1. What's New
Welcome to the 21.3 release of the NVIDIA HPC SDK, a comprehensive suite of compilers and libraries enabling developers to program the entire HPC platform, from the GPU foundation to the CPU and out through the interconnect.
Key features that are new in the 21.3 release of the NVIDIA HPC SDK for Linux include:
- The HPC SDK now includes the HPC-X toolkit, a comprehensive software package that includes MPI, SHMEM/PGAS communications libraries and various acceleration packages.
- C++ Standard Language Parallelism is now supported on multicore CPUs via the -stdpar=multicore command line flag.
- The HPC SDK now includes 64-bit versions of the host-only OpenBLAS libraries, which have '_ilp64.*" suffixes on the filenames.
2. Release Component Versions
The NVIDIA HPC SDK 21.3 release contains the following versions of each component:
| Linux_x86_64 | Linux_ppc64le | Linux_aarch64 | |||||||
|---|---|---|---|---|---|---|---|---|---|
| CUDA 10.2 | CUDA 11.0 | CUDA 11.2 | CUDA 10.2 | CUDA 11.0 | CUDA 11.2 | CUDA 10.2 | CUDA 11.0 | CUDA 11.2 | |
| nvc++ | 21.3 | 21.3 | 21.3 | ||||||
| nvc | 21.3 | 21.3 | 21.3 | ||||||
| nvfortran | 21.3 | 21.3 | 21.3 | ||||||
| nvcc | 10.2.89 | 11.0.221 | 11.2.1.007 | 10.2.89 | 11.0.221 | 11.2.1.007 | N/A | 11.0.221 | 11.2.1.007 |
| NCCL | 2.8.3-1 | 2.8.3-1 | 2.8.3-1 | 2.8.3-1 | 2.8.3-1 | 2.8.3-1 | N/A | N/A | 2.8.3-1 |
| NVSHMEM | 1.1.3 | 1.1.3 | 1.1.3 | 1.1.3 | 1.1.3 | 1.1.3 | N/A | N/A | N/A |
| cuBLAS | 10.2.2.89 | 11.2.0.252 | 11.4.1.1026 | 10.2.2.89 | 11.2.0.252 | 11.4.1.1026 | N/A | 11.2.0.252 | 11.4.1.1026 |
| cuFFT | 10.1.2.89 | 10.2.1.245 | 10.4.0.135 | 10.1.2.89 | 10.2.1.245 | 10.4.0.135 | N/A | 10.2.1.245 | 10.4.0.135 |
| cuRAND | 10.1.2.89 | 10.2.1.245 | 10.2.3.135 | 10.1.2.89 | 10.2.1.245 | 10.2.3.135 | N/A | 10.2.1.245 | 10.2.3.135 |
| cuSOLVER | 10.3.0.89 | 10.6.0.245 | 11.1.0.135 | 10.3.0.89 | 10.6.0.245 | 11.1.0.135 | N/A | 10.6.0.245 | 11.1.0.135 |
| cuSPARSE | 10.3.1.89 | 11.1.1.245 | 11.4.0.135 | 10.3.1.89 | 11.1.1.245 | 11.4.0.135 | N/A | 11.1.1.245 | 11.4.0.135 |
| cuTENSOR | 1.2.1 | 1.2.1 | 1.2.2 | 1.2.1 | 1.2.1 | 1.2.2 | N/A | 1.2.1 | 1.2.2 |
| Nsight Compute | 2020.3.0.0-29307467 | 2020.3.0.0-29307467 | 2020.3.1.0-29471205 | ||||||
| Nsight Systems | 2020.5.1.85 | 2020.5.1.85 | 2021.1.1.66 | ||||||
| OpenMPI | 3.1.5 | 3.1.5 | 3.1.5 | ||||||
| HPC-X | N/A | 2.7.4 | 2.7.4 | N/A | 2.7.4 | 2.7.4 | N/A | 2.7.4 | 2.7.4 |
| UCX | N/A | 1.9.0 | 1.9.0 | N/A | 1.9.0 | 1.9.0 | N/A | 1.9.0 | 1.9.0 |
| OpenBLAS | 0.3.13 | 0.3.13 | 0.3.13 | ||||||
| Scalapack | 2.1.0 | 2.1.0 | 2.1.0 | ||||||
| Thrust | 1.9.7 | 1.9.9 | 1.10.0 | 1.9.7 | 1.9.9 | 1.10.0 | 1.9.7 | 1.9.10 | 1.10.0 |
| CUB | N/A | 1.9.9 | 1.10.0 | N/A | 1.9.9 | 1.10.0 | N/A | 1.9.9 | 1.10.0 |
| libcu++ | 1.0.0 | 2.0.0 | 2.0.0 | 1.0.0 | 2.0.0 | 2.0.0 | 1.0.0 | 2.0.0 | 2.0.0 |
3. Supported Platforms
3.1. Platform Requirements for the HPC SDK
