AMD ROCm Release Notes v3.9.0

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
  • ROCm Installation Updates
  • AMD ROCm Documentation Updates

• What's New in This Release

  • ROCm Compiler Enhancements
  • ROCm System Management Information
  • ROCm Math and Communication Libraries
  • ROCM AOMP Enhancements

• Fixed Defects

• Known Issues

• Deprecations

• Deploying ROCm

• Hardware and Software Support

• Machine Learning and High Performance Computing Software Stack for AMD GPU

  • ROCm Binary Package Structure
  • ROCm Platform Packages

Supported Operating Systems

Support for Ubuntu 20.04.1

In this release, AMD ROCm extends support to Ubuntu 20.04.1, including v5.4 and v5.6-oem.

Support for SLES 15 SP2

This release extends support to SLES 15 SP2.

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 & 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 SP2

ROCm Installation Updates

Fresh Installation of AMD ROCm v3.9 Recommended

A fresh and clean installation of AMD ROCm v3.9 is recommended. An upgrade from previous releases to AMD ROCm v3.9 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.

ROCm MultiVersion Installation Update

With the AMD ROCm v3.9 release, the following ROCm multi-version installation changes apply:

The meta packages rocm-dkms 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 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 <= 3.9.0

  • command: echo | sudo tee /opt/rocm-/.info/version

  • example: echo 3.9.0 | sudo tee /opt/rocm-3.9.0/.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:

• Updated Supported Environments
• Multi-version Installation Instructions

https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html

ROCm Compiler Documentation Updates

The ROCm Compiler documentation updates include,

• OpenMP – Extras v12.9-0
• OpenMP-Extras Installation
• OpenMP-Extras Source Build
• AOMP-v11.9-0
• AOMP Source Build

For more information, see

https://rocmdocs.amd.com/en/latest/Programming_Guides/openmp_support.html

For the updated ROCm SMI API Guide, see

https://github.com/RadeonOpenCompute/ROCm/blob/master/ROCm_SMI_Manual_v3.9.pdf

ROCm System Management Information

ROCM-SMI version: 1.4.1 | Kernel version: 5.6.20

• ROCm SMI and Command Line Interface
• ROCm SMI APIs for Compute Unit Occupancy
  • Usage
  • Optional Arguments
  • Display Options
  • Topology
  • Pages Information
  • Hardware-related Information
  • Software-related/controlled information
  • Set Options
  • Reset Options
  • Auto-response Options
  • Output Options

For more information, refer to

https://rocmdocs.amd.com/en/latest/ROCm_System_Managment/ROCm-System-Managment.html#rocm-command-line-interface

For ROCm SMI API Guide, see

https://github.com/RadeonOpenCompute/ROCm/blob/master/ROCm_SMI_Manual_v3.9.pdf

AMD ROCm - HIP Documentation Updates

• HIP Porting Guide – CU_Pointer_Attribute_Memory_Type

For more information, refer to

https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-porting-guide.html#hip-porting-guide

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/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

ROCm Compiler Enhancements

The ROCm compiler support in the llvm-amdgpu-12.0.dev-amd64.deb package is enhanced to include support for OpenMP. To utilize this support, the additional package openmp-extras_12.9-0_amd64.deb is required.

Note, by default, both packages are installed during the ROCm v3.9 installation. For information about ROCm installation, refer to the ROCm Installation Guide.

AMD ROCm supports the following compilers:

• C++ compiler - Clang++
• C compiler - Clang
• Flang - FORTRAN compiler (FORTRAN 2003 standard)

NOTE : All of the above-mentioned compilers support:

• OpenMP standard 4.5 and an evolving subset of the OpenMP 5.0 standard
• OpenMP computational offloading to the AMD GPUs

For more information about AMD ROCm compilers, see the Compiler Documentation section at,

https://rocmdocs.amd.com/en/latest/index.html

Auxiliary Package Supporting OpenMP

The openmp-extras_12.9-0_amd64.deb auxiliary package supports OpenMP within the ROCm compiler. It contains OpenMP specific header files, which are installed in /opt/rocm/llvm/include as well as runtime libraries, fortran runtime libraries, and device bitcode files in /opt/rocm/llvm/lib. The auxiliary package also consists of examples in the /opt/rocm/llvm/examples folder.

NOTE: The optional AOMP package resides in /opt/rocm//aomp/bin/clang and the ROCm compiler, which supports OpenMP for AMDGPU, is located in /opt/rocm/llvm/bin/clang.

