20.02.0 of SLURM includes AMD plugins that enable SLURM to detect and configure AMD GPUs automatically. It also collects and reports the energy consumption of AMD GPUs.
https://rocmdocs.amd.com/en/latest/
* For installation instructions on supped platforms, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
## Known Issues
* For AMD ROCm binary structure, see
### MIVision MIGraphX Installation
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#build-amd-rocm
* Install and use the latest version of the MIVision/MIGraphX code.
* Ensure the /opt/rocm symbolic link for the new version of ROCm is present and points to the right version of the ROCm toolkit.
* For AMD ROCm Release History, see
### Using TensorFlow
The TensorFlow build system requires the following additional changes to support the new installation path:
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#amd-rocm-version-history
* Ensure the /opt/rocm symbolic link is preset and points to the right version of the ROCm toolkit.
* Modify the build configure file to include the header files from the respective ROCm version-specific folder
### HIP Compiler Dependency Issue
If the HIP compiler has a dependency on /opt/rocm, use the following workaround:
* Ensure the /opt/rocm symbolic link points to the right version of the ROCm software
* Use the ROCM_PATH environment variable that points to the version of the ROCm software installed on the system.
* Use the rocm-dkms package to install required ROCm components.
# What\'s New in This Release
### Error Running ROC Profiler
**Issue:** Running ROC profiler results in the following error -
“: hip / hsa trace due to "ImportError: No module named sqlite3" error”
## Hipfort-Interface for GPU Kernel Libraries
**Workaround:** Export the Python version before running ROC profiler:
Hipfort is an interface library for accessing GPU Kernels. It provides support to the AMD ROCm architecture from within the Fortran programming language. Currently, the gfortran and HIP-Clang compilers support hipfort. Note, the gfortran compiler belongs to the GNU Compiler Collection (GCC). While hipfc wrapper calls hipcc for the non-fortran kernel source, gfortran is used for FORTRAN applications that call GPU kernels.
*export ROCP_PYTHON_VERSION=<python version>*
*ex: export ROCP_PYTHON_VERSION=python3*
The hipfort interface library is meant for Fortran developers with a focus on gfortran users.
For information on HIPFort installation and examples, see
https://github.com/ROCmSoftwarePlatform/hipfort
## Deploying ROCm
AMD hosts both Debian and RPM repositories for the ROCm v3.1.0x packages.
## ROCm Data Center Tool
The following directions show how to install ROCm on supported Debian-based systems such as Ubuntu 18.04.x.
The ROCm™ Data Center Tool™ simplifies the administration and addresses key infrastructure challenges in AMD GPUs in cluster and datacenter environments. The important features of this tool are:
Note: These directions may not work as written on unsupported Debian-based distributions. For example, newer versions of Ubuntu may not be compatible with the rock-dkms kernel driver. In this case, you can exclude the rocm-dkms and rock-dkms packages.
* GPU telemetry
For more information on the ROCm binary structure, see
https://github.com/RadeonOpenCompute/ROCm/blob/master/README.md#rocm-binary-package-structure
* GPU statistics for jobs
For information about upstream kernel drivers, see the Using Debian-based ROCm with Upstream Kernel Drivers section.
* Integration with third-party tools
## Ubuntu
### Installing a ROCm Package from a Debian Repository
To install from a Debian Repository:
1. Run the following code to ensure that your system is up to date:
sudo apt update
sudo apt dist-upgrade
sudo apt install libnuma-dev
sudo reboot
2. Add the ROCm apt repository.
* Open source
For Debian-based systems like Ubuntu, configure the Debian ROCm repository as follows:
wget -qO - http://repo.radeon.com/rocm/apt/debian/rocm.gpg.key | sudo apt-key add -
echo 'deb [arch=amd64] http://repo.radeon.com/rocm/apt/debian/ xenial main' | sudo tee /etc/apt/sources.list.d/rocm.list
The ROCm Data Center Tool can be used in the standalone mode if all components are installed. The same set of features is also available in a library format that can be used by existing management tools.
The gpg key may change; ensure it is updated when installing a new release. If the key signature verification fails while updating, re-add the key from the ROCm apt repository.
![ScreenShot](https://github.com/Rmalavally/ROCm/blob/master/RDCComponentsrevised.png)
The current rocm.gpg.key is not available in a standard key ring distribution, but has the following sha1sum hash:
e85a40d1a43453fe37d63aa6899bc96e08f2817a rocm.gpg.key
Refer to the ROCm Data Center Tool™ User Guide for more details on the different modes of operation.
3. Install the ROCm meta-package.
Update the appropriate repository list and install the rocm-dkms meta-package:
NOTE: The ROCm Data Center User Guide is intended to provide an overview of ROCm Data Center Tool features and how system administrators and Data Center (or HPC) users can administer and configure AMD GPUs. The guide also provides an overview of its components and open source developer handbook.
sudo apt update
sudo apt install rocm-dkms
For installation information on different distributions, refer to the ROCm Data Center User Guide at
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_DataCenter_Tool_User_Guide.pdf
4. Set permissions.
To access the GPU, you must be a user in the video group. Ensure your user account is a member of the video group prior to using ROCm. To identify the groups you are a member of, use the following command:
groups
5. To add your user to the video group, use the following command for the sudo password:
sudo usermod -a -G video $LOGNAME
6. By default, add any future users to the video group. Run the following command to add users to the video group:
### Error Correcting Code Fields in ROCm Data Center Tool
echo 'ADD_EXTRA_GROUPS=1'
sudo tee -a /etc/adduser.conf
echo 'EXTRA_GROUPS=video'
sudo tee -a /etc/adduser.conf
7. Restart the system.
The ROCm Data Center (RDC) tool is enhanced to provide counters to track correctable and uncorrectable errors. While a single bit per word error can be corrected, double bit per word errors cannot be corrected.
8. Test the basic ROCm installation.
The RDC tool now helps monitor and protect undetected memory data corruption. If the system is using ECC- enabled memory, the ROCm Data Center tool can report the error counters to monitor the status of the memory.
9. After restarting the system, run the following commands to verify that the ROCm installation is successful. If you see your GPUs listed by both commands, the installation is considered successful.
![ScreenShot](https://github.com/Rmalavally/ROCm/blob/master/forweb.PNG)
/opt/rocm/bin/rocminfo
/opt/rocm/opencl/bin/x86_64/clinfo
## Static Linking Libraries
Note: To run the ROCm programs more efficiently, add the ROCm binaries in your PATH.
The underlying libraries of AMD ROCm are dynamic and are called shared objects (.so) in Linux.
The AMD ROCm v3.8 release includes the capability to build static ROCm libraries and link to the applications statically. CMake target files enable linking an application statically to ROCm libraries and each component exports the required dependencies for linking. The static libraries are called Archives (.a) in Linux.
echo 'export PATH=$PATH:/opt/rocm/bin:/opt/rocm/profiler/bin:/opt/rocm/opencl/bin/x86_64' |
sudo tee -a /etc/profile.d/rocm.sh
This release also comprises of the requisite changes required for all the components to work in a static environment. The components have been successfully tested for basic functionalities like *rocminfo /rocm_bandwidth_test* and archives.
If you have an installation issue, refer the FAQ at:
https://rocm.github.io/install_issues.html
In the AMD ROCm v3.8 release, the following libraries support static linking:
![ScreenShot](https://github.com/Rmalavally/ROCm/blob/master/staticlinkinglib.PNG)
# Fixed Defects
The following defects are fixed in this release:
### Uninstalling ROCm Packages from Ubuntu
To uninstall the ROCm packages from Ubuntu v16.04 or Ubuntu v18.04.x, run the following command:
* GPU Kernel C++ Names Not Demangled
* MIGraphX Fails for fp16 Datatype
* Issue with Peer-to-Peer Transfers
* rocprof option --parallel-kernels Not Supported in this Release
sudo apt autoremove rocm-dkms
# Known Issues
## Undefined Reference Issue in Statically Linked Libraries
### Installing Development Packages for Cross Compilation
It is recommended that you develop and test applications on different systems. For example, some development or build systems may not have an AMD GPU installed. In this scenario, you must avoid installing the ROCk kernel driver on the development system.
