Update ROCm_Installation_Guide_v3.7.md

README.md

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-
-# AMD ROCm™ Release Notes v4.0
-
-This page describes the features, fixed issues, and information about downloading and installing the ROCm software.
-It also covers known issues 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)
-  * [INTRODUCING AMD INSTINCT MI100](#INTRODUCING-AMD-INSTINCT-MI100)
-  * [RAS Enhancements](#RAS-Enhancements)
-  * [Using CMake with AMD ROCm](#Using-CMake-with-AMD-ROCm)
-  * [AMD ROCm and Mesa Multimedia](#AMD-ROCm-and-Mesa-Multimedia)
-  * [ROCm System Management Information](#ROCm-System-Management-Information)
-  * [AMD GPU Debugger Enhancements](#AMD-GPU-Debugger-Enhancements)
-
-    
-- [Known Issues](#Known-Issues)
-
-- [Deprecations](#Deprecations)
-
-  * [Compiler Generated Code Object Version 2 Deprecation ](#Compiler-Generated-Code-Object-Version-2-Deprecation)
-  * [ROCr Runtime Deprecations](#ROCr-Runtime-Deprecations)
-  * [AOMP Deprecation](#AOMP-Deprecation)
-  
-
-- [Deploying ROCm](#Deploying-ROCm)
- 
-- [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)
-  
-
-
-# Supported Operating Systems 
-
-## List of Supported Operating Systems
-
-The AMD ROCm platform is designed to support the following operating systems:
-
-* Ubuntu 20.04.1 (5.4 and 5.6-oem) and 18.04.5 (Kernel 5.4)	
-
-* CentOS 7.8 (3.10.0-1127) & RHEL 7.9 (3.10.0-1160.6.1.el7) (Using devtoolset-7 runtime support)
-
-* CentOS 8.2 (4.18.0-193.el8) and RHEL 8.2 (4.18.0-193.1.1.el8) (devtoolset is not required)
-
-* SLES 15 SP2
-
- 
-# ROCm Installation Updates
-
-## Fresh Installation of AMD ROCm v4.0 Recommended
-
-A fresh and clean installation of AMD ROCm v4.0 is recommended. An upgrade from previous releases to AMD ROCm v4.0 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 unchanged -  */opt/rocm/opencl/bin/x86_64/clinfo*.
-
-**Note**: After an operating system upgrade, AMD ROCm may upgrade automatically and result in an error. This is because AMD ROCm does not support upgrades currently. You must uninstall and reinstall AMD ROCm after an operating system upgrade.
-
-
-## ROCm MultiVersion Installation Update
-
-With the AMD ROCm v4.0 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.   
-* Version files must be created for each multi-version rocm <= 4.0.0
-
-    * command: echo <version> | sudo tee /opt/rocm-<version>/.info/version
-
-    * example: echo 4.0.0 | sudo tee /opt/rocm-4.0.0/.info/version
-
-* 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.
-
-
-
-# AMD ROCm Documentation Updates
-
-## AMD ROCm Installation Guide 
-
-The AMD ROCm Installation Guide in this release includes:
-
-* Supported Environments
-
-* Installation Instructions for v4.0
-
-* HIP Installation Instructions 
-
-* AMD ROCm and Mesa Multimedia Installation 
-
-* Using CMake with AMD ROCm 
-
-For more information, refer to the ROCm documentation website at:
-
-https://rocmdocs.amd.com/en/latest/
-
-
-## AMD ROCm - HIP Documentation Updates
-
-* HIP Programming Guide v4.0 
-
-https://github.com/RadeonOpenCompute/ROCm/blob/master/HIP_Programming_Guide_v4.0.pdf
-
-* HIP API Guide v4.0
-
-https://github.com/RadeonOpenCompute/ROCm/blob/master/HIP-API_Guide_v4.0.pdf
-
-* HIP FAQ  
-
-For more information, refer to
-
-https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-FAQ.html#hip-faq
-
-
-## ROCm SMI API Documentation Updates 
-
-* xGMI API
-
-For more information, refer to the ROCm SMI API Guide at,
-
-https://github.com/RadeonOpenCompute/ROCm/blob/master/ROCm_SMI_API_Guide_v4.0.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
-
-## INTRODUCING AMD INSTINCT MI100
-
-The AMD Instinct™ MI100 accelerator is the world’s fastest HPC GPU, and a culmination of the AMD CDNA architecture, with all-new Matrix Core Technology, and AMD ROCm™ open ecosystem to deliver new levels of performance, portability, and productivity. AMD CDNA is an all-new GPU architecture from AMD to drive accelerated computing into the era of exascale computing. The new architecture augments scalar and vector processing with new Matrix Core Engines and adds Infinity Fabric™ technology to scale up to larger systems. The open ROCm ecosystem puts customers in control and is a robust, mature platform that is easy to develop for and capable of running the most critical applications. The overall result is that the MI100 is the first GPU to break the 10TFLOP/s FP64 barrier designed as the steppingstone to the next generation of Exascale systems that will deliver pioneering discoveries in machine learning and scientific computing.