AOMP Optional Package Deprecation

Before the AMD ROCm v3.9 release, the optional AOMP package provided support for OpenMP. While AOMP is available in this release, the optional package may be deprecated from ROCm in the future. It is recommended you transition to the ROCm compiler or AOMP standalone releases for OpenMP support.

Understanding ROCm Compiler OpenMP Support and AOMP OpenMP Support

The AOMP OpenMP support in ROCm v3.9 is based on the standalone AOMP v11.9-0, with LLVM v11 as the underlying system. However, the ROCm compiler's OpenMP support is based on LLVM v12 (upstream).

NOTE: Do not combine the object files from the two LLVM implementations. You must rebuild the application in its entirety using either the AOMP OpenMP or the ROCm OpenMP implementation.

Example – OpenMP Using the ROCm Compiler

$ cat helloworld.c
#include <stdio.h>
#include <omp.h>
 int main(void) {
  int isHost = 1; 
#pragma omp target map(tofrom: isHost)
  {
    isHost = omp_is_initial_device();
    printf("Hello world. %d\n", 100);
    for (int i =0; i<5; i++) {
      printf("Hello world. iteration %d\n", i);
    }
  }
   printf("Target region executed on the %s\n", isHost ? "host" : "device");
  return isHost;
}
$ /opt/rocm/llvm/bin/clang  -O3 -target x86_64-pc-linux-gnu -fopenmp -fopenmp-targets=amdgcn-amd-amdhsa -Xopenmp-target=amdgcn-amd-amdhsa -march=gfx900 helloworld.c -o helloworld
$ export LIBOMPTARGET_KERNEL_TRACE=1
$ ./helloworld
DEVID: 0 SGN:1 ConstWGSize:256  args: 1 teamsXthrds:(   1X 256) reqd:(   1X   0) n:__omp_offloading_34_af0aaa_main_l7
Hello world. 100
Hello world. iteration 0
Hello world. iteration 1
Hello world. iteration 2
Hello world. iteration 3
Hello world. iteration 4
Target region executed on the device

For more examples, see /opt/rocm/llvm/examples.

ROCm SYSTEM MANAGEMENT INFORMATION

The AMD ROCm v3.9 release consists of the following ROCm System Management Information (SMI) enhancements:

• Shows the hardware topology

• The ROCm-SMI showpids option shows per-process Compute Unit (CU) Occupancy, VRAM usage, and SDMA usage

• Support for GPU Reset Event and Thermal Throttling Event in ROCm-SMI Library

ROCm-SMI Hardware Topology

The ROCm-SMI Command Line Interface (CLI) is enhanced to include new options to denote GPU inter-connect topology in the system along with the relative distance between each other and the closest NUMA (CPU) node for each GPU.

Compute Unit Occupancy

The AMD ROCm stack now supports a user process in querying Compute Unit (CU) occupancy at a particular moment. This service can be accessed to determine if a process P is using sufficient compute units.

A periodic collection is used to build the profile of a compute unit occupancy for a workload.

ROCm supports this capability only on GFX9 devices. Users can access the functionality in two ways:

• indirectly from the SMI library

• directly via Sysfs

NOTE: On systems that have both GFX9 and non-GFX9 devices, users should interpret the compute unit (CU) occupancy value carefully as the service does not support non-GFX9 devices.

Accessing Compute Unit Occupancy Indirectly

The ROCm System Management Interface (SMI) library provides a convenient interface to determine the CU occupancy for a process. To get the CU occupancy of a process reported in percentage terms, invoke the SMI interface using rsmi_compute_process_info_by_pid_get(). The value is reported through the member field cu_occupancy of struct rsmi_process_info_t.

/**
   * @brief Encodes information about a process
   * @cu_occupancy Compute Unit usage in percent
   */
  typedef struct {
      - - -,
      uint32_t cu_occupancy;
  } rsmi_process_info_t;

  /**
   * API to get information about a process
  rsmi_status_t
      rsmi_compute_process_info_by_pid_get(uint32_t pid,
          rsmi_process_info_t *proc);

Accessing Compute Unit Occupancy Directly Using SYSFS

Information provided by SMI library is built from sysfs. For every valid device, ROCm stack surfaces a file by the name cu_occupancy in Sysfs. Users can read this file to determine how that device is being used by a particular workload. The general structure of the file path is /proc//stats_/cu_occupancy