Libraries and applications statically linked using flags -rtlib=compiler-rt, such as rocBLAS, have an implicit dependency on gcc_s not captured in their CMAKE configuration.
Instead, install the following development subset of applications:
Client applications may require linking with an additional library -lgcc_s to resolve the undefined reference to symbol '_Unwind_Resume@@GCC_3.0'.
sudo apt update
sudo apt install rocm-dev
## MIGraphX Pooling Operation Fails for Some Models
Note: To execute ROCm enabled applications, you must install the full ROCm driver stack on your system.
MIGraphX does not work for some models with pooling operations and the following error appears:
*test_gpu_ops_test FAILED*
### Using Debian-based ROCm with Upstream Kernel Drivers
You can install the ROCm user-level software without installing the AMD's custom ROCk kernel driver. To use the upstream kernels, run the following commands instead of installing rocm-dkms:
This issue is currently under investigation and there is no known workaround currently.
sudo apt update
sudo apt install rocm-dev
echo 'SUBSYSTEM=="kfd", KERNEL=="kfd", TAG+="uaccess", GROUP="video"'
sudo tee /etc/udev/rules.d/70-kfd.rules
## MIVisionX Installation Error on CentOS/RHEL8.2 and SLES 15
Installing ROCm on MIVisionX results in the following error on CentOS/RHEL8.2 and SLES 15:
## CentOS RHEL v7
*"Problem: nothing provides opencv needed"*
This section describes how to install ROCm on supported RPM-based systems such as CentOS v7.7.
As a workaround, install opencv before installing MIVisionX.
For more details, refer:
https://github.com/RadeonOpenCompute/ROCm/blob/master/README.md#rocm-binary-package-structure
### Preparing RHEL v7 (7.7) for Installation
RHEL is a subscription-based operating system. You must enable the external repositories to install on the devtoolset-7 environment and the dkms support files.
# Deploying ROCm
AMD hosts both Debian and RPM repositories for the ROCm v3.8.x packages.
Note: The following steps do not apply to the CentOS installation.
For more information on ROCM installation on all platforms, see
1. The subscription for RHEL must be enabled and attached to a pool ID. See the Obtaining an RHEL image and license page for instructions on registering your system with the RHEL subscription server and attaching to a pool id.
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
2. Enable the following repositories:
sudo subscription-manager repos --enable rhel-server-rhscl-7-rpms
sudo subscription-manager repos --enable rhel-7-server-optional-rpms
sudo subscription-manager repos --enable rhel-7-server-extras-rpms
3. Enable additional repositories by downloading and installing the epel-release-latest-7 repository RPM:
sudo rpm -ivh <repo>
For more details, see
https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm
4. Install and set up Devtoolset-7.
To setup the Devtoolset-7 environment, follow the instructions on this page:
https://www.softwarecollections.org/en/scls/rhscl/devtoolset-7/
Note: devtoolset-7 is a software collections package and is not supported by AMD.
### Installing CentOS/RHEL (v7.7) for DKMS
Use the dkms tool to install the kernel drivers on CentOS/RHEL v7.7:
sudo yum install -y epel-release
sudo yum install -y dkms kernel-headers-`uname -r` kernel-devel-`uname -r`
### Installing ROCm
To install ROCm on your system, follow the instructions below:
1. Delete the previous versions of ROCm before installing the latest version.
2. Create a /etc/yum.repos.d/rocm.repo file with the following contents:
[ROCm]
name=ROCm
baseurl=http://repo.radeon.com/rocm/yum/rpm
enabled=1
gpgcheck=0
Note: The URL of the repository must point to the location of the repositories repodata database.
3. Install ROCm components using the following command:
sudo yum install rocm-dkms
4. Restart the system.The rock-dkms component is installed and the /dev/kfd device is now available.
5. Set permissions.
To access the GPU, you must be a user in the video group. Ensure your user account is a member of the video group prior to using ROCm. To identify the groups you are a member of, use the following command:
groups
6. To add your user to the video group, use the following command for the sudo password:
sudo usermod -a -G video $LOGNAME
7. By default, add any future users to the video group. Run the following command to add users to the video group:
echo 'ADD_EXTRA_GROUPS=1' | sudo tee -a /etc/adduser.conf
echo 'EXTRA_GROUPS=video' | sudo tee -a /etc/adduser.conf
8. Restart the system.
9. Test the ROCm installation.
### Testing ROCm Installation
After restarting the system, run the following commands to verify that the ROCm installation is successful. If you see your GPUs listed, you are good to go!
/opt/rocm/bin/rocminfo
/opt/rocm/opencl/bin/x86_64/clinfo
Note: To run the ROCm programs more efficiently, add the ROCm binaries in your PATH for easy implementation of the ROCm programs.
echo 'export PATH=$PATH:/opt/rocm/bin:/opt/rocm/profiler/bin:/opt/rocm/opencl/bin/x86_64' |
sudo tee -a /etc/profile.d/rocm.sh
#### Compiling Applications Using HCC, HIP, and Other ROCm Software
To compile applications or samples, run the following command to use gcc-7.2 provided by the devtoolset-7 environment:
scl enable devtoolset-7 bash
### Uninstalling ROCm from CentOS/RHEL v7.7
To uninstall the ROCm packages, run the following command:
sudo yum autoremove rocm-dkms rock-dkms
### Installing Development Packages for Cross Compilation
You can develop and test ROCm packages on different systems. For example, some development or build systems may not have an AMD GPU installed. In this scenario, you can avoid installing the ROCm kernel driver on your development system. Instead, install the following development subset of packages:
sudo yum install rocm-dev
Note: To execute ROCm-enabled applications, you will require a system installed with the full ROCm driver stack.
### Using ROCm with Upstream Kernel Drivers
You can install ROCm user-level software without installing AMD's custom ROCk kernel driver. To use the upstream kernel drivers, run the following commands
sudo yum install rocm-dev
echo 'SUBSYSTEM=="kfd", KERNEL=="kfd", TAG+="uaccess", GROUP="video"'
sudo tee /etc/udev/rules.d/70-kfd.rules
Note: You can use these commands instead of installing rocm-dkms.
## SLES 15 Service Pack 1
The following section tells you how to perform an install and uninstall ROCm on SLES 15 SP 1.
### Installation
1. Install the "dkms" package.
sudo SUSEConnect --product PackageHub/15.1/x86_64
sudo zypper install dkms
2. Add the ROCm repo.
sudo zypper clean all
sudo zypper addrepo --no-gpgcheck http://repo.radeon.com/rocm/zyp/zypper/ rocm
sudo zypper ref
zypper install rocm-dkms
sudo zypper install rocm-dkms
sudo reboot
3. Run the following command once
cat <<EOF | sudo tee /etc/modprobe.d/10-unsupported-modules.conf
allow_unsupported_modules 1
EOF
sudo modprobe amdgpu
4. Verify the ROCm installation.
5. Run /opt/rocm/bin/rocminfo and /opt/rocm/opencl/bin/x86_64/clinfo commands to list the GPUs and verify that the ROCm installation is successful.
6. Set permissions.
To access the GPU, you must be a user in the video group. Ensure your user account is a member of the video group prior to using ROCm. To identify the groups you are a member of, use the following command:
groups
7. To add your user to the video group, use the following command for the sudo password:
sudo usermod -a -G video $LOGNAME
8. By default, add any future users to the video group. Run the following command to add users to the video group:
echo 'ADD_EXTRA_GROUPS=1' | sudo tee -a /etc/adduser.conf
echo 'EXTRA_GROUPS=video' | sudo tee -a /etc/adduser.conf
9. Restart the system.
10. Test the basic ROCm installation.
11. After restarting the system, run the following commands to verify that the ROCm installation is successful. If you see your GPUs listed by both commands, the installation is considered successful.
/opt/rocm/bin/rocminfo
/opt/rocm/opencl/bin/x86_64/clinfo
Note: To run the ROCm programs more efficiently, add the ROCm binaries in your PATH.
echo 'export PATH=$PATH:/opt/rocm/bin:/opt/rocm/profiler/bin:/opt/rocm/opencl/bin/x86_64' |
sudo tee -a /etc/profile.d/rocm.sh
### Uninstallation
To uninstall, use the following command:
sudo zypper remove rocm-dkms rock-dkms
Note: Ensure all other installed packages/components are removed.
