GPU

GPU Computing on Sapelo2

Hardware

For a description of the Graphics Processing Units (GPU) device specifications, please see GPU Hardware.

The following table summarizes the GPU devices available on sapelo2:

Number of nodes	CPU cores/node	CPU RAM/node	CPU processor	GPU model	GPU devices/node	GPU memory/device	Partition Name	Notes
1	64	1TB	AMD Milan	A100	4	80GB	gpu_p, gpu_30d_p	Need to request --gres=gpu:A100
4	32	192GB	Intel Skylake	P100	1	16GB	gpu_p, gpu_30d_p
2	K40

Software

Sapelo2 has the following tools for programming for GPUs:

1. NVIDIA CUDA toolkit

Several versions of the CUDA toolkit are available. Please see our CUDA page.

2. PGI/CUDA compilers

The PGI compilers available on Sapelo2 support GPU acceleration, including Fortran/CUDA.

For more information on the GPU support of PGI compilers, please visit the PGI website http://www.pgroup.com/resources/cudafortran.htm

For information on versions of PGI compilers installed on Sapelo2, please see Code Compilation on Sapelo2.

3. OpenACC

Using PGI Accelerator compilers, programmers can accelerate applications on x64+accelerator platforms by adding OpenACC compiler directives to Fortran and C programs and then recompiling with appropriate compiler options. Please see http://www.pgroup.com/resources/accel.htm

OpenACC is also supported by GNU compilers, especially the latest versions, e.g. GNU 7.2.0, installed on Sapelo2. For more information on OpenACC support by GNU compilers, please refer to https://gcc.gnu.org/wiki/OpenACC

For information on versions of GNU compilers installed on Sapelo2, please see Code Compilation on Sapelo2.

Running Jobs

For information on how to run GPU jobs on Sapelo2, please refer to Running Jobs on Sapelo2.