/**
   * CU occupancy files for processes P1 and P2 on two devices with 
   * ids: 1008 and 112326
   */
  /sys/devices/virtual/kfd/kfd/proc/<Pid_1>/stats_1008/cu_occupancy
  /sys/devices/virtual/kfd/kfd/proc/<Pid_1>/stats_2326/cu_occupancy
  /sys/devices/virtual/kfd/kfd/proc/<Pid_2>/stats_1008/cu_occupancy
  /sys/devices/virtual/kfd/kfd/proc/<Pid_2>/stats_2326/cu_occupancy
  
// To get CU occupancy for a process P<i>
  for each valid-device from device-list {
    path-1 = Build path for cu_occupancy file;
    path-2 = Build path for file Gpu-Properties;
    cu_in_use += Open and Read the file path-1;
    cu_total_cnt += Open and Read the file path-2;
  }
  cu_percent = ((cu_in_use * 100) / cu_total_cnt);
  

GPU Reset Event and Thermal Throttling Event

The ROCm-SMI library clients can now register for the following events:

ROCm Math and Communication Libraries

‘rocfft_execution_info_set_stream’ API

rocFFT is a software library for computing Fast Fourier Transforms (FFT). It is part of AMD’s software ecosystem based on ROCm. In addition to AMD GPU devices, the library can be compiled with the CUDA compiler using HIP tools for running on Nvidia GPU devices.

The ‘rocfft_execution_info_set_stream’ API is a function to specify optional and additional information to control execution. This API specifies the compute stream, which must be invoked before the call to rocfft_execute. Compute stream is the underlying device queue/stream where the library computations are inserted.

PREREQUISITES

Using the compute stream API makes the following assumptions:

• This stream already exists in the program and assigns work to the stream

• The stream must be of type hipStream_t. Note, it is an error to pass the address of a hipStream_t object

PARAMETERS

Input

• info execution info handle
• stream underlying compute stream

Improved GEMM Performance

Currently, rocblas_gemm_ext2() supports matrix multiplication D <= alpha * A * B + beta * C, where the A, B, C, and D matrices are single-precision float, column-major, and non-transposed, except that the row stride of C may equal 0. This means the first row of C is broadcast M times in C:

If an optimized kernel solution for a particular problem is not available, a slow fallback algorithm is used, and the first time a fallback algorithm is used, the following message is printed to standard error:

*“Warning: Using slow on-host algorithm, because it is not implemented in Tensile yet.”

NOTE: ROCBLAS_LAYER controls the logging of the calls. It is recommended to use logging with the rocblas_gemm_ext2() feature, to identify the precise parameters which are passed to it.

• Setting the ROCBLAS_LAYER environment variable to 2 will print the problem parameters as they are being executed.
• Setting the ROCBLAS_LAYER environment variable to 4 will collect all of the sizes, and print them out at the end of program execution.

For more logging information, refer to https://rocblas.readthedocs.io/en/latest/logging.html.

New Matrix Pruning Functions

In this release, the following new Matrix Pruning functions are introduced.

rocSOLVER General Matrix Singular Value Decomposition API

The rocSOLVER General Matrix Singular Value Decomposition (GESVD) API is now available in the AMD ROCm v3.9 release.

GESVD computes the Singular Values and, optionally, the Singular Vectors of a general m-by-n matrix A (Singular Value Decomposition).

The SVD of matrix A is given by:

A = U * S * V'

For more information, refer to

https://rocsolver.readthedocs.io/en/latest/userguide_api.html

ROCm AOMP ENHANCEMENTS

AOMP v11.9-0

The source code base for this release is the upstream LLVM 11 monorepo release/11.x sources as of August 18, 2020, with the hash value

1e6907f09030b636054b1c7b01de36f281a61fa2

The llvm-project branch used to build this release is aomp11. In addition to completing the source tarball, the artifacts of this release include the file llvm-project.patch. This file shows the delta from the llvm-project upstream release/11.x. The size of this patch XXXX lines in XXX files. These changes include support for flang driver, OMPD support, and the hsa libomptarget plugin. The goal is to reduce this with continued upstreaming activity.

The changes for this release of AOMP are:

• Fix compiler warnings for build_project.sh and build_openmp.sh.

• Fix: [flang] The AOMP 11.7-1 Fortran compiler claims to support the -isystem flag, but ignores it.

• Fix: [flang] producing internal compiler error when a character is used with KIND.