Note: Ensure all the content in the /opt/rocm directory is completely removed.
## Performing an OpenCL-only Installation of ROCm
Some users may want to install a subset of the full ROCm installation. If you are trying to install on a system with a limited amount of storage space, or which will only run a small collection of known applications, you may want to install only the packages that are required to run OpenCL applications. To do that, you can run the following installation command instead of the command to install rocm-dkms.
sudo yum install rock-dkms rocm-opencl-devel
## ROCm Installation - Known Issues and Workarounds
### Closed source components
The ROCm platform relies on some closed source components to provide functionalities like HSA image support. These components are only available through the ROCm repositories, and they may be deprecated or become open source components in the future. These components are made available in the following packages:
• hsa-ext-rocr-dev
## Getting the ROCm Source Code
AMD ROCm is built from open source software. It is, therefore, possible to modify the various components of ROCm by downloading the source code and rebuilding the components. The source code for ROCm components can be cloned from each of the GitHub repositories using git. For easy access to download the correct versions of each of these tools, the ROCm repository contains a repo manifest file called default.xml. You can use this manifest file to download the source code for ROCm software.
### Installing the Repo
The repo tool from Google® allows you to manage multiple git repositories simultaneously. Run the following commands to install the repo:
mkdir -p ~/bin/
curl https://storage.googleapis.com/git-repo-downloads/repo > ~/bin/repo
chmod a+x ~/bin/repo
Note: You can choose a different folder to install the repo into if you desire. ~/bin/ is used as an example.
### Downloading the ROCm Source Code
The following example shows how to use the repo binary to download the ROCm source code. If you choose a directory other than ~/bin/ to install the repo, you must use that chosen directory in the code as shown below:
mkdir -p ~/ROCm/
cd ~/ROCm/
~/bin/repo init -u https://github.com/RadeonOpenCompute/ROCm.git -b roc-3.1.0
repo sync
Note: Using this sample code will cause the repo to download the open source code associated with this ROCm release. Ensure that you have ssh-keys configured on your machine for your GitHub ID prior to the download.
### Building the ROCm Source Code
Each ROCm component repository contains directions for building that component. You can access the desired component for instructions to build the repository.
### Hardware and Software Support
# 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.
@@ -502,18 +231,18 @@ The following list of GPUs are enabled in the ROCm software, though full support
* 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 3.1.0 (PCIe 3.1.0) with support for PCIe atomics. This requires both CPU and motherboard support. GFX9 GPUs require PCIe 3.1.0 with support for PCIe atomics by default, but they can operate in most cases without this capability.
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 our HCC or HIP runtimes, and may not work due to motherboard or OEM hardware limitations.
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://rocm.github.io/hardware.html).
#### Supported CPUs
As described above, GFX8 GPUs require PCIe 3.1.0 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 3.1.0 and PCIe atomics.
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:
@@ -549,15 +278,16 @@ does not require or take advantage of PCIe Atomics. However, we still recommend
from the list provided above for compatibility purposes.
#### Not supported or limited support under ROCm
##### Limited support
* ROCm 2.9.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 HCC, HIP, or our libraries built on top of these compilers and runtimes.
* 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 HCC, HIP, or our libraries built on top of these compilers and runtimes.
* 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.
@@ -565,18 +295,10 @@ from the list provided above for compatibility purposes.
##### Not supported
* "Tonga", "Iceland", "Vega M", and "Vega 12" GPUs are not supported in ROCm 2.9.x
* We do not support GFX8-class GPUs (Fiji, Polaris, etc.) on CPUs that do not have PCIe 3.1.0 with PCIe atomics.
* 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.
### Supported Operating Systems - New operating systems available
The ROCm 3.1.0.x platform supports the following operating systems:
* Ubuntu 16.04.5(Kernel 4.15) and 18.04.3(Kernel 4.15 and Kernel 4.18)
* CentOS 7.7 (Using devtoolset-7 runtime support)
* RHEL 7.7 (Using devtoolset-7 runtime support)
#### 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.
@@ -603,180 +325,9 @@ For users that have the option of using either AMD's or the upstreamed driver, t
| | | Does not include most up-to-date firmware |
## Software Support
As of AMD ROCm v1.9.0, the ROCm user-level software is compatible with the AMD drivers in certain upstream Linux kernels. You have the following options:
• Use the ROCk kernel driver that is a part of AMDs ROCm repositories
or
• Use the upstream driver and only install ROCm user-level utilities from AMDs ROCm repositories
The releases of the upstream Linux kernel support the following GPUs in ROCm:
• Fiji, Polaris 10, Polaris 11
• Fiji, Polaris 10, Polaris 11, Vega10
• Fiji, Polaris 10, Polaris 11, Vega10, Vega 7nm
## Machine Learning and High Performance Computing Software Stack for AMD GPU
ROCm Version 3.1.0
For an updated version of the software stack for AMD GPU, see
### ROCm Binary Package Structure
ROCm is a collection of software ranging from drivers and runtimes to libraries and developer tools.
In AMD's package distributions, these software projects are provided as a separate packages.
This allows users to install only the packages they need, if they do not wish to install all of ROCm.
These packages will install most of the ROCm software into `/opt/rocm/` by default.
The packages for each of the major ROCm components are:
* ROCm Core Components
- ROCk Kernel Driver: `rock-dkms`
- ROCr Runtime: `hsa-rocr-dev`, `hsa-ext-rocr-dev`
- ROCt Thunk Interface: `hsakmt-roct`, `hsakmt-roct-dev`
* ROCm Support Software
- ROCm SMI: `rocm-smi`
- ROCm cmake: `rocm-cmake`
- rocminfo: `rocminfo`
- ROCm Bandwidth Test: `rocm_bandwidth_test`
* ROCm Development Tools
- HCC compiler: `hcc`
- HIP: `hip_base`, `hip_doc`, `hip_hcc`, `hip_samples`
- ROCm Device Libraries: `rocm-device-libs`
- ROCm OpenCL: `rocm-opencl`, `rocm-opencl-devel` (on RHEL/CentOS), `rocm-opencl-dev` (on Ubuntu)
- ROCM Clang-OCL Kernel Compiler: `rocm-clang-ocl`
- Asynchronous Task and Memory Interface (ATMI): `atmi`
- ROCr Debug Agent: `rocr_debug_agent`
- ROCm Code Object Manager: `comgr`
- ROC Profiler: `rocprofiler-dev`
- ROC Tracer: `roctracer-dev`
- Radeon Compute Profiler: `rocm-profiler`
* ROCm Libraries
- rocALUTION: `rocalution`
- rocBLAS: `rocblas`
- hipBLAS: `hipblas`
- hipCUB: `hipCUB`
- rocFFT: `rocfft`
- rocRAND: `rocrand`
- rocSPARSE: `rocsparse`
- hipSPARSE: `hipsparse`
- ROCm SMI Lib: `rocm_smi_lib64`
- rocThrust: `rocThrust`
- MIOpen: `MIOpen-HIP` (for the HIP version), `MIOpen-OpenCL` (for the OpenCL version)
- MIOpenGEMM: `miopengemm`
- MIVisionX: `mivisionx`
- RCCL: `rccl`
To make it easier to install ROCm, the AMD binary repositories provide a number of meta-packages that will automatically install multiple other packages.
For example, `rocm-dkms` is the primary meta-package that is used to install most of the base technology needed for ROCm to operate.
It will install the `rock-dkms` kernel driver, and another meta-package (`rocm-dev`) which installs most of the user-land ROCm core components, support software, and development tools.
The `rocm-utils` meta-package will install useful utilities that, while not required for ROCm to operate, may still be beneficial to have.
Finally, the `rocm-libs` meta-package will install some (but not all) of the libraries that are part of ROCm.
The chain of software installed by these meta-packages is illustrated below
```
rocm-dkms
|--rock-dkms
\--rocm-dev
|--comgr
|--hcc
|--hip_base
|--hip_doc
|--hip_hcc
|--hip_samples
|--hsakmt-roct
|--hsakmt-roct-dev
|--hsa-amd-aqlprofile
|--hsa-ext-rocr-dev
|--hsa-rocr-dev
|--rocm-cmake
|--rocm-device-libs
|--rocm-smi
|--rocprofiler-dev
|--rocr_debug_agent
\--rocm-utils
|--rocminfo
\--rocm-clang-ocl # This will cause OpenCL to be installed
rocm-libs
|--hipblas
|--hipcub
|--hipsparse
|--rocalution
|--rocblas
|--rocfft
|--rocprim
|--rocrand
|--rocsparse
\--rocthrust
```
These meta-packages are not required but may be useful to make it easier to install ROCm on most systems.
