1. What's New

Welcome to the 22.11 version 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. The 22.11 release of the HPC SDK includes new features, as well as important functionality and performance improvements.

  • The HPC SDK now provides preview implementations of several new proposed features of ISO Standard C++ for parallel and high-performance computing.
    • ISO Standard C++ proposal p2300 "std::execution": The stdexec library introduces a performance-portable way of writing asynchronous pipelines of work in standard C++, with fine-grained control of where and how the work executes. This preview release supports execution on the CPU, and on single- and multi-GPU systems.
    • ISO Standard C++ proposal p0009 "mdspan": This feature provides a multidimensional array view, mdspan, along with classes, class templates, and constants for describing and creating multidimensional array views. The mdspan class template can represent arbitrary mixes of compile-time or run-time extents.
    • ISO Standard C++ proposal p1673 "A free function linear algebra interface based on the BLAS": These proposed C++ standard algorithms make up a C++ Standard Library dense linear algebra interface based on the dense Basic Linear Algebra Subroutines (BLAS), which correspond to a subset of the BLAS Standard.
  • The HPC SDK is now supported on Redhat Enterprise Linux version 8.6 for x86-64, Arm Server, and POWER architectures.

2. Release Component Versions

The NVIDIA HPC SDK 22.11 release contains the following versions of each component:

Table 1. HPC SDK Release Components
  Linux_x86_64 Linux_ppc64le Linux_aarch64
  CUDA 10.2 CUDA 11.0 CUDA 11.8 CUDA 10.2 CUDA 11.0 CUDA 11.8 CUDA 10.2 CUDA 11.0 CUDA 11.8
nvc++ 22.11 22.11 22.11
nvc 22.11 22.11 22.11
nvfortran 22.11 22.11 22.11
nvcc 10.2.89 11.0.221 11.8.89 10.2.89 11.0.221 11.8.89 N/A 11.0.221 11.8.89
NCCL 2.13.4 2.13.4 2.13.4 2.13.4 2.13.4 2.13.4 N/A 2.13.4 2.13.4
NVSHMEM 2.6.0 2.6.0 2.6.0 2.6.0 2.6.0 2.6.0 N/A N/A N/A
cuBLAS 10.2.2.89 11.2.0.252 11.11.3.6 10.2.2.89 11.2.0.252 11.11.3.6 N/A 11.2.0.252 11.11.3.6
cuFFT 10.1.2.89 10.2.1.245 10.9.0.58 10.1.2.89 10.2.1.245 10.9.0.58 N/A 10.2.1.245 10.9.0.58
cuFFTMp N/A N/A 10.8.1 N/A N/A 10.8.1 N/A N/A N/A
cuRAND 10.1.2.89 10.2.1.245 10.3.0.86 10.1.2.89 10.2.1.245 10.3.0.86 N/A 10.2.1.245 10.3.0.86
cuSOLVER 10.3.0.89 10.6.0.245 11.4.1.48 10.3.0.89 10.6.0.245 11.4.1.48 N/A 10.6.0.245 11.4.1.48
cuSOLVERMp N/A N/A 0.2.1 N/A N/A N/A N/A N/A N/A
cuSPARSE 10.3.1.89 11.1.1.245 11.7.5.86 10.3.1.89 11.1.1.245 11.7.5.86 N/A 11.1.1.245 11.7.5.86
cuTENSOR 1.6.1 1.6.1 1.6.1 1.6.1 1.6.1 1.6.1 N/A 1.6.1 1.6.1
Nsight Compute 2022.3.0 2022.3.0 2022.3.0
Nsight Systems 2022.4.1.21 2022.4.1.21 2022.4.1.21
OpenMPI 3.1.5 3.1.5 3.1.5
HPC-X N/A 2.12 2.12 N/A N/A N/A N/A 2.12 2.12
UCX N/A 1.14.0 1.14.0 N/A N/A N/A N/A 1.14.0 1.14.0
OpenBLAS 0.3.20 0.3.20 0.3.20
Scalapack 2.2.0 2.2.0 2.2.0
Thrust 1.9.7 1.9.9 1.15.1 1.9.7 1.9.9 1.15.1 N/A 1.9.10 1.15.1
CUB N/A 1.9.9 1.15.1 N/A 1.9.9 1.15.1 N/A 1.9.9 1.15.1
libcu++ N/A 1.0.0 1.8.1 N/A 1.0.0 1.8.1 N/A 1.0.0 1.8.1