-
-
-### Key Features of AMD Instinct™ MI100 
-
-Important features of the AMD Instinct™ MI100 accelerator include:
-
-* Extended matrix core engine with Matrix Fused Multiply-Add (MFMA) for mixed-precision arithmetic and operates on KxN matrices (FP32, FP16, BF16, Int8) 
-
-* Added native support for the bfloat16 data type
-
-* 3 Infinity fabric connections per GPU enable a fully connected group of 4 GPUs in a ‘hive’ 
-
-![Screenshot](https://github.com/Rmalavally/ROCm/blob/master/images/keyfeatures.PNG)
-
-
-### Matrix Core Engines and GFX908 Considerations
-
-The AMD CDNA architecture builds on GCN’s foundation of scalars and vectors and adds matrices while simultaneously adding support for new numerical formats for machine learning and preserving backward compatibility for any software written for the GCN architecture. These Matrix Core Engines add a new family of wavefront-level instructions, the Matrix Fused MultiplyAdd or MFMA. The MFMA family performs mixed-precision arithmetic and operates on KxN matrices using four different types of input data: 8-bit integers (INT8), 16-bit half-precision FP (FP16), 16-bit brain FP (bf16), and 32-bit single-precision (FP32). All MFMA instructions produce either a 32-bit integer (INT32) or FP32 output, which reduces the likelihood of overflowing during the final accumulation stages of matrix multiplication.
-
-On nodes with gfx908, MFMA instructions are available to substantially speed up matrix operations. This hardware feature is used only in matrix multiplications functions in rocBLAS and supports only three base types f16_r, bf16_r, and f32_r. 
-
-* For half precision (f16_r and bf16_r) GEMM, use the function rocblas_gemm_ex, and set the compute_type parameter to f32_r.
-
-* For single precision (f32_r) GEMM, use the function rocblas_sgemm.
-
-* For single precision complex (f32_c) GEMM, use the function rocblas_cgemm.
-
-
-### References
-* For more information about bfloat16, see 
-
-https://rocblas.readthedocs.io/en/master/usermanual.html
-
-* For more details about AMD Instinct™ MI100 accelerator key features, see 
-
-https://www.amd.com/system/files/documents/instinct-mi100-brochure.pdf
-
-* For more information about the AMD Instinct MI100 accelerator, refer to the following sources:
-
-  - AMD CDNA whitepaper at https://www.amd.com/system/files/documents/amd-cdna-whitepaper.pdf
-  
-  - MI100 datasheet at https://www.amd.com/system/files/documents/instinct-mi100-brochure.pdf
-
-* AMD Instinct MI100/CDNA1 Shader Instruction Set Architecture (Dec. 2020) – This document describes the current environment, organization, and program state of AMD CDNA “Instinct MI100” devices. It details the instruction set and the microcode formats native to this family of processors that are accessible to programmers and compilers.
-
-https://developer.amd.com/wp-content/resources/CDNA1_Shader_ISA_14December2020.pdf
-
-
-## RAS ENHANCEMENTS
-
-RAS (Reliability, Availability, and Accessibility) features provide help with data center GPU management. It is a method provided to users to track and manage data points via options implemented in the ROCm-SMI Command Line Interface (CLI) tool. 
-
-For more information about rocm-smi, see 
-
-https://github.com/RadeonOpenCompute/ROC-smi 
-
-The command options are wrappers of the system calls into the device driver interface as described here:
-
-https://dri.freedesktop.org/docs/drm/gpu/amdgpu.html#amdgpu-ras-support
-
-
-
-## USING CMake with AMD ROCm
-
-Most components in AMD ROCm support CMake 3.5 or higher out-of-the-box and do not require any special Find modules. A Find module is often used downstream to find the files by guessing locations of files with platform-specific hints. Typically, the Find module is required when the upstream is not built with CMake or the package configuration files are not available.
-
-AMD ROCm provides the respective config-file packages, and this enables find_package to be used directly. AMD ROCm does not require any Find module as the config-file packages are shipped with the upstream projects.
-
-For more information, see 
-
-https://rocmdocs.amd.com/en/latest/Installation_Guide/Using-CMake-with-AMD-ROCm.html
-
-
-## AMD ROCm and Mesa Multimedia
-
-AMD ROCm extends support to Mesa Multimedia. Mesa is an open-source software implementation of OpenGL, Vulkan, and other graphics API specifications. Mesa translates these specifications to vendor-specific graphics hardware drivers.
-
-For detailed installation instructions, refer to
-
-https://rocmdocs.amd.com/en/latest/Installation_Guide/Mesa-Multimedia-Installation.html
-
-
-## ROCm System Management Information 
-
-The following enhancements are made to ROCm System Management Interface (SMI).
-
-### Support for Printing PCle Information on AMD Instinct™100
-
-AMD ROCm extends support for printing PCle information on AMD Instinct MI100. 
-
-To check the pp_dpm_pcie file, use *"rocm-smi --showclocks"*.
-
-*/opt/rocm-4.0.0-6132/bin/rocm_smi.py  --showclocks*
-
-![Screenshot](https://github.com/Rmalavally/ROCm/blob/master/images/SMI.PNG)
-
-
-### New API for xGMI 
-
-Rocm_smi_lib now provides an API that exposes xGMI (inter-chip Global Memory Interconnect) throughput from one node to another. 
-
-Refer to the rocm_smi_lib API documentation for more details. 