Note:Some users may want to skip certain packages. For instance, a user that wants to use the upstream kernel drivers (rather than those supplied by AMD) may want to skip the `rocm-dkms` and `rock-dkms` packages, and instead directly install `rocm-dev`.
Similarly, a user that only wants to install OpenCL support instead of HCC and HIP may want to skip the `rocm-dkms` and `rocm-dev` packages. Instead, they could directly install `rock-dkms`, `rocm-opencl`, and `rocm-opencl-dev` and their dependencies.
### ROCm Platform Packages
Drivers, ToolChains, Libraries, and Source Code
The latest supported version of the drivers, tools, libraries and source code for the ROCm platform have been released and are available from the following GitHub repositories:
#### ROCm Core Components
- [ROCk Kernel Driver](https://github.com/RadeonOpenCompute/ROCK-Kernel-Driver/tree/roc-3.1.0)
- [ROCr Runtime](https://github.com/RadeonOpenCompute/ROCR-Runtime/tree/roc-3.1.0)
- [ROCT Thunk Interface](https://github.com/RadeonOpenCompute/ROCT-Thunk-Interface/tree/roc-3.1.0)
#### ROCm Support Software
- [ROCm SMI](https://github.com/RadeonOpenCompute/ROC-smi/tree/roc-3.1.0)
- [ROCm cmake](https://github.com/RadeonOpenCompute/rocm-cmake/tree/roc-3.0.0)
- [rocminfo](https://github.com/RadeonOpenCompute/rocminfo/tree/roc-3.1.0)
- [ROCm Bandwidth Test](https://github.com/RadeonOpenCompute/rocm_bandwidth_test/tree/roc-3.1.0)
#### ROCm Development ToolChains
- [HCC compiler](https://github.com/RadeonOpenCompute/hcc/tree/roc-hcc-3.1.0)
- [HIP](https://github.com/ROCm-Developer-Tools/HIP/tree/roc-3.1.0)
- [ROCm Device Libraries HCC](https://github.com/RadeonOpenCompute/ROCm-Device-Libs/tree/roc-hcc-3.1.0)
- ROCm OpenCL, which is created from the following components:
- [ROCm OpenCL Runtime](http://github.com/RadeonOpenCompute/ROCm-OpenCL-Runtime/tree/roc-3.1.0)
- The ROCm OpenCL compiler, which is created from the following components:
- [ROCm LLVM OCL](http://github.com/RadeonOpenCompute/llvm-project/tree/roc-ocl-3.1.0)
- [ROCm Device Libraries OCL](https://github.com/RadeonOpenCompute/ROCm-Device-Libs/tree/roc-ocl-3.1.0)
- [ROCM Clang-OCL Kernel Compiler](https://github.com/RadeonOpenCompute/clang-ocl/tree/roc-3.1.0)
- [Asynchronous Task and Memory Interface (ATMI)](https://github.com/RadeonOpenCompute/atmi/tree/rocm_3.1.0)
- [ROCr Debug Agent](https://github.com/ROCm-Developer-Tools/rocr_debug_agent/tree/roc-3.1.0)
- [ROCm Code Object Manager](https://github.com/RadeonOpenCompute/ROCm-CompilerSupport/tree/roc-3.1.0)
- [ROC Profiler](https://github.com/ROCm-Developer-Tools/rocprofiler/tree/roc-3.1.0)
- [ROC Tracer](https://github.com/ROCm-Developer-Tools/roctracer/tree/roc-3.1.x)
- [AOMP](https://github.com/ROCm-Developer-Tools/aomp/tree/roc-3.1.0)
- [Radeon Compute Profiler](https://github.com/GPUOpen-Tools/RCP/tree/3a49405)
- [ROCmValidationSuite](https://github.com/ROCm-Developer-Tools/ROCmValidationSuite/tree/roc-3.1.0)
- Example Applications:
- [HCC Examples](https://github.com/ROCm-Developer-Tools/HCC-Example-Application/tree/ffd65333)
- [HIP Examples](https://github.com/ROCm-Developer-Tools/HIP-Examples/tree/roc-3.1.0)
#### ROCm Libraries
- [rocBLAS](https://github.com/ROCmSoftwarePlatform/rocBLAS/tree/rocm-3.1)
- [hipBLAS](https://github.com/ROCmSoftwarePlatform/hipBLAS/tree/rocm-3.1)
- [rocFFT](https://github.com/ROCmSoftwarePlatform/rocFFT/tree/rocm-3.1)
- [rocRAND](https://github.com/ROCmSoftwarePlatform/rocRAND/tree/3.1.0)
- [rocSPARSE](https://github.com/ROCmSoftwarePlatform/rocSPARSE/tree/rocm-3.1)
- [hipSPARSE](https://github.com/ROCmSoftwarePlatform/hipSPARSE/tree/rocm-3.1)
- [rocALUTION](https://github.com/ROCmSoftwarePlatform/rocALUTION/tree/rocm-3.1)
- [MIOpenGEMM](https://github.com/ROCmSoftwarePlatform/MIOpenGEMM/tree/b51a125)
- [MIOpen](https://github.com/ROCmSoftwarePlatform/MIOpen/tree/roc-3.1.0)
- [rocThrust](https://github.com/ROCmSoftwarePlatform/rocThrust/tree/3.1.0)
- [ROCm SMI Lib](https://github.com/RadeonOpenCompute/rocm_smi_lib/tree/roc-3.1.0)
- [RCCL](https://github.com/ROCmSoftwarePlatform/rccl/tree/3.1.0)
- [MIVisionX](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/commit/755e7a08d5299a95c42def092af7c736d5eda90c)
- [hipCUB](https://github.com/ROCmSoftwarePlatform/hipCUB/tree/3.1.0)
- [AMDMIGraphX](https://github.com/ROCmSoftwarePlatform/AMDMIGraphX/tree/0.5.1)
Features and enhancements introduced in previous versions of ROCm can be found in [version_history.md](version_history.md)
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#software-stack-for-amd-gpu

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fetch="http://github.com/RadeonOpenCompute/" />
<remote name="rocm-devtools"
@@ -11,75 +10,70 @@
fetch="https://github.com/GPUOpen-ProfessionalCompute-Libraries/" />
<remote name="gpuopen-tools"
fetch="https://github.com/GPUOpen-Tools/" />
<default revision="refs/tags/roc-3.1.0"
<remote name="KhronosGroup"
fetch="https://github.com/KhronosGroup/" />
<default revision="refs/tags/rocm-3.8.0"
remote="roc-github"
sync-c="true"
sync-j="4" />
<!--list of projects for ROCM-->
<project name="ROCK-Kernel-Driver" />
<project name="ROCT-Thunk-Interface" />
<project name="ROCR-Runtime" />
<project name="ROC-smi" />
<project name="rocm_smi_lib" remote="roc-github" revision="refs/tags/roc-3.1.0" />
<project name="rocm-cmake" revision="1abe21258481d4cf92f5bab0ef5956636c52f735" />
<project name="rocm_smi_lib" remote="roc-github" />
<project name="rocm-cmake" />
<project name="rocminfo" />
<project name="rocprofiler" remote="rocm-devtools" revision="refs/tags/roc-3.1.0" />
<project name="roctracer" remote="rocm-devtools" revision="roc-3.1.x" />
<!-- If you want to get the full OpenCL runtime, there is a separate repo
manifest that is more authoritative than the copy in this file. It can
be found at the following URL:
https://github.com/RadeonOpenCompute/ROCm-OpenCL-Runtime/blob/roc-2.0.0/opencl.xml -->
<remote name="KhronosGroup" fetch="https://github.com/KhronosGroup/" />
<project name="rocprofiler" remote="rocm-devtools" />
<project name="roctracer" remote="rocm-devtools" />
<project name="ROCm-OpenCL-Runtime" />
<project path="ROCm-OpenCL-Runtime/api/opencl/khronos/icd" name="OpenCL-ICD-Loader" remote="KhronosGroup" revision="6c03f8b58fafd9dd693eaac826749a5cfad515f8" />
<project name="clang-ocl" />
<!-- HCC needs to be recursively synced to get it submodules -->
<project name="hcc" sync-s="true" revision="refs/tags/roc-hcc-3.1.0" />
<project name="HCC-Example-Application" remote="rocm-devtools" revision="ffd6533305e79eed667badd3c4cdb7879a1281b8" />
<project name="HIP" remote="rocm-devtools" revision="refs/tags/roc-3.1.0" />
<!--HIP Projects-->
<project name="HIP" remote="rocm-devtools" />
<project name="HIP-Examples" remote="rocm-devtools" />
<project name="ROCclr" remote="rocm-devtools" />
<project name="HIPIFY" remote="rocm-devtools" />
<!-- The following projects are all associated with the AMDGPU LLVM compiler -->
<project name="llvm-project" path="llvm_amd-stg-open" revision="refs/tags/roc-ocl-3.1.0"/>
<project name="ROCm-Device-Libs" revision="refs/tags/roc-ocl-3.1.0"/>
<project name="atmi" revision="refs/tags/rocm_3.1.0" />
<project name="llvm-project" path="llvm_amd-stg-open" />
<project name="ROCm-Device-Libs" />
<project name="atmi" />
<project name="ROCm-CompilerSupport" />
<project name="rocr_debug_agent" remote="rocm-devtools" />
<project name="rocm_bandwidth_test" />
<project name="RCP" remote="gpuopen-tools" revision="3a49405a1500067c49d181844ec90aea606055bb" />