3. Supported Platforms

3.1. Platform Requirements for the HPC SDK

Table 2. HPC SDK Platform Requirements
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, 7.9
CentOS 8.0, 8.1, 8.2
Fedora 29, 30, 31, 32, 33, 34
OpenSUSE Leap 15.0, 15.1, 15.2
RHEL 7.0, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, 7.9
RHEL 8.0, 8.1, 8.4, 8.5, 8.6
SLES 12SP4, 12SP5, 15, 15SP1, 15SP2, 15SP3
Ubuntu 18.04, 20.04, 22.04
Rocky Linux 8.0
              

C99: 4.8
C11: 4.9
C++03: 4.8
C++11: 4.9
C++14: 5.1
C++17: 7.1
C++20: 10.1
              

440.33
ppc64le

RHEL 7.3, 7.4, 7.5, 7.6, 7.7, 8.0, 8.1, 8.3, 8.4
RHEL Pegas 7.5, 7.6
Ubuntu 18.04
              

C99: 4.8
C11: 4.9
C++03: 4.8
C++11: 4.9
C++14: 5.1
C++17: 7.1
C++20: 10.1
              

440.33
aarch64

CentOS 8.0, 8.1, 8.2, 8.3, 8.4
RHEL 8.1, 8.2, 8.6
Ubuntu 18.04, 20.04, 22.04
SLES 15SP3
Amazon Linux 2
              

C99: 4.8
C11: 4.9
C++03: 4.8
C++11: 4.9
C++14: 5.1
C++17: 7.1
C++20: 10.1
              

450.36

Programs generated by the HPC Compilers for x86_64 processors require a minimum of AVX instructions, which includes Sandy Bridge and newer CPUs from Intel, as well as Bulldozer and newer CPUs from AMD. POWER 8 and POWER 9 CPUs from the POWER architecture are supported. For the Arm architecture, the minimum required version is Arm v8.1.

The HPC Compilers are compatible with gcc and g++ and use the GCC C and C++ libraries; the minimum compatible versions of GCC are listed in Table 2. The minimum system requirements for CUDA and NVIDIA Math Library requiremetns are available in the NVIDIA CUDA Toolkit documentation.

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.

The NVIDIA HPC SDK 22.11 includes the following CUDA toolchain versions:
  • CUDA 10.2
  • CUDA 11.0
  • CUDA 11.8
The minimum required CUDA driver versions are listed in the table in Section 3.1.

4.  Known Limitations

  • Prior to using HPC-X, users should take care to source the hpcx-init.sh script: $ . /[install-path]/Linux_x86_64/dev/comm_libs/hpcx/hpcx-2.11/hpcx-init.sh Then, run the hpcx_load function defined by this script: $ hpcx_load These actions will set important environment variables that are needed when running HPC-X. Also, if you see the following warning from HPC-X while running an MPI job: WARNING: Open MPI tried to bind a process but failed. This is a warning only; your job will continue, though performance may be degraded. This is a known issue, and may be worked around as follows: export OMPI_MCA_hwloc_base_binding_policy=""
  • Derived type objects with zero-size derived type allocatable components that are used in sourced allocation or allocatable assignment may result in a runtime segmentation violation.
  • 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 and Changes

  • Corresponding with the release of new upcoming CUDA Toolkit versions, all three bundled CUDA versions included in the HPC SDK "multi" packages will be updated.
  • Support for CUDA Fortran textures has been deprecated and will be removed in a future release.
  • cudaDeviceSynchronize() in CUDA Fortran has been deprecated and will be removed in a future release.
  • Starting with the 21.11 version of the NVIDIA HPC SDK, the HPC-X package is no longer shipped as part of the packages made available for the POWER architecture.
  • Starting with the 21.5 version of the NVIDIA HPC SDK, the -cuda option for NVC++ and NVFORTRAN no longer automatically links the NVIDIA GPU math libraries. Please refer to the -cudalib option.
  • HPC Compiler support for the Kepler architecture of NVIDIA GPUs was deprecated starting with the 21.3 version of the NVIDIA HPC SDK.
  • Support for the KNL architecture of multicore CPUs in the NVIDIA HPC SDK was removed in the HPC SDK version 21.3.

Notices

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