#Gpu benchmark software#

Please see the HPCG-Benchmark for getting started with the HPCG software concepts and best practices.

The HPCG-NVIDIA benchmark uses the same input format as the standard HPCG-Benchmark. Please see the Netlib HPL benchmark for getting started with the HPL software concepts and best practices. The HPL-NVIDIA and HPL-AI-NVIDIA benchmarks use the same input format as the standard Netlib HPL benchmark. Running the HPL-NVIDIA, HPL-AI-NVIDIA, and HPCG-NVIDIA Benchmarks hpcg.sh script to invoke the xhpcg executable.HPCG-NVIDIA in folder /workspace/hpcg-linux-x86_64 contains:.The 21.4-hpcg container provides the HPCG-NVIDIA benchmark in the following folder structure: HPL-AI-NVIDIA in folder /workspace/hpl-ai-linux-x86_64 contains: HPL-NVIDIA in folder /workspace/hpl-linux-x86_64 contains: Hpl.sh script in folder /workspace to invoke the xhpl or xhpl-ai executables. The 21.4-hpl container provides the HPL-NVIDIA and HPL-AI-NVIDIA benchmarks in the following folder structure: For older Docker versions, use nvidia-docker >= 2.0.3.Docker 19.03 or later which includes support for the -gpus option,.>= 418.39 with CUDA forward compatibility.The current container version is aimed at clusters of DGX A100 nodes (Previous GPU generations are expected to work but has not been verified nor optimized with this container). Your system meets the following requirements: The 21.4-hpcg container image is provided with the following packages embedded:Д«efore running the NVIDIA HPC-Benchmarks NGC containers, please ensure that The 21.4-hpl container image is provided with the following packages embedded: The NVIDIA HPC-Benchmarks NGC collection provides two container images: 21.4-hpl and 21.4-hpcg. HPCG is a software package that performs a fixed number of multigrid preconditioned (using a symmetric Gauss-Seidel smoother) conjugate gradient (PCG) iterations using double precision (64 bit) floating point values. NVIDIA's HPCG benchmark accelerates the High Performance Conjugate Gradients (HPCG) Benchmark. NVIDIA's HPL and HPL-AI benchmarks provide software packages to solve a (random) dense linear system in double precision (64 bits) arithmetic and in mixed precision arithmetic using Tensor Cores, respectively, on distributed-memory computers equipped with NVIDIA GPUs, based on the netlib HPL benchmark. The NVIDIA HPC-Benchmarks collection provides three benchmarks (HPL, HPL-AI, and HPCG) widely used in HPC community optimized for performance on NVIDIA accelerated HPC systems.

Gpu benchmark