<!-- gdb projects -->
<project name="ROCgdb" remote="rocm-devtools" />
<project name="ROCdbgapi" remote="rocm-devtools" />
<!-- ROCm Libraries -->
<project name="rocBLAS" remote="rocm-swplat" revision="refs/tags/rocm-3.1" />
<project name="hipBLAS" remote="rocm-swplat" revision="refs/tags/rocm-3.1" />
<project name="rocFFT" remote="rocm-swplat" revision="refs/tags/rocm-3.1" />
<project name="rocRAND" remote="rocm-swplat" revision="refs/tags/3.1.0" />
<project name="rocSPARSE" remote="rocm-swplat" revision="refs/tags/rocm-3.1" />
<project name="hipSPARSE" remote="rocm-swplat" revision="refs/tags/rocm-3.1" />
<project name="rocALUTION" remote="rocm-swplat" revision="refs/tags/rocm-3.1" />
<project name="MIOpenGEMM" remote="rocm-swplat" revision="b51a12523676451bf38bfcf0506a0745e80ac64f" />
<project name="MIOpen" remote="rocm-swplat" revision="refs/tags/roc-3.1.0" />
<project name="rccl" remote="rocm-swplat" revision="refs/tags/3.1.0" />
<project name="MIVisionX" remote="gpuopen-libs" revision="755e7a08d5299a95c42def092af7c736d5eda90c" />
<project name="rocThrust" remote="rocm-swplat" revision="refs/tags/3.1.0" />
<project name="hipCUB" remote="rocm-swplat" revision="refs/tags/3.1.0" />
<project name="rocPRIM" remote="rocm-swplat" revision="refs/tags/3.1.0" />
<project name="AMDMIGraphX" remote="rocm-swplat" revision="79bfafc1b02dc276883fe5bab82eb9e481de8bc0" />
<project name="ROCmValidationSuite" remote="rocm-devtools" revision="refs/tags/roc-3.1.0" />
<project name="rocBLAS" remote="rocm-swplat" />
<project name="hipBLAS" remote="rocm-swplat" />
<project name="rocFFT" remote="rocm-swplat" />
<project name="rocRAND" remote="rocm-swplat" />
<project name="rocSPARSE" remote="rocm-swplat" />
<project name="rocSOLVER" remote="rocm-swplat" />
<project name="hipSPARSE" remote="rocm-swplat" />
<project name="rocALUTION" remote="rocm-swplat" />
<project name="MIOpenGEMM" remote="rocm-swplat" />
<project name="MIOpen" remote="rocm-swplat" />
<project name="rccl" remote="rocm-swplat" />
<project name="MIVisionX" remote="gpuopen-libs" />
<project name="rocThrust" remote="rocm-swplat" />
<project name="hipCUB" remote="rocm-swplat" />
<project name="rocPRIM" remote="rocm-swplat" />
<project name="hipfort" remote="rocm-swplat" />
<project name="ROCmValidationSuite" remote="rocm-devtools" />
<!-- Projects for AOMP -->
<project name="ROCT-Thunk-Interface" path="aomp/roct-thunk-interface" remote="roc-github" revision="refs/tags/roc-3.1.0" />
<project name="ROCR-Runtime" path="aomp/rocr-runtime" remote="roc-github" revision="refs/tags/roc-3.1.0" />
<project name="hcc" path="aomp/hcc" remote="roc-github" revision="6d267cfb2895cb057e15b51a82c310bcc5f4462d" />
<project name="ROCm-Device-Libs" path="aomp/rocm-device-libs" remote="roc-github" revision="8f441a8aff556ff02fb2f501a3df0377dd58d15d" />
<project name="ROCm-CompilerSupport" path="aomp/rocm-compilersupport" remote="roc-github" revision="refs/tags/roc-3.1.0" />
<project name="rocminfo" path="aomp/rocminfo" remote="roc-github" revision="refs/tags/roc-3.1.0" />
<project name="atmi" path="aomp/atmi" remote="roc-github" revision="06e4962fab54b51cd5afa43b9118bca669e01fa3" />
<project name="HIP" path="aomp/hip" remote="rocm-devtools" revision="6edce9543de8621ccb6442bec9ef7314d123cc1a" />
<project name="aomp" path="aomp/aomp" remote="rocm-devtools" revision="refs/tags/roc-3.1.0" />
<project name="aomp-extras" path="aomp/aomp-extras" remote="rocm-devtools" revision="refs/tags/roc-3.1.0" />
<project name="flang" path="aomp/flang" remote="rocm-devtools" revision="refs/tags/roc-3.1.0" />
<project name="llvm-project" path="aomp/llvm-project" remote="rocm-devtools" revision="refs/tags/roc-aomp-3.1.0" />
<project name="ROCT-Thunk-Interface" path="aomp/roct-thunk-interface" remote="roc-github" />
<project name="ROCR-Runtime" path="aomp/rocr-runtime" remote="roc-github" />
<project name="ROCm-Device-Libs" path="aomp/rocm-device-libs" remote="roc-github" />
<project name="ROCm-CompilerSupport" path="aomp/rocm-compilersupport" remote="roc-github" />
<project name="rocminfo" path="aomp/rocminfo" remote="roc-github" />
<project name="HIP" path="aomp/hip-on-vdi" remote="rocm-devtools" />
<project name="aomp" path="aomp/aomp" remote="rocm-devtools" />
<project name="aomp-extras" path="aomp/aomp-extras" remote="rocm-devtools" />
<project name="flang" path="aomp/flang" remote="rocm-devtools" />
<project name="amd-llvm-project" path="aomp/amd-llvm-project" remote="rocm-devtools" />
<project name="ROCclr" path="aomp/vdi" remote="rocm-devtools" />
<project name="ROCm-OpenCL-Runtime" path="aomp/opencl-on-vdi" remote="roc-github" />
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## ROCm Version History
This file contains archived version history information for the [ROCm project](https://github.com/RadeonOpenCompute/ROCm)
### Current ROCm Version: 3.0
- [New features and enhancements in ROCm v3.0](#new-features-and-enhancements-in-rocm-v30)
- [New features and enhancements in ROCm v2.10](#new-features-and-enhancements-in-rocm-v210)
- [New features and enhancements in ROCm 2.9](#new-features-and-enhancements-in-rocm-29)
- [New features and enhancements in ROCm 2.8](#new-features-and-enhancements-in-rocm-28)
- [New features and enhancements in ROCm 2.7.2](#new-features-and-enhancements-in-rocm-272)
- [New features and enhancements in ROCm 2.7](#new-features-and-enhancements-in-rocm-27)
- [New features and enhancements in ROCm 2.6](#new-features-and-enhancements-in-rocm-26)
- [New features and enhancements in ROCm 2.5](#new-features-and-enhancements-in-rocm-25)
- [New features and enhancements in ROCm 2.4](#new-features-and-enhancements-in-rocm-24)
- [New features and enhancements in ROCm 2.3](#new-features-and-enhancements-in-rocm-23)
- [New features and enhancements in ROCm 2.2](#new-features-and-enhancements-in-rocm-22)
- [New features and enhancements in ROCm 2.1](#new-features-and-enhancements-in-rocm-21)
- [New features and enhancements in ROCm 2.0](#new-features-and-enhancements-in-rocm-20)
- [New features and enhancements in ROCm 1.9.2](#new-features-and-enhancements-in-rocm-192)
- [New features and enhancements in ROCm 1.9.2](#new-features-and-enhancements-in-rocm-192-1)
- [New features and enhancements in ROCm 1.9.1](#new-features-and-enhancements-in-rocm-191)
- [New features and enhancements in ROCm 1.9.0](#new-features-and-enhancements-in-rocm-190)
- [New features as of ROCm 1.8.3](#new-features-as-of-rocm-183)
- [New features as of ROCm 1.8](#new-features-as-of-rocm-18)
- [New Features as of ROCm 1.7](#new-features-as-of-rocm-17)
- [New Features as of ROCm 1.5](#new-features-as-of-rocm-15)
### New features and enhancements in ROCm v3.0
### Support for CentOS RHEL v7.7 <a id="centos-anchor"></a>
Support is extended for CentOS/RHEL v7.7 in the ROCm v3.0 release. For more information about the CentOS/RHEL v7.7 release, see:
[CentOS/RHEL](https://centos.org/forums/viewtopic.php?t=71657)
### Initial distribution of AOMP 0.7-5 in ROCm v3.0 <a id="aomp-anchor"></a>
The code base for this release of AOMP is the Clang/LLVM 9.0 sources as of October 8th, 2019. The LLVM-project branch used to build this release is AOMP-191008. It is now locked. With this release, an artifact tarball of the entire source tree is created. This tree includes a Makefile in the root directory used to build AOMP from the release tarball. You can use Spack to build AOMP from this source tarball or build manually without Spack.