-
-https://github.com/RadeonOpenCompute/ROCm/blob/master/ROCm_SMI_API_Guide_v4.0.pdf
-
-
-
-
-## AMD GPU Debugger Enhancements
-
-In this release, AMD GPU Debugger has the following enhancements:
-
-* ROCm v4.0 ROCgdb is based on gdb 10.1
-
-* Extended support for AMD Instinct™ MI100 
-
-
-
-
-# Known Issues 
-
-The following are the known issues in this release.
-
-## Upgrade to AMD ROCm v4.0 Not Supported
-
-An upgrade from previous releases to AMD ROCm v4.0 is not supported. A fresh and clean installation of AMD ROCm v4.0 is recommended. 
-
-
-
-# Deprecations
-
-This section describes deprecations and removals in AMD ROCm.
-
-## Compiler Generated Code Object Version 2 Deprecation 
-
-**WARNING**
-
-Compiler-generated code object version 2 is no longer supported and will be removed shortly. AMD ROCm users must plan for the code object version 2 deprecation immediately. 
-
-Support for loading code object version 2 is also being deprecated with no announced removal release.
-
-## ROCr Runtime Deprecations
-
-The following ROCr Runtime enumerations, functions, and structs are deprecated in the AMD ROCm v4.0 release.
-
-### Deprecated ROCr Runtime Functions
-
-* hsa_isa_get_info
-
-* hsa_isa_compatible
-
-* hsa_executable_create
-
-* hsa_executable_get_symbol
-
-* hsa_executable_iterate_symbols
-
-* hsa_code_object_serialize
-
-* hsa_code_object_deserialize
-
-* hsa_code_object_destroy
-
-* hsa_code_object_get_info
-
-* hsa_executable_load_code_object
-
-* hsa_code_object_get_symbol
-
-* hsa_code_object_get_symbol_from_name
-
-* hsa_code_symbol_get_info
-
-* hsa_code_object_iterate_symbols
-
-
-### Deprecated ROCr Runtime Enumerations
-
-* HSA_ISA_INFO_CALL_CONVENTION_COUNT
-
-* HSA_ISA_INFO_CALL_CONVENTION_INFO_WAVEFRONT_SIZE
-
-* HSA_ISA_INFO_CALL_CONVENTION_INFO_WAVEFRONTS_PER_COMPUTE_UNIT
-
-* HSA_EXECUTABLE_SYMBOL_INFO_MODULE_NAME_LENGTH
-
-* HSA_EXECUTABLE_SYMBOL_INFO_MODULE_NAME
-
-* HSA_EXECUTABLE_SYMBOL_INFO_AGENT
-
-* HSA_EXECUTABLE_SYMBOL_INFO_VARIABLE_ALLOCATION
-
-* HSA_EXECUTABLE_SYMBOL_INFO_VARIABLE_SEGMENT
-
-* HSA_EXECUTABLE_SYMBOL_INFO_VARIABLE_ALIGNMENT
-
-* HSA_EXECUTABLE_SYMBOL_INFO_VARIABLE_SIZE
-
-* HSA_EXECUTABLE_SYMBOL_INFO_VARIABLE_IS_CONST
-
-* HSA_EXECUTABLE_SYMBOL_INFO_KERNEL_CALL_CONVENTION
-
-* HSA_EXECUTABLE_SYMBOL_INFO_INDIRECT_FUNCTION_CALL_CONVENTION
-
-   - hsa_code_object_type_t
-   
-   - hsa_code_object_info_t
-   
-   - hsa_code_symbol_info_t
-
-
-### Deprecated ROCr Runtime Structs
-
-* hsa_code_object_t
-
-* hsa_callback_data_t
-
-* hsa_code_symbol_t
-
-
-
-## AOMP Deprecation
-
-As of AMD ROCm v4.0, AOMP (aomp-amdgpu) is deprecated. OpenMP support has moved to the openmp-extras auxiliary package, which leverages the ROCm compiler on LLVM 12.
-
-For more information, refer to 
-
-https://rocmdocs.amd.com/en/latest/Programming_Guides/openmp_support.html
-
-
-# Deploying ROCm
-
-AMD hosts both Debian and RPM repositories for the ROCm v4.0.0 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.
-
-#### 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, 
-
-* 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 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 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 in ROCm 2.9.x
-* 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.
-
-#### 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 |
-
-
-
-
+
+# AMD ROCm Release Notes v3.7.0
+
+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 this release.
+
+- [Supported Operating Systems and Documentation Updates](#Supported-Operating-Systems-and-Documentation-Updates)
+  * [Supported Operating Systems](#Supported-Operating-Systems)
+  * [AMD ROCm Documentation Updates](#AMD-ROCm-Documentation-Updates)
+   
+- [What\'s New in This Release](#Whats-New-in-This-Release)
+  * [AOMP Enhancements](#AOMP-Enhancements)
+  * [Compatibility with NVIDIA Communications Collective Library v2\.7 API](#Compatibility-with-NVIDIA-Communications-Collective-Library-v27-API)
+  * [Singular Value Decomposition of Bi\-diagonal Matrices](#Singular-Value-Decomposition-of-Bi-diagonal-Matrices)
+  * [rocSPARSE_gemmi\() Operations for Sparse Matrices](#rocSPARSE_gemmi-Operations-for-Sparse-Matrices)
+    
+ 
+- [Known Issues](#Known-Issues)
+
+- [Deploying ROCm](#Deploying-ROCm)
+ 
+- [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)
+  
+
+
+# Supported Operating Systems 
+
+## Support for Ubuntu 20.04 
+
+
+In this release, AMD ROCm extends support to Ubuntu 20.04, including dual-kernel.
