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Overview
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NVidia’s HPC
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is a comprehensive suite of compilers, libraries and tools for HPC, including the proven compilers, libraries and software tools essential to maximizing developer productivity and the performance and portability of HPC applications.
Documentation: Please refer for details on:
Compilers:
nvc,nvc++,nvfortranandnvcc.Programming models: C++ parallel algorithms, MPI, OpenACC, OpenMP and CUDA.
Math libraries: cuBLAS, cuTENSOR, cuPARSE, cuSOLVER, cuFFT…
Tools: CUDA-GDB, Nsight
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Using
Beartooth: Use the module name
nvhpcto discover versions available and to load the application.Teton: Use the module name
hpc-sdkto discover versions available and to load the application.
Documentation
Compilers:
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Compilers: Quick Overview
The SDK provides a number of compilers. Choose depending on your language and programming model:
Compiler | Description | Supports |
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nvc | C11 compiler for NVIDIA GPUs and AMD, Intel, OpenPOWER, and Arm CPUs. It invokes the C compiler, assembler, and linker for the target processors with options derived from its command line arguments. |
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nvc++ |
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C++17 compiler for NVIDIA GPUs and Intel CPUs. It invokes the C++ compiler, assembler, and linker for the target processors with options derived from its command line arguments. |
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nvfortran |
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Fortran compiler for NVIDIA GPUs and Intel CPUs. It invokes the Fortran compiler, assembler, and linker for the target processors with options derived from its command line arguments. |
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nvcc |
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CUDA C and CUDA C++ compiler driver for NVIDIA GPUs. nvcc accepts a range of conventional compiler options, such as for defining macros and include/library paths, and for steering the compilation process. |
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nvcc produces optimized code for NVIDIA GPUs and drives a supported host compiler for |
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Version 22.7, CUDA and GPUs:
Has been installed and uses CUDA 11.7 by default.
If you specifically need to use CUDA then load this module using:
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module load cuda/11.7.1 |
and when creating an interactive session (salloc) or submitting a batch script (sbatch) then remember to request a GPU resource and use srun when running any executables. Further information of requesting GPUs on teton can be found here.
Version 20.7, CUDA and GPUs:
Has been installed and uses CUDA 10.1 by default.
If you specifically need to use CUDA then load this module using:
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module load cuda/10.1.243 |
and when creating an interactive session (salloc) or submitting a batch script (sbatch) then remember to request a GPU resource and use srun when running any executables. Further information for requesting GPUs on teton can be found here.
Math Libraries
For further documentation see the respective pages:
Tools:
Both the Nsight_Compute and Nsight_Systems tools have been installed, but not tested. Documentation on their use will be added as we use/learn. For further documentation see:
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AMD, Intel, OpenPOWER, and Arm CPUs. |