AMD ROCm Release Notes v3.5.1¶
June, 2020
AMD ROCm released a maintenance patch release v3.5.1. For more information, see
https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_Release_Notes_v3.5.1.pdf
Known Issue with AMD ROCm v3.5.1 Installation¶
Multiple Release Installations of AMD ROCm on a Server Fail
The Side-by-Side install feature does not behave as expected, and multiple release installations of AMD ROCm on a server fail. Attempts to install AMD ROCm v3.5.0 and AMD ROCm v3.5.1 side-by-side can result in breaking the existing ROCm v3.5.0 installation.
This known issue is currently under investigation.
AMD ROCm Release Notes v3.5.0¶
This page describes the features, fixed issues, and information about downloading and installing the ROCm software. It also covers known issues and deprecated features in the ROCm v3.5.0 release.
Supported Operating Systems and Documentation Updates¶
Supported Operating Systems¶
The AMD ROCm v3.5.x platform is designed to support the following operating systems:
Ubuntu 16.04.6(Kernel 4.15) and 18.04.4(Kernel 5.3)
CentOS 7.7 (Kernel 3.10-1062) and RHEL 7.8(Kernel 3.10.0-1127)(Using devtoolset-7 runtime support)
SLES 15 SP1
CentOS and RHEL 8.1(Kernel 4.18.0-147)
Documentation Updates¶
HIP-Clang Compiler¶
AMD ROCDebugger (ROCgdb)¶
AMD ROCm Systems Management Interface¶
AMD ROCm Deep Learning¶
AMD ROCm Glossary of Terms¶
General AMD ROCm Documentation Links¶
Access the following links for more information on:
For AMD ROCm documentation, see
For installation instructions on supported platforms, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
For AMD ROCm binary structure, see
For AMD ROCm Release History, see
What’s New in This Release¶
Upgrading to This Release¶
You must perform a fresh and a clean AMD ROCm install to successfully upgrade from v3.3 to v3.5. The following changes apply in this release:
HCC is deprecated and replaced with the HIP-Clang compiler
HIP-HCC runtime is changed to Radeon Open Compute Common Language Runtime (HIP-ROCClr)
In the v3.5 release, the firmware is separated from the kernel package. The difference is as follows:
v3.5 release has two separate rock-dkms and rock-dkms-firmware packages
v3.3 release had the firmware as part of the rock-dkms package
rocProf Command Line Tool Python Requirement¶
SQLite3 is a required Python module for the rocprof command-line tool. You can install the SQLite3 Python module using the pip utility and set env var ROCP_PYTHON_VERSION to the Python version, which includes the SQLite3 module.
Heterogeneous-Compute Interface for Portability¶
In this release, the Heterogeneous Compute Compiler (HCC) compiler is deprecated and the HIP-Clang compiler is introduced for compiling Heterogeneous-Compute Interface for Portability (HIP) programs.
NOTE: The HCC environment variables will be gradually deprecated in subsequent releases.
The majority of the codebase for the HIP-Clang compiler has been upstreamed to the Clang trunk. The HIP-Clang implementation has undergone a strict code review by the LLVM/Clang community and comprehensive tests consisting of LLVM/Clang build bots. These reviews and tests resulted in higher productivity, code quality, and lower cost of maintenance.
For most HIP applications, the transition from HCC to HIP-Clang is transparent and efficient as the HIPCC and HIP cmake files automatically choose compilation options for HIP-Clang and hide the difference between the HCC and HIP-Clang code. However, minor changes may be required as HIP-Clang has a stricter syntax and semantic checks compared to HCC.
NOTE: Native HCC language features are no longer supported.
Radeon Open Compute Common Language Runtime¶
In this release, the HIP runtime API is implemented on top of Radeon Open Compute Common Language Runtime (ROCclr). ROCclr is an abstraction layer that provides the ability to interact with different runtime backends such as ROCr.