+
+## List of Supported Operating Systems
+
+The AMD ROCm v3.7.x platform is designed to support the following operating systems:
+
+* Ubuntu 20.04 and 18.04.4 (Kernel 5.3)	
+* 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
+
+## Fresh Installation of AMD ROCm v3.7 Recommended
+A fresh and clean installation of AMD ROCm v3.7 is recommended. An upgrade from previous releases to AMD ROCm v3.7 is not supported.
+
+For more information, refer to the AMD ROCm Installation Guide at:
+
+https://github.com/RadeonOpenCompute/ROCm/blob/roc-3.7.x/ROCm_Installation_Guide_v3.7.md
+
+**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.
+
+
+# AMD ROCm Documentation Updates
+
+## AMD ROCm Installation Guide 
+
+The AMD ROCm Installation Guide in this release includes:
+
+* Updated Supported Environments
+
+https://github.com/RadeonOpenCompute/ROCm/blob/roc-3.7.x/ROCm_Installation_Guide_v3.7.md
+
+
+## AMD ROCm - HIP Documentation Updates
+
+### Texture and Surface Functions
+The documentation for Texture and Surface functions is updated and available at:
+
+https://rocmdocs.amd.com/en/latest/Programming_Guides/Kernel_language.html
+
+### Warp Shuffle Functions
+The documentation for Warp Shuffle functions is updated and available at:
+
+https://rocmdocs.amd.com/en/latest/Programming_Guides/Kernel_language.html
+
+### Compiler Defines and Environment Variables
+The documentation for the updated HIP Porting Guide is available at:
+
+https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-porting-guide.html#hip-porting-guide
+
+
+## AMD ROCm Debug Agent
+
+ROCm Debug Agent Library 
+
+https://rocmdocs.amd.com/en/latest/ROCm_Tools/rocm-debug-agent.html
+
+
+## General AMD ROCm Documentatin 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/Installation-Guide.html#build-amd-rocm
+
+* For AMD ROCm Release History, see
+
+  https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#amd-rocm-version-history
+
+
+
+# What\'s New in This Release
+
+## AOMP ENHANCEMENTS
+
+AOMP is a scripted build of LLVM. It supports OpenMP target offload on AMD GPUs. Since AOMP is a Clang/LLVM compiler, it also supports GPU offloading with HIP, CUDA, and OpenCL.
+
+The following enhancements are made for AOMP in this release: 
+* OpenMP 5.0 is enabled by default. You can use -fopenmp-version=45 for OpenMP 4.5 compliance
+* Restructured to include the ROCm compiler
+* B=Bitcode search path using hip policy HIP_DEVICE_LIB_PATH and hip-devic-lib command line option to enable global_free for kmpc_impl_free
+
+Restructured hostrpc, including:
+* Replaced hostcall register functions with handlePayload(service, payload). Note, handlPayload has a simple switch to call the correct service handler function.
+* Removed the WITH_HSA macro
+* Moved the hostrpc stubs and host fallback functions into a single library and the include file. This enables the stubs openmp cpp source instead of hip and reorganizes the directory openmp/libomptarget/hostrpc.
+* Moved hostrpc_invoke.cl to DeviceRTLs/amdgcn.
+* Generalized the vargs processing in printf to work for any vargs function to execute on the host, including a vargs function that uses a function pointer.
+* Reorganized files, added global_allocate and global_free.
+* Fixed llvm TypeID enum to match the current upstream llvm TypeID.
+* Moved strlen_max function inside the declare target #ifdef _DEVICE_GPU in hostrpc.cpp to resolve linker failure seen in pfspecifier_str smoke test.
+* Fixed AOMP_GIT_CHECK_BRANCH in aomp_common_vars to not block builds in Red Hat if the repository is on a specific commit hash.
+* Simplified and reduced the size of openmp host runtime
+* Switched to default OpenMP 5.0
+
+For more information, see https://github.com/ROCm-Developer-Tools/aomp
+     
+
+## ROCm COMMUNICATIONS COLLECTIVE LIBRARY
+
+### Compatibility with NVIDIA Communications Collective Library v2\.7 API
+
+ROCm Communications Collective Library (RCCL) is now compatible with the NVIDIA Communications Collective Library (NCCL) v2.7 API.
+
+RCCL (pronounced "Rickle") is a stand-alone library of standard collective communication routines for GPUs, implementing all-reduce, all-gather, reduce, broadcast, reduce-scatter, gather, scatter, and all-to-all. There is also initial support for direct GPU-to-GPU send and receive operations. It has been optimized to achieve high bandwidth on platforms using PCIe, xGMI as well as networking using InfiniBand Verbs or TCP/IP sockets. RCCL supports an arbitrary number of GPUs installed in a single node or multiple nodes, and can be used in either single- or multi-process (e.g., MPI) applications.
+
+The collective operations are implemented using ring and tree algorithms and have been optimized for throughput and latency. For best performance, small operations can be either batched into larger operations or aggregated through the API.
+
+For more information about RCCL APIs and compatibility with NCCL v2.7, see
+https://rccl.readthedocs.io/en/develop/index.html
+
+
+## Singular Value Decomposition of Bi\-diagonal Matrices
+
+Rocsolver_bdsqr now computes the Singular Value Decomposition (SVD) of bi-diagonal matrices. It is an auxiliary function for the SVD of general matrices (function rocsolver_gesvd). 