For more information about AOMP 0.7-5, see: [AOMP](https://github.com/ROCm-Developer-Tools/aomp/tree/roc-3.0.0)
### Fast Fourier Transform Updates
The Fast Fourier Transform (FFT) is an efficient algorithm for computing the Discrete Fourier Transform. Fast Fourier transforms are used in signal processing, image processing, and many other areas. The following real FFT performance change is made in the ROCm v3.0 release:
• Implement efficient real/complex 2D transforms for even lengths.
Other improvements:
• More 2D test coverage sizes.
• Fix buffer allocation error for large 1D transforms.
• C++ compatibility improvements.
### MemCopy Enhancement for rocProf
In the v3.0 release, the rocProf tool is enhanced with an additional capability to dump asynchronous GPU memcopy information into a .csv file. You can use the '-hsa-trace' option to create the results_mcopy.csv file.
Future enhancements will include column labels.
### New features and enhancements in ROCm v2.10
#### rocBLAS Support for Complex GEMM
The rocBLAS library is a gpu-accelerated implementation of the standard Basic Linear Algebra Subroutines (BLAS). rocBLAS is designed to enable you to develop algorithms, including high performance computing, image analysis, and machine learning.
In the AMD ROCm release v2.10, support is extended to the General Matrix Multiply (GEMM) routine for multiple small matrices processed simultaneously for rocBLAS in AMD Radeon Instinct MI50. Both single and double precision, CGEMM and ZGEMM, are now supported in rocBLAS.
#### Support for SLES 15 SP1
In the AMD ROCm v2.10 release, support is added for SUSE Linux® Enterprise Server (SLES) 15 SP1. SLES is a modular operating system for both multimodal and traditional IT.
#### Code Marker Support for rocProfiler and rocTracer Libraries
Code markers provide the external correlation ID for the calling thread. This function indicates that the calling thread is entering and leaving an external API region.
### New features and enhancements in ROCm 2.9
#### Initial release for Radeon Augmentation Library(RALI)
The AMD Radeon Augmentation Library (RALI) is designed to efficiently decode and process images from a variety of storage formats and modify them through a processing graph programmable by the user. RALI currently provides C API.
#### Quantization in MIGraphX v0.4
MIGraphX 0.4 introduces support for fp16 and int8 quantization. For additional details, as well as other new MIGraphX features, see [MIGraphX documentation](https://github.com/ROCmSoftwarePlatform/AMDMIGraphX/wiki/Getting-started:-using-the-new-features-of-MIGraphX-0.4).
#### rocSparse csrgemm
csrgemm enables the user to perform matrix-matrix multiplication with two sparse matrices in CSR format.
#### Singularity Support
ROCm 2.9 adds support for Singularity container version 2.5.2.
#### Initial release of rocTX
ROCm 2.9 introduces rocTX, which provides a C API for code markup for performance profiling. This initial release of rocTX supports annotation of code ranges and ASCII markers. For an example, see this [code](https://github.com/ROCm-Developer-Tools/roctracer/blob/amd-master/test/MatrixTranspose_test/MatrixTranspose.cpp).
#### Added support for Ubuntu 18.04.3
Ubuntu 18.04.3 is now supported in ROCm 2.9.
### New features and enhancements in ROCm 2.8
#### Support for NCCL2.4.8 API
Implements ncclCommAbort() and ncclCommGetAsyncError() to match the NCCL 2.4.x API
### New features and enhancements in ROCm 2.7.2
This release is a hotfix for ROCm release 2.7.
#### Issues fixed in ROCm 2.7.2
##### A defect in upgrades from older ROCm releases has been fixed.
##### rocprofiler --hiptrace and --hsatrace fails to load roctracer library
In ROCm 2.7.2, rocprofiler --hiptrace and --hsatrace fails to load roctracer library defect has been fixed.
To generate traces, please provide directory path also using the parameter: -d <$directoryPath> for example:
```shell
/opt/rocm/bin/rocprof --hsa-trace -d $PWD/traces /opt/rocm/hip/samples/0_Intro/bit_extract/bit_extract
```
All traces and results will be saved under $PWD/traces path
#### Upgrading from ROCm 2.7 to 2.7.2
To upgrade, please remove 2.7 completely as specified [for ubuntu](#how-to-uninstall-from-ubuntu-1604-or-Ubuntu-1804) or [for centos/rhel](#how-to-uninstall-rocm-from-centosrhel-76), and install 2.7.2 as per instructions [install instructions](#installing-from-amd-rocm-repositories)
#### Other notes
To use rocprofiler features, the following steps need to be completed before using rocprofiler:
##### Step-1: Install roctracer
###### Ubuntu 16.04 or Ubuntu 18.04:
```shell
sudo apt install roctracer-dev
```
###### CentOS/RHEL 7.6:
```shell
sudo yum install roctracer-dev
```
##### Step-2: Add /opt/rocm/roctracer/lib to LD_LIBRARY_PATH
### New features and enhancements in ROCm 2.7
#### [rocFFT] Real FFT Functional
Improved real/complex 1D even-length transforms of unit stride. Performance improvements of up to 4.5x are observed. Large problem sizes should see approximately 2x.
#### rocRand Enhancements and Optimizations
- Added support for new datatypes: uchar, ushort, half.
- Improved performance on "Vega 7nm" chips, such as on the Radeon Instinct MI50
- mtgp32 uniform double performance changes due generation algorithm standardization. Better quality random numbers now generated with 30% decrease in performance
- Up to 5% performance improvements for other algorithms
#### RAS
Added support for RAS on Radeon Instinct MI50, including:
- Memory error detection
- Memory error detection counter
#### ROCm-SMI enhancements
Added ROCm-SMI CLI and LIB support for FW version, compute running processes, utilization rates, utilization counter, link error counter, and unique ID.
