This file contains archived version history information for the ROCm project
- New features and enhancements in ROCm v2.10
- New features and enhancements in ROCm 2.9
- New features and enhancements in ROCm 2.8
- New features and enhancements in ROCm 2.7.2
- New features and enhancements in ROCm 2.7
- New features and enhancements in ROCm 2.6
- New features and enhancements in ROCm 2.5
- New features and enhancements in ROCm 2.4
- New features and enhancements in ROCm 2.3
- New features and enhancements in ROCm 2.2
- New features and enhancements in ROCm 2.1
- New features and enhancements in ROCm 2.0
- New features and enhancements in ROCm 1.9.2
- New features and enhancements in ROCm 1.9.2
- New features and enhancements in ROCm 1.9.1
- New features and enhancements in ROCm 1.9.0
- New features as of ROCm 1.8.3
- New features as of ROCm 1.8
- New Features as of ROCm 1.7
- New Features as of ROCm 1.5
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.
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 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.
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.
MIGraphX 0.4 introduces support for fp16 and int8 quantization. For additional details, as well as other new MIGraphX features, see MIGraphX documentation.
csrgemm enables the user to perform matrix-matrix multiplication with two sparse matrices in CSR format.
ROCm 2.9 adds support for Singularity container version 2.5.2.
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.
Ubuntu 18.04.3 is now supported in ROCm 2.9.
Implements ncclCommAbort() and ncclCommGetAsyncError() to match the NCCL 2.4.x API
This release is a hotfix for ROCm release 2.7.
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
To use rocprofiler features, the following steps need to be completed before using rocprofiler:
sudo apt install roctracer-dev
sudo yum install roctracer-dev
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.
- 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
Added support for RAS on Radeon Instinct MI50, including:
- Memory error detection
- Memory error detection counter
Added ROCm-SMI CLI and LIB support for FW version, compute running processes, utilization rates, utilization counter, link error counter, and unique ID.
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
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 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
- 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/
Added mixed precision bfloat16/IEEE f32 to gemm_ex. The input and output matrices are bfloat16. All arithmetic is in IEEE f32.
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.
- mGPU & Vendor check
- Fix clock printout if DPM is disabled
- Fix finding marketing info on CentOS
- Clarify some error messages
- Documentation updates
- Improvements to *name_get functions
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.
- Added: Debian package with FFT test, benchmark, and sample programs
- Improved: hipFFT interfaces
- Improved: rocFFT CPU reference code, plan generation code and logging code
Support for UCX version 1.6 has been added.
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
CLI support for querying the memory size, driver version, and firmware version has been added to ROCm-smi.
Multi-GPU support is enabled in PyTorch using Dataparallel path for versions of PyTorch built using the 06c8aa7a3bbd91cda2fd6255ec82aad21fa1c0d5 commit or later.
This release includes performance optimizations for csrsv routines in the rocSparse library.
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.
HIP API has been enhanced to allow independent kernels to run in parallel on the same stream.
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.
ROCm 2.4 includes the enhanced compilation toolchain and a set of bug fixes to support TensorFlow 2.0 features natively
ROCm 2.4 adds support to connect two Radeon Instinct MI60 or Radeon Instinct MI50 boards via AMD Infinity Fabric™ Link GPU interconnect technology.
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
ONNX parser changes to adjust to new file formats
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
- 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
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.
Introduces support and performance optimizations for Int8 GEMM, implements TRSV support, and includes improvements and optimizations with Tensile.
Functional implementation of BLAS L1/L2/L3 functions
Improvements and optimizations with tensile
Support for int8
Cache usage optimizations for csrsv (sparse triangular solve), coomv (SpMV in COO format) and ellmv (SpMV in ELL format) are available.
Improved DGEMM performance for reduced matrix sizes (k=384, k=256)
Added support for multi-GPU training
Supports HSA API tracing and HSA asynchronous GPU activity including kernels execution and memory copy
Added support to show real-time PCIe bandwidth usage via the -b/--showbw flag
Improved DGEMM performance for large square and reduced matrix sizes (k=384, k=256)
- A comprehensive computer vision and machine intelligence libraries, utilities and applications bundled into a single toolkit.
- rocSPARSE & hipSPARSE
- rocBLAS with improved DGEMM efficiency on Vega 7nm
- This release contains general bug fixes and an updated performance database
- Group convolutions backwards weights performance has been improved
- RNNs now support fp16
- TensorFlow v1.12 is enabled with fp16 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
- Support for Vega 7nm
- 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.
- 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
- 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
- Support ROCnRDMA based on Mellanox InfiniBand
- Improved link time optimization
- General bug fixes and implemented versioning APIs
- Support ROCnRDMA based on Mellanox InfiniBand
- Improved link time optimization
- General bug fixes and implemented versioning APIs
- 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
- Enables developer preview support for Vega 7nm
- Adds support for the ROCm SMI (System Management Interface) library, which provides monitoring and management capabilities for AMD GPUs.
- 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
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
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
- Binary package support for Ubuntu 18.04
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
- 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 and ROCK-Kernel-Driver for additional documentation on driver setup
- 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
- UCX support for OpenMPI
- ROCm RDMA
- 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
- 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.