+
+BDSQR computes the singular value decomposition (SVD) of a n-by-n bidiagonal matrix B.
+
+The SVD of B has the following form:
+
+B = Ub * S * Vb'
+where 
+•	S is the n-by-n diagonal matrix of singular values of B
+•	the columns of Ub are the left singular vectors of B
+•	the columns of Vb are its right singular vectors
+
+The computation of the singular vectors is optional; this function accepts input matrices U (of size nu-by-n) and V (of size n-by-nv) that are overwritten with U*Ub and Vb’*V. If nu = 0 no left vectors are computed; if nv = 0 no right vectors are computed.
+
+Optionally, this function can also compute Ub’*C for a given n-by-nc input matrix C.
+
+PARAMETERS
+
+•	[in] handle: rocblas_handle.
+
+•	[in] uplo: rocblas_fill.
+
+Specifies whether B is upper or lower bidiagonal.
+
+•	[in] n: rocblas_int. n >= 0.
+
+The number of rows and columns of matrix B.
+
+•	[in] nv: rocblas_int. nv >= 0. 
+
+The number of columns of matrix V.
+
+•	[in] nu: rocblas_int. nu >= 0. 
+
+The number of rows of matrix U.
+
+•	[in] nc: rocblas_int. nu >= 0. 
+
+The number of columns of matrix C.
+
+•	[inout] D: pointer to real type. Array on the GPU of dimension n.
+
+On entry, the diagonal elements of B. On exit, if info = 0, the singular values of B in decreasing order; if info > 0, the diagonal elements of a bidiagonal matrix orthogonally equivalent to B.
+
+•	[inout] E: pointer to real type. Array on the GPU of dimension n-1.
+
+On entry, the off-diagonal elements of B. On exit, if info > 0, the off-diagonal elements of a bidiagonal matrix orthogonally equivalent to B (if info = 0 this matrix converges to zero).
+
+•	[inout] V: pointer to type. Array on the GPU of dimension ldv*nv.
+
+On entry, the matrix V. On exit, it is overwritten with Vb’*V. (Not referenced if nv = 0).
+
+•	[in] ldv: rocblas_int. ldv >= n if nv > 0, or ldv >=1 if nv = 0.
+
+Specifies the leading dimension of V.
+
+•	[inout] U: pointer to type. Array on the GPU of dimension ldu*n.
+
+On entry, the matrix U. On exit, it is overwritten with U*Ub. (Not referenced if nu = 0).
+
+•	[in] ldu: rocblas_int. ldu >= nu.
+
+Specifies the leading dimension of U.
+
+•	[inout] C: pointer to type. Array on the GPU of dimension ldc*nc.
+
+On entry, the matrix C. On exit, it is overwritten with Ub’*C. (Not referenced if nc = 0).
+
+•	[in] ldc: rocblas_int. ldc >= n if nc > 0, or ldc >=1 if nc = 0.
+
+Specifies the leading dimension of C.
+
+•	[out] info: pointer to a rocblas_int on the GPU.
+
+If info = 0, successful exit. If info = i > 0, i elements of E have not converged to zero.
+
+For more information, see
+https://rocsolver.readthedocs.io/en/latest/userguide_api.html#rocsolver-type-bdsqr
+
+
+### rocSPARSE_gemmi\() Operations for Sparse Matrices
+
+This enhancement provides a dense matrix sparse matrix multiplication using the CSR storage format.
+rocsparse_gemmi multiplies the scalar αα with a dense m×km×k matrix AA and the sparse k×nk×n matrix BB defined in the CSR storage format, and adds the result to the dense m×nm×n matrix CC that is multiplied by the scalar ββ, such that
+C:=α⋅op(A)⋅op(B)+β⋅CC:=α⋅op(A)⋅op(B)+β⋅C
+with
+
+op(A)=⎧⎩⎨⎪⎪A,AT,AH,if trans_A == rocsparse_operation_noneif trans_A == rocsparse_operation_transposeif trans_A == rocsparse_operation_conjugate_transposeop(A)={A,if trans_A == rocsparse_operation_noneAT,if trans_A == rocsparse_operation_transposeAH,if trans_A == rocsparse_operation_conjugate_transpose
+
+and
+
+op(B)=⎧⎩⎨⎪⎪B,BT,BH,if trans_B == rocsparse_operation_noneif trans_B == rocsparse_operation_transposeif trans_B == rocsparse_operation_conjugate_transposeop(B)={B,if trans_B == rocsparse_operation_noneBT,if trans_B == rocsparse_operation_transposeBH,if trans_B == rocsparse_operation_conjugate_transpose
+Note: This function is non-blocking and executed asynchronously with the host. It may return before the actual computation has finished.
+
+For more information and examples, see
+https://rocsparse.readthedocs.io/en/master/usermanual.html#rocsparse-gemmi
+ 
+
+# Known Issues 
+The following are the known issues in this release.
+
+## (AOMP) ‘Undefined Hidden Symbol’ Linker Error Causes Compilation Failure in HIP
+
+The HIP example device_lib fails to compile due to unreferenced symbols with Link Time Optimization resulting in ‘undefined hidden symbol’ errors. 