| Architecture | Linux Distributions | Minimum gcc/glibc Toolchain | Minimum CUDA Driver |
|---|---|---|---|
| x86_64 |
CentOS 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8 |
C99: 4.8 |
440.33 |
| ppc64le |
RHEL 7.3, 7.4, 7.5, 7.6, 7.7, 8.0, 8.1 |
C99: 4.8 |
440.33 |
| aarch64 |
RHEL 8.1 |
C99: 4.8 |
450.36 |
3.2. Supported CUDA Toolchain Versions
The NVIDIA HPC SDK uses elements of the CUDA toolchain when building programs for execution with NVIDIA GPUs. Every HPC SDK installation package puts the required CUDA components into an installation directory called [install-prefix]/[arch]/[nvhpc-version]/cuda.
An NVIDIA CUDA GPU device driver must be installed on a system with a GPU before you can run a program compiled for the GPU on that system. The NVIDIA HPC SDK does not contain CUDA Drivers. You must download and install the appropriate CUDA Driver from NVIDIA , including the CUDA Compatibility Platform if that is required.
The nvaccelinfo tool prints the CUDA Driver version in its output. You can use it to find out which version of the CUDA Driver is installed on your system.
- CUDA 10.2
- CUDA 11.0
- CUDA 11.2
4. Known Limitations
- When invoking MPI executables directly from comm_libs/mpi/bin, the user must explicitly set the LD_LIBRARY_PATH environment variable to include the compilers/lib directory, or use the included modulefiles with the NVIDIA HPC SDK to access the MPI executables.
- When compiling for Skylake Core or Skylake Xeon processors, it is recommended that the target processor compiler option -tp skylake be specified. Specifying -tp skylake at link time is optional.
- The cuda-gdb debugger is included in this release. Currently, Fortran arrays with non-constant bounds are not handled correctly and querying values will yield incorrect results. Stepping through cuda-fortran and OpenACC kernels is partially supported, but incorrect line numbers are displayed. For additional general limitations with cuda-gdb, please refer to its documentation.
- When using -stdpar to accelerate C++ parallel algorithms, the algorithm calls cannot include virtual function calls or function calls through a function pointer, cannot use C++ exceptions, can only dereference pointers that point to the heap, and must use random access iterators (raw pointers as iterators work best).
5. Deprecations
- The 21.3 release of the NVIDIA HPC SDK supports NVIDIA GPUs with compute capability 3.5 (cc35) and newer.
- Support for the KNL architecture of multicore CPUs in the NVIDIA HPC SDK is deprecated in the 21.3 release.
- Starting with the 21.3 release of the NVIDIA HPC SDK, the -cuda option for NVC++ and NVFORTRAN will no longer automatically link the NVIDIA GPU math libraries.
- Support for the Kepler architecture of NVIDIA GPUs is deprecated starting with the 21.3 release of the NVIDIA HPC SDK.
Notices
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