Improved Multi-GPU parallelization of a Lagrangian Transport Model

11/22/2022
by   Saheed Bolarinwa, et al.
0

This report highlights our work on improving GPU parallelization by supporting compute nodes with multiple GPUs. However, since the default support for multi-GPUs in OpenACC is limited[6], the current implementation allows each MPI process to access only a single GPU. Thus, the only way to take full advantage of multi-GPU nodes in the current version is to launch multiple processes, which increases resource contention. We investigated the benefits of having only one process offload to all available GPU devices.

READ FULL TEXT
research
12/20/2013

Multi-GPU Training of ConvNets

In this work we evaluate different approaches to parallelize computation...
research
06/14/2019

A Performance Study of the 2D Ising Model on GPUs

The simulation of the two-dimensional Ising model is used as a benchmark...
research
06/14/2021

Scalable and accurate multi-GPU based image reconstruction of large-scale ptychography data

While the advances in synchrotron light sources, together with the devel...
research
01/01/2020

A Hybrid MPI-CUDA Approach for Nonequispaced Discrete Fourier Transformation

Nonequispaced discrete Fourier transformation (NDFT) is widely applied i...
research
06/16/2020

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

The introduction of accelerator devices such as graphics processing unit...
research
03/14/2019

More Bang for Your Buck: Improved use of GPU Nodes for GROMACS 2018

We identify hardware that is optimal to produce molecular dynamics traje...
research
07/01/2019

GPU-based Parallel Computation Support for Stan

This paper details an extensible OpenCL framework that allows Stan to ut...

Please sign up or login with your details

Forgot password? Click here to reset