+
+This issue is under investigation and there is no known workaround at this time.
+
+
+## MIGraphX Fails for fp16 Datatype
+The MIGraphX functionality does not work for the fp16 datatype.  
+
+The following workaround is recommended: 
+
+Use the AMD ROCm v3.3 of MIGraphX 
+
+Or
+
+Build MIGraphX v3.7 from the source using AMD ROCm v3.3
+
+## Missing Google Test Installation May Cause RCCL Unit Test Compilation Failure
+Users of the RCCL install.sh script may encounter an RCCL unit test compilation error. It is recommended to use CMAKE directly instead of install.sh to compile RCCL. Ensure Google Test 1.10+ is available in the CMAKE search path.
+
+
+As a workaround, use the latest RCCL from the GitHub development branch at:
+https://github.com/ROCmSoftwarePlatform/rccl/pull/237
+
+
+## Issue with Peer-to-Peer Transfers 
+Using peer-to-peer (P2P) transfers on systems without the hardware P2P assistance may produce incorrect results.
+
+Ensure the hardware supports peer-to-peer transfers and enable the peer-to-peer setting in the hardware to resolve this issue. 
+
+
+## Partial Loss of Tracing Events for Large Applications
+An internal tracing buffer allocation issue can cause a partial loss of some tracing events for large applications.
+
+As a workaround, rebuild the roctracer/rocprofiler libraries from the GitHub ‘roc-3.7’ branch at:
+•	https://github.com/ROCm-Developer-Tools/rocprofiler
+•	https://github.com/ROCm-Developer-Tools/roctracer
+
+
+## GPU Kernel C++ Names Not Demangled
+GPU kernel C++ names in the profiling traces and stats produced by ‘—hsa-trace’ option are not demangled.
+
+As a workaround, users may choose to demangle the GPU kernel C++ names as required.
+
+
+## ‘rocprof’ option ‘--parallel-kernels’ Not Supported in This Release
+
+‘rocprof’ option ‘--parallel-kernels’ is available in the options list, however,  it is not fully validated and supported in this release.
+
+## Random Soft Hang Observed When Running ResNet-Based Models
+
+A random soft hang is observed when running ResNet-based models for a loop run of more than 25 to 30 hours.  The issue is observed on both PyTorch and TensorFlow frameworks.
+You can terminate the unresponsive process to temporarily resolve the issue.
+
+There is no known workaround at this time.
+
+
+
+# Deploying ROCm
+AMD hosts both Debian and RPM repositories for the ROCm v3.7.x packages. 
+
+For more information on ROCM installation on all platforms, see
+
+https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
+
+# 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.
+
+#### 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.
+
+ROCm officially supports AMD GPUs that use following chips:
+
+  * GFX8 GPUs
+    * "Fiji" chips, such as on the AMD Radeon R9 Fury X and Radeon Instinct MI8
+    * "Polaris 10" chips, such as on the AMD Radeon RX 580 and Radeon Instinct MI6
+  * 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
+
+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://rocm.github.io/hardware.html).
+
+#### 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 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 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 in ROCm 2.9.x
+* 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.
+
+#### 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 |
+
+
+
+## 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#machine-learning-and-high-performance-computing-software-stack-for-amd-gpu-v3-5-0

ROCm_Installation_Guide_v3.7.md

@@ -0,0 +1,444 @@
+![AMD Logo](amdblack.jpg)
+
+
+# AMD ROCm Installation Guide v3.7
+
+## Install AMD ROCm
+
+
+-   [Deploying ROCm](#deploying-rocm)
+
+-   [Prerequisites](#prerequisites-1)
+
+-   [Install ROCm on Supported Operating Systems](#supported-operating-systems)
+
+     -   [Ubuntu](#ubuntu)
+     -   [CentOS RHEL](#centos-rhel)
+     -   [SLES 15 Service Pack 1](#sles-15-service-pack-1)
+    
+-   [ROCm Installation Known Issues and
+    Workarounds](#rocm-installation-known-issues-and-workarounds)
+
+
+## Deploying ROCm 
+
+AMD hosts both Debian and RPM repositories for the ROCm v3.x packages.
+
+The following directions show how to install ROCm on supported Debian-based systems such as Ubuntu 18.04.x
+
+**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.
+
+
+## Prerequisites
+
+In this release, AMD ROCm extends support to Ubuntu 20.04, including dual kernel.
+
+The AMD ROCm platform is designed to support the following operating systems:
+
+-   Ubuntu 20.04 (5.4 and 5.6-oem) and 18.04.4 (Kernel 5.3)
+-   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
+
+### FRESH INSTALLATION OF AMD ROCm V3.7 RECOMMENDED
+
+A fresh and clean installation of AMD ROCm v3.7 is recommended. An upgrade from previous releases to AMD ROCm v3.7 is not supported.
+
+**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 unchanged - */opt/rocm/opencl/bin/x86\_64/clinfo*.
+
+    
+## Supported Operating Systems
+
+### 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.
+
+For Debian-based systems like Ubuntu, configure the Debian ROCm repository as follows:
+
+**Note**: The public key has changed to reflect the new location. You must update to the new location as the old key will be removed in a
+future release.
+
+-   Old Key: <http://repo.radeon.com/rocm/apt/debian/rocm.gpg.key>
+-   New Key: <http://repo.radeon.com/rocm/rocm.gpg.key>
+
+
+```
+    wget -q -O - http://repo.radeon.com/rocm/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 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.
