GPUs on NeSI
GPUs (Graphics Processing Units) have been used for many years to successfully accelerate scientific applications. The amount of work required to take advantage of GPU acceleration can vary significantly depending on the code you are using, the problem you are trying to solve, etc. In some cases it may be as simple as recompiling your code to enable GPU support; other cases may require modifying the code, for example using an API such as OpenACC to offload loops to the GPU, or even porting code to CUDA to take full advantage of the parallelisation offered by the GPU.
NeSI’s consultancy service (https://www.nesi.org.nz/services/consultancy) can help researchers take advantage of the GPUs on our HPC systems. Here we will present an overview of NeSI’s GPU capability, including our recent investment into the latest NVIDIA A100 cards, and then highlight some case studies where we have helped researchers take advantage of GPU acceleration, to give the audience an idea of the amount of work involved and potential speedups.
Some examples of recent work we have done in this area include: enabling GPU support in the molecular dynamics application NAMD to accelerate protein modelling simulations; using OpenACC to accelerate a code for computing the log-determinant of a matrix, a fundamental kernel of some data science applications; linking against cuBLAS to accelerate a tropical circulation model; and writing CUDA code to accelerate N-body simulations of the solar system.
Chris Scott is a Research Software Engineer for NeSI.
Wolfgang Hayek is a Research Software Engineer for NeSI and NIWA.
Alex Pletzer is a Research Software for NeSI.
Maxime Rio is a Data Science Engineer for NeSI and NIWA.
Georgina Rae is NeSI’s Science Engagement Manager.