• Fix: [flang] openmp map clause on complex allocatable expressions !$omp target data map( chunk%tiles(1)%field%density0).

• DeviceRTL memory footprint has been reduced from ~2.3GB to ~770MB for AMDGCN target.

• Workaround for red_bug_51 failing on gfx908.

• Switch to python3 for ompd and rocgdb.

• Now require cmake 3.13.4 to compile from source.

• Fix aompcc to accept file type cxx.

AOMP v11.08-0

The source code base for this release is the upstream LLVM 11 monorepo release/11.x sources as of August 18, 2020 with the hash value

aabff0f7d564b22600b33731e0d78d2e70d060b4

The amd-llvm-project branch used to build this release is amd-stg-openmp. In addition to complete source tarball, the artifacts of this release includes the file llvm-project.patch. This file shows the delta from the llvm-project upstream release/11.x which is currently at 32715 lines in 240 files. These changes include support for flang driver, OMPD support and the hsa libomptarget plugin. Our goal is to reduce this with continued upstreaming activity.

These are the major changes for this release of AOMP:

• Switch to the LLVM 11.x stable code base.

• OMPD updates for flang.

• To support debugging OpenMP, selected OpenMP runtime sources are included in lib-debug/src/openmp. The ROCgdb debugger will find these automatically.

• Threadsafe hsa plugin for libomptarget.

• Updates to support device libraries.

• Openmpi configure issue with real16 resolved.

• DeviceRTL memory use is now independent of number of openmp binaries.

• Startup latency on first kernel launch reduced by order of magnitude.

AOMP v11.07-1

The source code base for this release is the upstream LLVM 11 monorepo development sources as July 10, 2020 with hash valued 979c5023d3f0656cf51bd645936f52acd62b0333 The amd-llvm-project branch used to build this release is amd-stg-openmp. In addition to complete source tarball, the artifacts of this release includes the file llvm-project.patch. This file shows the delta from the llvm-project upstream trunk which is currently at 34121 lines in 277 files. Our goal is to reduce this with continued upstreaming activity.

• Inclusion of OMPD support which is not yet upstream

• Build of ROCgdb

• Host runtime optimisation. GPU image information is now mostly read on the host instead of from the GPU.

• Fixed the source build scripts so that building from the source tarball does not fail because of missing test directories. This fixes issue #116.

Fixed Defects

The following defects are fixed in this release:

• Random Soft Hang Observed When Running ResNet-Based Models

• (AOMP) ‘Undefined Hidden Symbol’ Linker Error Causes Compilation Failure in HIP

• MIGraphx -> test_gpu_ops_test FAILED

• Unable to install RDC on CentOS/RHEL 7.8/8.2 & SLES

Known Issues

The following are the known issues in this release.

(AOMP) HIP EXAMPLE DEVICE_LIB FAILS TO COMPILE

The HIP example device_lib fails to compile and displays the following error:

*lld: error: undefined hidden symbol: inc_arrayval

The recommended workaround is to use /opt/rocm/hip/bin/hipcc to compile HIP applications.

HIPFORT INSTALLATION FAILURE

Hipfort fails to install during the ROCm installation.

As a workaround, you may force install hipfort using the following instructions:

Ubuntu

sudo apt-get -o Dpkg::Options::="--force-overwrite" install hipfort

SLES

Zypper gives you an option to continue with the overwrite during the installation.

CentOS

Download hipfort to a temporary location and force install with rpm:

yum install --downloadonly --downloaddir=/tmp/hipfort hipfort
rpm -i --replacefiles hipfort<package-version>

MEMORY FAULT ACCESS ERROR DURING MEMORY TEST OF ROCM VALIDATION SUITE

When the ROCm Validation Suite (RVS) is installed using the prebuilt Debian/rpm package and run for the first time, the memory module displays the following error message,

“Memory access fault by GPU node- (Agent handle: 0xa55170) on address 0x7fc268c00000. Reason: Page not present or supervisor privilege. Aborted (core dumped)”

As a workaround, run the test again. Subsequent runs appear to fix the error.

NOTE: The error may appear after a system reboot. Run the test again to fix the issue.

Note, reinstallation of ROCm Validation Suite is not required.

Deprecations

This section describes deprecations and removals in AMD ROCm.

WARNING: COMPILER-GENERATED CODE OBJECT VERSION 2 DEPRECATION

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.

Deploying ROCm

AMD hosts both Debian and RPM repositories for the ROCm v3.9.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, "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.

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:

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