OpenCL Runtime¶
The following OpenCL runtime changes are made in this release:
AMD ROCm OpenCL Runtime extends support to OpenCL2.2
The developer branch is changed from master to master-next
AMD ROCm GNU Debugger - ROCgdb¶
The AMD ROCm GNU Debugger (ROCgdb) is the AMD ROCm source-level debugger for Linux based on the GNU Debugger (GDB). It enables heterogeneous debugging on the AMD ROCm platform of an x86-based host architecture along with AMD GPU architectures and supported by the AMD Debugger API Library (ROCdbgapi).
The AMD ROCm Debugger is installed by the rocm-gdb package. The rocm-gdb package is part of the rocm-dev meta-package, which is in the rocm-dkms package.
The current AMD ROCm Debugger (ROCgdb) is an initial prototype that focuses on source line debugging. Note, symbolic variable debugging capabilities are not currently supported.
You can use the standard GDB commands for both CPU and GPU code debugging. For more information about ROCgdb, refer to the ROCgdb User Guide, which is installed at:
/opt/rocm/share/info/gdb.info as a texinfo file
/opt/rocm/share/doc/gdb/gdb.pdf as a PDF file
The AMD ROCm Debugger User Guide is available as a PDF at:
https://github.com/RadeonOpenCompute/ROCm/blob/master/gdb.pdf
For more information about GNU Debugger (GDB), refer to the GNU Debugger (GDB) web site at: http://www.gnu.org/software/gdb
AMD ROCm Debugger API Library¶
The AMD ROCm Debugger API Library (ROCdbgapi) implements an AMD GPU debugger application programming interface (API) that provides the support necessary for a client of the library to control the execution and inspect the state of AMD GPU devices.
The following AMD GPU architectures are supported: * Vega 10 * Vega 7nm
The AMD ROCm Debugger API Library is installed by the rocm-dbgapi package. The rocm-gdb package is part of the rocm-dev meta-package, which is in the rocm-dkms package. The AMD ROCm Debugger API Specification is available as a PDF at:
https://github.com/RadeonOpenCompute/ROCm/blob/master/amd-dbgapi.pdf
rocProfiler Dispatch Callbacks Start Stop API¶
In this release, a new rocprofiler start/stop API is added to enable/disable GPU kernel HSA dispatch callbacks. The callback can be registered with the ‘rocprofiler_set_hsa_callbacks’ API. The API helps you eliminate some profiling performance impact by invoking the profiler only for kernel dispatches of interest. This optimization will result in significant performance gains.
The API provides the following functions: * hsa_status_t rocprofiler_start_queue_callbacks(); is used to start profiling * hsa_status_t rocprofiler_stop_queue_callbacks(); is used to stop profiling.
For more information on kernel dispatches, see the HSA Platform System Architecture Specification guide at http://www.hsafoundation.com/standards/.
ROCm Communications Collective Library¶
The ROCm Communications Collective Library (RCCL) consists of the following enhancements: * Re-enable target 0x803 * Build time improvements for the HIP-Clang compiler
NVIDIA Communications Collective Library Version Compatibility
AMD RCCL is now compatible with NVIDIA Communications Collective Library (NCCL) v2.6.4 and provides the following features: * Network interface improvements with API v3 * Network topology detection * Improved CPU type detection * Infiniband adaptive routing support
MIOpen - Optional Kernel Package Installation¶
MIOpen provides an optional pre-compiled kernel package to reduce startup latency.
NOTE: The installation of this package is optional. MIOpen will continue to function as expected even if you choose to not install the pre-compiled kernel package. This is because MIOpen compiles the kernels on the target machine once the kernel is run. However, the compilation step may significantly increase the startup time for different operations.
To install the kernel package for your GPU architecture, use the following command:
apt-get install miopen-kernels–
is the GPU architecture. For example, gfx900, gfx906
is the number of CUs available in the GPU. For example, 56 or 64
New SMI Event Interface and Library¶
An SMI event interface is added to the kernel and ROCm SMI lib for system administrators to get notified when specific events occur. On the kernel side, AMDKFD_IOC_SMI_EVENTS input/output control is enhanced to allow notifications propagation to user mode through the event channel.
