1. What's New

Welcome to the 22.7 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 NVIDIA HPC Compilers add support for Arm’s Scalable Vector Extension (SVE) in the 22.7 release. The compilers generate code for a specific vector bit width at compile time to generate highly-optimized vector length specific (VLS) code for the target CPU core. Note that VLS code is not portable between systems with different vector lengths. Portable vector length agnostic (VLA) code generation, where the generated code adapts to the vector length of the host architecture, is not available.

The HPC SDK compilers support several different -⁠tp architecture flags for arm:
  • -⁠tp neoverse-n1 for Arm Neoverse N1 architecture (NEON)
  • -⁠tp neoverse-v1 for Arm Neoverse V1 architecture (SVE x 256)
The default setting for -⁠tp is to match the system on which the compiler is being used.

Amazon EC2 C7g instances, powered by the latest generation AWS Graviton3 processors is now supported by the HPC SDK 22.7. Applications compiled with the NVIDIA HPC Compilers on AWS C7g instances featuring the AWS Graviton3 processors will automatically take advantage of the CPU’s 2x256-bit SVE SIMD units.

With the 22.7 release, the default compiler settings for how denormal values are handled at runtime have been changed to be more consistent.
  22.5 defaults 22.7 defaults
Intel -Mdaz -Mdaz
-Mnoflushz -Mflushz
AMD -Mnodaz -Mdaz
-Mnoflushz -Mflushz
Arm v8 -Mnodaz -Mdaz
-Mnoflushz -Mflushz
For further information, see the HPC Compilers user manual.

Rocky Linux is a supported version of Linux starting with the 22.7 release of the HPC SDK. Please refer to the Supported Platforms section for more details.

The NVCOMPLER_NOSWITCHERROR is an environment variable that can be set to ignore unknown command line switches. This is the same as -⁠noswitcherror.

The HPC Compilers now produce debug information for Fortran arrays with variable bounds that can be used with debuggers such as GDB.

The OpenMP Tools (OMPT) interface is now enabled by the HPC Compilers for use with the NVIDIA NSight developer tools.

The default value for -⁠noimplicitsections has changed to correspond to the behavior described by the OpenACC specification. Please refer to the HPC Compilers documentation for more details.

The random number sequence generated by nvfortran version 22.7 differs from previous versions.

2. Release Component Versions

The NVIDIA HPC SDK 22.7 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 11.7 CUDA 10.2 CUDA 11.0 CUDA 11.7 CUDA 10.2 CUDA 11.0 CUDA 11.7
nvc++ 22.7 22.7 22.7
nvc 22.7 22.7 22.7
nvfortran 22.7 22.7 22.7
nvcc 10.2.89 11.0.221 11.7.60 10.2.89 11.0.221 11.7.60 N/A 11.0.221 11.7.60
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
cuFFTMp N/A N/A 10.8.1 N/A N/A 10.8.1 N/A N/A N/A
cuSOLVERMp N/A N/A 0.2.1 N/A N/A N/A N/A N/A N/A
cuTENSOR 1.5.0 1.5.0 1.5.0 1.5.0 1.5.0 1.5.0 N/A 1.5.0 1.5.0
Nsight Compute 2022.2.0 2022.2.0 2022.2.0
Nsight Systems 2022.2.1.31 2022.2.1.31 2022.2.1.31
OpenMPI 3.1.5 3.1.5 3.1.5
HPC-X N/A 2.11 2.11 N/A N/A N/A N/A 2.11 2.11
UCX N/A 1.13.0 1.13.0 N/A N/A N/A N/A 1.13.0 1.13.0
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 1.15.0 1.9.7 1.9.9 1.15.0 N/A 1.9.10 1.15.0
CUB N/A 1.9.9 1.15.0 N/A 1.9.9 1.15.0 N/A 1.9.9 1.15.0
libcu++ N/A 1.0.0 1.8.0 N/A 1.0.0 1.8.0 N/A 1.0.0 1.8.0

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

CentOS 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8
CentOS 7.9, 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
SLES 12SP4, 12SP5, 15, 15SP1, 15SP2
Ubuntu 18.04, 20.04
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


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


CentOS 8.0, 8.1, 8.2, 8.3, 8.4
RHEL 8.1, 8.2
Ubuntu 18.04, 20.04

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


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 22.7 includes the following CUDA toolchain versions:
  • CUDA 10.2
  • CUDA 11.0
  • CUDA 11.7
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: $ . /proj/nv/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

  • 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.




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