### New features and enhancements in ROCm 2.6
#### ROCmInfo enhancements
ROCmInfo was extended to do the following:
For ROCr API call errors including initialization determine if the error could be explained by:
- ROCk (driver) is not loaded / available
- User does not have membership in appropriate group - "video"
- If not above print the error string that is mapped to the returned error code
- If no error string is available, print the error code in hex
#### Thrust - Functional Support on Vega20
ROCm2.6 contains the first official release of rocThrust and hipCUB. rocThrust is a port of thrust, a parallel algorithm library. hipCUB is a port of CUB, a reusable software component library. Thrust/CUB has been ported to the HIP/ROCm platform to use the rocPRIM library. The HIP ported library works on HIP/ROCm platforms.
Note: rocThrust and hipCUB library replaces https://github.com/ROCmSoftwarePlatform/thrust (hip-thrust), i.e. hip-thrust has been separated into two libraries, rocThrust and hipCUB. Existing hip-thrust users are encouraged to port their code to rocThrust and/or hipCUB. Hip-thrust will be removed from official distribution later this year.
#### MIGraphX v0.3
MIGraphX optimizer adds support to read models frozen from Tensorflow framework. Further details and an example usage at https://github.com/ROCmSoftwarePlatform/AMDMIGraphX/wiki/Getting-started:-using-the-new-features-of-MIGraphX-0.3
#### MIOpen 2.0
- This release contains several new features including an immediate mode for selecting convolutions, bfloat16 support, new layers, modes, and algorithms.
- MIOpenDriver, a tool for benchmarking and developing kernels is now shipped with MIOpen.
BFloat16 now supported in HIP requires an updated rocBLAS as a GEMM backend.
- Immediate mode API now provides the ability to quickly obtain a convolution kernel.
- MIOpen now contains HIP source kernels and implements the ImplicitGEMM kernels. This is a new feature and is currently disabled by default. Use the environmental variable "MIOPEN_DEBUG_CONV_IMPLICIT_GEMM=1" to activation this feature. ImplicitGEMM requires an up to date HIP version of at least 1.5.9211.
- A new "loss" catagory of layers has been added, of which, CTC loss is the first. See the API reference for more details.
2.0 is the last release of active support for gfx803 architectures. In future releases, MIOpen will not actively debug and develop new features specifically for gfx803.
- System Find-Db in memory cache is disabled by default. Please see build instructions to enable this feature.
Additional documentation can be found here: https://rocmsoftwareplatform.github.io/MIOpen/doc/html/
#### Bloat16 software support in rocBLAS/Tensile
Added mixed precision bfloat16/IEEE f32 to gemm_ex. The input and output matrices are bfloat16. All arithmetic is in IEEE f32.
#### AMD Infinity Fabric™ Link enablement
The ability to connect four Radeon Instinct MI60 or Radeon Instinct MI50 boards in two hives or two Radeon Instinct MI60 or Radeon Instinct MI50 boards in four hives via AMD Infinity Fabric™ Link GPU interconnect technology has been added.
#### ROCm-smi features and bug fixes
- mGPU & Vendor check
- Fix clock printout if DPM is disabled
- Fix finding marketing info on CentOS
- Clarify some error messages
#### ROCm-smi-lib enhancements
- Documentation updates
- Improvements to *name_get functions
#### RCCL2 Enablement
RCCL2 supports collectives intranode communication using PCIe, Infinity Fabric™, and pinned host memory, as well as internode communication using Ethernet (TCP/IP sockets) and Infiniband/RoCE (Infiniband Verbs). Note: For Infiniband/RoCE, RDMA is not currently supported.
#### rocFFT enhancements
- Added: Debian package with FFT test, benchmark, and sample programs
- Improved: hipFFT interfaces
- Improved: rocFFT CPU reference code, plan generation code and logging code
### New features and enhancements in ROCm 2.5
#### UCX 1.6 support
Support for UCX version 1.6 has been added.
#### BFloat16 GEMM in rocBLAS/Tensile
Software support for BFloat16 on Radeon Instinct MI50, MI60 has been added. This includes:
- Mixed precision GEMM with BFloat16 input and output matrices, and all arithmetic in IEEE32 bit
- Input matrix values are converted from BFloat16 to IEEE32 bit, all arithmetic and accumulation is IEEE32 bit. Output values are rounded from IEEE32 bit to BFloat16
- Accuracy should be correct to 0.5 ULP
#### ROCm-SMI enhancements
CLI support for querying the memory size, driver version, and firmware version has been added to ROCm-smi.
#### [PyTorch] multi-GPU functional support (CPU aggregation/Data Parallel)
Multi-GPU support is enabled in PyTorch using Dataparallel path for versions of PyTorch built using the 06c8aa7a3bbd91cda2fd6255ec82aad21fa1c0d5 commit or later.
#### rocSparse optimization on Radeon Instinct MI50 and MI60
This release includes performance optimizations for csrsv routines in the rocSparse library.
#### [Thrust] Preview
Preview release for early adopters. rocThrust is a port of thrust, a parallel algorithm library. Thrust has been ported to the HIP/ROCm platform to use the rocPRIM library. The HIP ported library works on HIP/ROCm platforms.
Note: This library will replace https://github.com/ROCmSoftwarePlatform/thrust in a future release. The package for rocThrust (this library) currently conflicts with version 2.5 package of thrust. They should not be installed together.
#### Support overlapping kernel execution in same HIP stream
HIP API has been enhanced to allow independent kernels to run in parallel on the same stream.
#### AMD Infinity Fabric&#x2122; Link enablement
The ability to connect four Radeon Instinct MI60 or Radeon Instinct MI50 boards in one hive via AMD Infinity Fabric™ Link GPU interconnect technology has been added.
### New features and enhancements in ROCm 2.4
#### TensorFlow 2.0 support
ROCm 2.4 includes the enhanced compilation toolchain and a set of bug fixes to support TensorFlow 2.0 features natively
#### AMD Infinity Fabric&#x2122; Link enablement
ROCm 2.4 adds support to connect two Radeon Instinct MI60 or Radeon Instinct MI50 boards via AMD Infinity Fabric&#x2122; Link GPU interconnect technology.
### New features and enhancements in ROCm 2.3
#### Mem usage per GPU
Per GPU memory usage is added to rocm-smi.
Display information regarding used/total bytes for VRAM, visible VRAM and GTT, via the --showmeminfo flag
#### MIVisionX, v1.1 - ONNX
ONNX parser changes to adjust to new file formats
#### MIGraphX, v0.2
MIGraphX 0.2 supports the following new features:
* New Python API
* Support for additional ONNX operators and fixes that now enable a large set of Imagenet models
* Support for RNN Operators
* Support for multi-stream Execution
* [Experimental] Support for Tensorflow frozen protobuf files
See: [Getting-started:-using-the-new-features-of-MIGraphX-0.2](https://github.com/ROCmSoftwarePlatform/AMDMIGraphX/wiki/Getting-started:-using-the-new-features-of-MIGraphX-0.2) for more details
#### MIOpen, v1.8 - 3d convolutions and int8
* This release contains full 3-D convolution support and int8 support for inference.
* Additionally, there are major updates in the performance database for major models including those found in Torchvision.
See: [MIOpen releases](https://github.com/ROCmSoftwarePlatform/MIOpen/releases)
#### Caffe2 - mGPU support
Multi-gpu support is enabled for Caffe2.
#### rocTracer library, ROCm tracing API for collecting runtimes API and asynchronous GPU activity traces
HIP/HCC domains support is introduced in rocTracer library.
#### BLAS - Int8 GEMM performance, Int8 functional and performance
Introduces support and performance optimizations for Int8 GEMM, implements TRSV support, and includes improvements and optimizations with Tensile.
#### Prioritized L1/L2/L3 BLAS (functional)
Functional implementation of BLAS L1/L2/L3 functions
#### BLAS - tensile optimization
Improvements and optimizations with tensile
#### MIOpen Int8 support
Support for int8
### New features and enhancements in ROCm 2.2
#### rocSparse Optimization on Vega20
Cache usage optimizations for csrsv (sparse triangular solve), coomv
(SpMV in COO format) and ellmv (SpMV in ELL format) are available.