On the ROCm SMI lib side, APIs are added to set an event mask and receive event notifications with a timeout option. Further, ROCm SMI API details can be found in the PDF generated by Doxygen from source or by referring to the rocm_smi.h header file (see the rsmi_event_notification_* functions).
For the more details about ROCm SMI API, see
https://github.com/RadeonOpenCompute/ROCm/blob/master/ROCm_SMI_Manual.pdf
API for CPU Affinity¶
A new API is introduced for aiding applications to select the appropriate memory node for a given accelerator(GPU).
The API for CPU affinity has the following signature:
rsmi_status_t rsmi_topo_numa_affinity_get(uint32_t dv_ind, uint32_tnuma_node);*
This API takes as input, device index (dv_ind), and returns the NUMA node (CPU affinity), stored at the location pointed by numa_node pointer, associated with the device.
Non-Uniform Memory Access (NUMA) is a computer memory design used in multiprocessing, where the memory access time depends on the memory location relative to the processor.
Radeon Performance Primitives Library¶
The new Radeon Performance Primitives (RPP) library is a comprehensive high-performance computer vision library for AMD (CPU and GPU) with the HIP and OpenCL backend. The target operating system is Linux.
For more information about prerequisites and library functions, see
https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/docs
Fixed Issues¶
Device printf Support for HIP-Clang¶
HIP now supports the use of printf in the device code. The parameters and return value for the device-side printf follow the POSIX.1 standard, with the exception that the “%n†specifier is not supported. A call to printf blocks the calling wavefront until the operation is completely processed by the host.
No host-side runtime calls by the application are needed to cause the output to appear. There is also no limit on the number of device-side calls to printf or the amount of data that is printed.
For more details, refer the HIP Programming Guide at: https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-GUIDE.html#hip-guide
Assertions in HIP Device Code¶
Previously, a failing assertion caused early termination of kernels and the application to exit with a line number, file, and failing condition printed to the screen. This issue is now fixed and the assert() and abort() functions are implemented for HIP device code.
NOTE: There may be a performance impact in the use of device assertions in its current form.
You may choose to disable the assertion in the production code. For example, to disable an assertion of:
assert(foo != 0);
you may comment it out as:
//assert(foo != 0);
NOTE: Assertions are currently enabled by default.
Known Issues¶
The following are the known issues in the v3.5 release.
HIPify-Clang Installation Failure on CentOS/RHEL¶
HIPify-Clang fails to install on CentOS/RHEL with the following error:
file from install of hipify-clang conflicts with file from package hip-base
Workaround: This is a known issue and the following workaround is recommended for a successful HIPify-Clang installation on CentOS/RHEL:
Download HIPify-Clang RPM. For example, hipify-clang-11.0.0.x86_64.rpm
Perform a force install using the following command:
sudo rpm -ivh --force hipify-clang-11.0.0.x86_64.rpm
Failure to Process Breakpoint before Queue Destroy Results in ROCm Debugger Error¶
When ROCgdb is in non-stop mode with an application that rapidly creates and destroys queues, a breakpoint may be reported that is not processed by the debugger before the queue is deleted. In some cases, this can result in the following error that prevents further debugging:
[amd-dbgapi]: fatal error: kfd_queue_id 2 should have been reported as a NEW_QUEUE before next_pending_event failed (rc=-2)
There are no known workarounds at this time.
Failure to Process Breakpoint before Queue Destroy Results in ROCm Debugger API Error¶
When the ROCdbgapi library is used with an application that rapidly creates and destroys queues, a breakpoint may be reported that is not processed by the client before the queue is deleted. In some cases, this can result in a fatal error and the following error log message is produced:
[amd-dbgapi]: fatal error: kfd_queue_id 2 should have been reported as a NEW_QUEUE before next_pending_event failed (rc=-2)
There are no known workarounds at this time.
rocThrust and hipCUB Unit Test Failures¶
The following unit test failures have been observed due to known issues in the ROCclr runtime.
rocThrust
sort
sort_by_key
hipCUB
BlockDiscontinuity
BlockExchange
BlockHistogram
BlockRadixSort
BlockReduce
BlockScan
There are no known workarounds in the current release.