+
+The current rocm.gpg.key is not available in a standard key ring distribution, but has the following sha1sum hash:
+
+    e85a40d1a43453fe37d63aa6899bc96e08f2817a rocm.gpg.key
+
+3.  Install the ROCm meta-package. Update the appropriate repository list and install the rocm-dkms meta-package:
+
+```
+    sudo apt update
+
+    sudo apt install rocm-dkms && sudo reboot
+ ```
+
+4.  Set permissions. To access the GPU, you must be a user in the video and render groups. Ensure your user account is a member of the video
+    and render groups 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 and render groups, use the following command with the sudo password:
+
+```
+    sudo usermod -a -G video $LOGNAME
+
+    sudo usermod -a -G render $LOGNAME
+    
+```
+
+6.  By default, you must add any future users to the video and render groups. To add future users to the video and render groups, run the
+    following command:
+
+```
+    echo 'ADD_EXTRA_GROUPS=1' | sudo tee -a /etc/adduser.conf
+
+    echo 'EXTRA_GROUPS=video' | sudo tee -a /etc/adduser.conf
+
+    echo 'EXTRA_GROUPS=render' | sudo tee -a /etc/adduser.conf
+ 
+ ```
+
+7.  Restart the system.
+
+8.  After restarting the system, run the following commands to verify that the ROCm installation is successful. If you see your GPUs
+    listed by both commands, the installation is considered successful.
+
+```
+    /opt/rocm/bin/rocminfo
+    /opt/rocm/opencl/bin/clinfo
+    
+ ```
+
+**Note**: To run the ROCm programs, add the ROCm binaries in your PATH.
+
+```
+
+    echo 'export PATH=$PATH:/opt/rocm/bin:/opt/rocm/profiler/bin:/opt/rocm/opencl/bin' | sudo tee -a /etc/profile.d/rocm.sh
+
+```
+
+#### Uninstalling ROCm Packages from Ubuntu
+
+To uninstall the ROCm packages from Ubuntu 16.04.6 or Ubuntu 18.04.4, run the following command:
+
+    sudo apt autoremove rocm-opencl rocm-dkms rocm-dev rocm-utils && sudo reboot
+
+#### Installing Development Packages for Cross Compilation
+
+It is recommended that you develop and test development packages 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.
+
+Instead, install the following development subset of packages:
+
+    sudo apt update
+    sudo apt install rocm-dev
+
+**Note**: To execute ROCm enabled applications, you must install the full ROCm driver stack on your system.
+
+#### 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:
+
+    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
+
+
+### CentOS RHEL
+
+#### CentOS v7.7/RHEL v7.8 and CentOS/RHEL 8.1
+
+This section describes how to install ROCm on supported RPM-based systems such as CentOS v7.7/RHEL v7.8 and CentOS/RHEL v8.1.
+
+#### Preparing RHEL 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.
+
+**Note**: The following steps do not apply to the CentOS installation.
+
+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.
+    
+2.  Enable the following repositories for RHEL v7.x:
+
+```
+    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/epel-release-latest-8 repository RPM:
+
+```
+    sudo rpm -ivh <repo>
+```
+
+For more details,
+
+-   For RHEL v7.x, see
+    <https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm>
+    
+-   For RHEL v8.x, see
+    <https://dl.fedoraproject.org/pub/epel/epel-release-latest-8.noarch.rpm>
+    
+
+4.  Install and set up Devtoolset-7.
+
+**Note**: Devtoolset is not required for CentOS/RHEL v8.x
+
+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 v7.7/v8.1 for DKMS
+
+Use the dkms tool to install the kernel drivers on CentOS/RHEL:
+
+    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:
+
+     -   CentOS/RHEL 7.x : <http://repo.radeon.com/rocm/yum/rpm>
+     -   CentOS/RHEL 8.x : <http://repo.radeon.com/rocm/centos8/rpm>
+
+```
+    [ROCm] 
+    name=ROCm
+    baseurl=http://repo.radeon.com/rocm/yum/rpm
+    enabled=1
+    gpgcheck=1
+    gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key
+
+```
+
+**Note**: The URL of the repository must point to the location of the repositories' repodata database.
+
+3.  Install ROCm components using the following command:
+
+**Note**: This step is applicable only for CentOS/RHEL v8.1 and is not required for v7.8.
+
+```
+    sudo yum install rocm-dkms && sudo reboot
+    
+```
+
+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 with the sudo password:
+
+```
+    sudo usermod -a -G video $LOGNAME
+ ```
+
+7.  By default, add any future users to the video group. Run the following command to add users to the video group:
+
+```
+    echo 'ADD_EXTRA_GROUPS=1' | sudo tee -a /etc/adduser.conf
+    echo 'EXTRA_GROUPS=video' | sudo tee -a /etc/adduser.conf
+```
+
+**Note**: Before updating to the latest version of the operating system, delete the ROCm packages to avoid DKMS-related issues.
+
+8.  Restart the system.
+
+9.  Test the ROCm installation.
+
+#### Testing the ROCm Installation
+
+After restarting the system, run the following commands to verify that the ROCm installation is successful. If you see your GPUs listed, you
+are good to go!