#### DGEMM and DTRSM Optimization
Improved DGEMM performance for reduced matrix sizes (k=384, k=256)
#### Caffe2
Added support for multi-GPU training
### New features and enhancements in ROCm 2.1
#### RocTracer v1.0 preview release 'rocprof' HSA runtime tracing and statistics support -
Supports HSA API tracing and HSA asynchronous GPU activity including kernels execution and memory copy
#### Improvements to ROCM-SMI tool -
Added support to show real-time PCIe bandwidth usage via the -b/--showbw flag
#### DGEMM Optimizations -
Improved DGEMM performance for large square and reduced matrix sizes (k=384, k=256)
### New features and enhancements in ROCm 2.0
#### Adds support for RHEL 7.6 / CentOS 7.6 and Ubuntu 18.04.1
#### Adds support for Vega 7nm, Polaris 12 GPUs
#### Introduces MIVisionX
* A comprehensive computer vision and machine intelligence libraries, utilities and applications bundled into a single toolkit.
#### Improvements to ROCm Libraries
* rocSPARSE & hipSPARSE
* rocBLAS with improved DGEMM efficiency on Vega 7nm
#### MIOpen
* This release contains general bug fixes and an updated performance database
* Group convolutions backwards weights performance has been improved
* RNNs now support fp16
#### Tensorflow multi-gpu and Tensorflow FP16 support for Vega 7nm
* TensorFlow v1.12 is enabled with fp16 support
#### PyTorch/Caffe2 with Vega 7nm Support
* fp16 support is enabled
* Several bug fixes and performance enhancements
* Known Issue: breaking changes are introduced in ROCm 2.0 which are not addressed upstream yet. Meanwhile, please continue to use ROCm fork at https://github.com/ROCmSoftwarePlatform/pytorch
#### Improvements to ROCProfiler tool
* Support for Vega 7nm
#### Support for hipStreamCreateWithPriority
* Creates a stream with the specified priority. It creates a stream on which enqueued kernels have a different priority for execution compared to kernels enqueued on normal priority streams. The priority could be higher or lower than normal priority streams.
#### OpenCL 2.0 support
* ROCm 2.0 introduces full support for kernels written in the OpenCL 2.0 C language on certain devices and systems.  Applications can detect this support by calling the “clGetDeviceInfo” query function with “parame_name” argument set to “CL_DEVICE_OPENCL_C_VERSION”.  In order to make use of OpenCL 2.0 C language features, the application must include the option “-cl-std=CL2.0” in options passed to the runtime API calls responsible for compiling or building device programs.  The complete specification for the OpenCL 2.0 C language can be obtained using the following link: https://www.khronos.org/registry/OpenCL/specs/opencl-2.0-openclc.pdf
#### Improved Virtual Addressing (48 bit VA) management for Vega 10 and later GPUs
* Fixes Clang AddressSanitizer and potentially other 3rd-party memory debugging tools with ROCm
* Small performance improvement on workloads that do a lot of memory management
* Removes virtual address space limitations on systems with more VRAM than system memory
#### Kubernetes support
### New features and enhancements in ROCm 1.9.2
#### RDMA(MPI) support on Vega 7nm
* Support ROCnRDMA based on Mellanox InfiniBand
#### Improvements to HCC
* Improved link time optimization
#### Improvements to ROCProfiler tool
* General bug fixes and implemented versioning APIs
### New features and enhancements in ROCm 1.9.2
#### RDMA(MPI) support on Vega 7nm
* Support ROCnRDMA based on Mellanox InfiniBand
#### Improvements to HCC
* Improved link time optimization
#### Improvements to ROCProfiler tool
* General bug fixes and implemented versioning APIs
#### Critical bug fixes
### New features and enhancements in ROCm 1.9.1
#### Added DPM support to Vega 7nm
* Dynamic Power Management feature is enabled on Vega 7nm.
#### Fix for 'ROCm profiling' that used to fail with a “Version mismatch between HSA runtime and libhsa-runtime-tools64.so.1” error
### New features and enhancements in ROCm 1.9.0
#### Preview for Vega 7nm
* Enables developer preview support for Vega 7nm
#### System Management Interface
* Adds support for the ROCm SMI (System Management Interface) library, which provides monitoring and management capabilities for AMD GPUs.
#### Improvements to HIP/HCC
* Support for gfx906
* Added deprecation warning for C++AMP. This will be the last version of HCC supporting C++AMP.
* Improved optimization for global address space pointers passing into a GPU kernel
* Fixed several race conditions in the HCC runtime
* Performance tuning to the unpinned copy engine
* Several codegen enhancement fixes in the compiler backend
#### Preview for rocprof Profiling Tool
Developer preview (alpha) of profiling tool rocProfiler. It includes a command-line front-end, `rpl_run.sh`, which enables:
* Cmd-line tool for dumping public per kernel perf-counters/metrics and kernel timestamps
* Input file with counters list and kernels selecting parameters
* Multiple counters groups and app runs supported
* Output results in CSV format
The tool can be installed from the `rocprofiler-dev` package. It will be installed into: `/opt/rocm/bin/rpl_run.sh`
#### Preview for rocr Debug Agent rocr_debug_agent
The ROCr Debug Agent is a library that can be loaded by ROCm Platform Runtime to provide the following functionality:
* Print the state for wavefronts that report memory violation or upon executing a "s_trap 2" instruction.
* Allows SIGINT (`ctrl c`) or SIGTERM (`kill -15`) to print wavefront state of aborted GPU dispatches.
* It is enabled on Vega10 GPUs on ROCm1.9.
The ROCm1.9 release will install the ROCr Debug Agent library at `/opt/rocm/lib/librocr_debug_agent64.so`
#### New distribution support
* Binary package support for Ubuntu 18.04
#### ROCm 1.9 is ABI compatible with KFD in upstream Linux kernels.
Upstream Linux kernels support the following GPUs in these releases:
4.17: Fiji, Polaris 10, Polaris 11
4.18: Fiji, Polaris 10, Polaris 11, Vega10
Some ROCm features are not available in the upstream KFD:
* More system memory available to ROCm applications
* Interoperability between graphics and compute
* RDMA
* IPC
To try ROCm with an upstream kernel, install ROCm as normal, but do not install the rock-dkms package. Also add a udev rule to control `/dev/kfd` permissions:
```
echo 'SUBSYSTEM=="kfd", KERNEL=="kfd", TAG+="uaccess", GROUP="video"' | sudo tee /etc/udev/rules.d/70-kfd.rules
```
### New features as of ROCm 1.8.3
* ROCm 1.8.3 is a minor update meant to fix compatibility issues on Ubuntu releases running kernel 4.15.0-33
### New features as of ROCm 1.8
#### DKMS driver installation
* Debian packages are provided for DKMS on Ubuntu
* RPM packages are provided for CentOS/RHEL 7.4 and 7.5 support
* See the [ROCT-Thunk-Interface](https://github.com/RadeonOpenCompute/ROCT-Thunk-Interface/tree/roc-1.8.x) and [ROCK-Kernel-Driver](https://github.com/RadeonOpenCompute/ROCK-Kernel-Driver/tree/roc-1.8.x) for additional documentation on driver setup
#### New distribution support
* Binary package support for Ubuntu 16.04 and 18.04
* Binary package support for CentOS 7.4 and 7.5
* Binary package support for RHEL 7.4 and 7.5
#### Improved OpenMPI via UCX support
* UCX support for OpenMPI
* ROCm RDMA
### New Features as of ROCm 1.7
#### DKMS driver installation
* New driver installation uses Dynamic Kernel Module Support (DKMS)
* Only amdkfd and amdgpu kernel modules are installed to support AMD hardware
* Currently only Debian packages are provided for DKMS (no Fedora suport available)
* See the [ROCT-Thunk-Interface](https://github.com/RadeonOpenCompute/ROCT-Thunk-Interface/tree/roc-1.7.x) and [ROCK-Kernel-Driver](https://github.com/RadeonOpenCompute/ROCK-Kernel-Driver/tree/roc-1.7.x) for additional documentation on driver setup
### New Features as of ROCm 1.5
#### Developer preview of the new OpenCL 1.2 compatible language runtime and compiler
* OpenCL 2.0 compatible kernel language support with OpenCL 1.2 compatible
runtime
* Supports offline ahead of time compilation today;
during the Beta phase we will add in-process/in-memory compilation.
#### Binary Package support for Ubuntu 16.04
#### Binary Package support for Fedora 24 is not currently available
#### Dropping binary package support for Ubuntu 14.04, Fedora 23
#### IPC support