Multiple GPU Configuration Freezes with Imagenet Training and tf_cnn_benchmark on TensorFlow¶
A random freeze has been observed with Imagenet training and tf_cnn_benchmark on TensorFlow when multiple GPU configurations are involved.
Note: There is no freeze observed with single GPUs.
There are no known workarounds at this time.
Issue with Running AMD ROCm v3.3 User Mode with AMD ROCm v3.5 DKMS Kernel Module¶
Running AMD ROCm v3.3 in the user mode with the AMD ROCm v3.5 DKMS kernel module will cause the following features to be broken:
IPC import/export, cross memory copy (used by UCX and MPI)
Experimental GDB support
Resolution: Install ROCm v3.5 Thunk (Hsakmt) when using ROCm 3.5 Kernel Fusion Driver (KFD).
Deprecations¶
Heterogeneous Compute Compiler¶
In this release, the Heterogeneous Compute Compiler (HCC) compiler is deprecated and the HIP-Clang compiler is introduced for compiling Heterogeneous-Compute Interface for Portability (HIP) programs.
For more information, see HIP documentation at: https://rocmdocs.amd.com/en/latest/Programming_Guides/Programming-Guides.html
Deploying ROCm¶
AMD hosts both Debian and RPM repositories for the ROCm v3.5.x packages.
For more information on ROCM installation on all platforms, see
https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
Features and enhancements introduced in previous versions of ROCm can be found in Current-Release-Notes.
AMD ROCm Version History¶
This file contains archived version history information for the ROCm project.
Release Notes: https://github.com/RadeonOpenCompute/ROCm/tree/roc-3.3.0
Multi-Version Installation Users can install and access multiple versions of the ROCm toolkit simultaneously. Previously, users could install only a single version of the ROCm toolkit.
GPU Process Information A new functionality to display process information for GPUs is available in this release. For example, you can view the process details to determine if the GPU(s) must be reset.
Support for 3D Pooling Layers AMD ROCm is enhanced to include support for 3D pooling layers. The implementation of 3D pooling layers now allows users to run 3D convolutional networks, such as ResNext3D, on AMD Radeon Instinct GPUs.
ONNX Enhancements Open Neural Network eXchange (ONNX) is a widely-used neural net exchange format. The AMD model compiler & optimizer support the pre-trained models in ONNX, NNEF, & Caffe formats. Currently, ONNX versions 1.3 and below are supported.
This release was not productized.
‘Release Notes: https://github.com/RadeonOpenCompute/ROCm/tree/roc-3.1.0
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.
Release Notes: https://github.com/RadeonOpenCompute/ROCm/tree/roc-3.0.0
Support for CentOS RHEL v7.7
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
Initial distribution of AOMP 0.7-5 in ROCm v3.0
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.
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.
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.
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.
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.
Added support for Ubuntu 18.04.3
Ubuntu 18.04.3 is now supported in ROCm 2.9.
Support for NCCL2.4.8 API
Implements ncclCommAbort() and ncclCommGetAsyncError() to match the NCCL 2.4.x API
This release is a hotfix for ROCm release 2.7.
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:
/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
To upgrade, please remove 2.7 completely as specified for ubuntu or for centos/rhel, and install 2.7.2 as per instructions install instructions
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: sudo apt install roctracer-dev CentOS/RHEL 7.6: 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.
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
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™ 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.
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™ Link enablement
ROCm 2.4 adds support to connect two Radeon Instinct MI60 or Radeon Instinct MI50 boards via AMD Infinity Fabric™ Link GPU interconnect technology.
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 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
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
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
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)
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
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
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
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
ROCm 1.8.3 is a minor update meant to fix compatibility issues on Ubuntu releases running kernel 4.15.0-33
DKMS driver installation
Debian packages are provided for DKMS on Ubuntu
RPM packages are provided for CentOS/RHEL 7.4 and 7.5
See the ROCT-Thunk-Interface and ROCK-Kernel-Driver 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
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 and ROCK-Kernel-Driver for additional documentation on driver setup
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
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