+
+    /opt/rocm/bin/rocminfo
+    /opt/rocm/opencl/bin/clinfo
+
+**Note**: Add the ROCm binaries in your PATH for easy implementation of the ROCm programs.
+
+    echo 'export PATH=$PATH:/opt/rocm/bin:/opt/rocm/profiler/bin:/opt/rocm/opencl/bin' | 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
+
+To uninstall the ROCm packages, run the following command:
+
+    sudo yum autoremove rocm-opencl 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  
+    sudo reboot
+
+**Note**: You can use this command instead of installing rocm-dkms.
+
+**Note**: Ensure you restart the system after ROCm installation.
+
+
+### 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 http://repo.radeon.com/rocm/zyp/zypper/ rocm
+    sudo zypper ref
+    sudo rpm --import http://repo.radeon.com/rocm/rocm.gpg.key
+    sudo zypper --gpg-auto-import-keys 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/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 with 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/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\'\|sudo
+     tee -a /etc/profile.d/rocm.sh
+
+#### Uninstallation
+
+To uninstall, use the following command:
+
+    sudo zypper remove rocm-opencl 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. If the command does not remove all the ROCm components/packages, ensure
+you remove them individually.
+
+
+## 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

default.xml

@@ -1,27 +1,27 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <manifest>
     <remote name="roc-github"
-fetch="http://github.com/RadeonOpenCompute/" />
+            fetch="http://github.com/RadeonOpenCompute/" />
     <remote name="rocm-devtools"
-fetch="https://github.com/ROCm-Developer-Tools/" />
+            fetch="https://github.com/ROCm-Developer-Tools/" />
     <remote name="rocm-swplat"
-fetch="https://github.com/ROCmSoftwarePlatform/" />
+            fetch="https://github.com/ROCmSoftwarePlatform/" />
     <remote name="gpuopen-libs"
-fetch="https://github.com/GPUOpen-ProfessionalCompute-Libraries/" />
+            fetch="https://github.com/GPUOpen-ProfessionalCompute-Libraries/" />
     <remote name="gpuopen-tools"
-fetch="https://github.com/GPUOpen-Tools/" />
+            fetch="https://github.com/GPUOpen-Tools/" />
     <remote name="KhronosGroup"
-fetch="https://github.com/KhronosGroup/" />
-    <default revision="refs/tags/rocm-4.0.0"
-remote="roc-github"
-sync-c="true"
-sync-j="4" />
-<!--list of projects for ROCM-->
+            fetch="https://github.com/KhronosGroup/" />
+    <default revision="refs/tags/rocm-3.7.0"
+             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" />
+    <project name="rocm_smi_lib" remote="roc-github" />
     <project name="rocm-cmake" />
     <project name="rocminfo" />
     <project name="rocprofiler" remote="rocm-devtools" />
@@ -29,25 +29,23 @@ sync-j="4" />
     <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" />
-<!--HIP Projects-->
+    <!--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" />
+    <!-- The following projects are all associated with the AMDGPU LLVM compiler -->
+    <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="rocr_debug_agent" remote="rocm-devtools" revision="refs/tags/roc-3.7.0" />
     <project name="rocm_bandwidth_test" />
-    <project name="half" remote="rocm-swplat" revision="37742ce15b76b44e4b271c1e66d13d2fa7bd003e" />
     <project name="RCP" remote="gpuopen-tools" revision="3a49405a1500067c49d181844ec90aea606055bb" />
-<!-- gdb projects -->
+    <!-- gdb projects -->
     <project name="ROCgdb" remote="rocm-devtools" />
     <project name="ROCdbgapi" remote="rocm-devtools" />
-<!-- ROCm Libraries -->
-    <project name="rdc" remote="roc-github" />
+    <!-- ROCm Libraries -->
     <project name="rocBLAS" remote="rocm-swplat" />
     <project name="hipBLAS" remote="rocm-swplat" />
     <project name="rocFFT" remote="rocm-swplat" />
@@ -63,11 +61,19 @@ sync-j="4" />
     <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="AMDMIGraphX" remote="rocm-swplat" />
+    <project name="AMDMIGraphX" remote="rocm-swplat" revision="e66968a25f9342a28af1157b06cbdbf8579c5519" />
     <project name="ROCmValidationSuite" remote="rocm-devtools" />
-<!-- Projects for OpenMP-Extras -->
-    <project name="aomp" path="openmp-extras/aomp" remote="rocm-devtools" />
-    <project name="aomp-extras" path="openmp-extras/aomp-extras" remote="rocm-devtools" />
-    <project name="flang" path="openmp-extras/flang" remote="rocm-devtools" />
+    <!-- Projects for AOMP -->
+    <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" />
 </manifest>

version_history.md

@@ -0,0 +1,503 @@
+## ROCm Version History
+This file contains archived version history information for the [ROCm project](https://github.com/RadeonOpenCompute/ROCm)
+
+### Current ROCm Version: 3.3
+- [New features and enhancements in ROCm v3.1](#new-features-and-enhancements-in-rocm-v31)
+- [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 v3.2
+The AMD ROCm v3.2 release was not productized.
+
+## New features and enhancements in ROCm v3.1
+### 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.
+
+### Reliability, Accessibility, and Serviceability Support for Vega 7nm
+
+The Reliability, Accessibility, and Serviceability (RAS) support for Vega7nm is now available.
+
+### 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.
+
+
+## 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