Performance and Energy Efficiency of CUDA and OpenCL for GPU Computing using Python

In this work, we examine the performance and energy efficiency when using Python for developing HPC codes running on the GPU. We investigate the portability of performance and energy efficiency between CUDA and OpenCL; between GPU generations; and between low-end, mid-range and high-end GPUs. Our fi...

Full description

Saved in:
Bibliographic Details
Main Authors: Holm, Håvard Heitlo, Brodtkorb, André R, Sætra, Martin Lilleeng
Format: Article
Language:English
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this work, we examine the performance and energy efficiency when using Python for developing HPC codes running on the GPU. We investigate the portability of performance and energy efficiency between CUDA and OpenCL; between GPU generations; and between low-end, mid-range and high-end GPUs. Our findings show that for some combinations of GPU and GPU code, there is a significant speedup for CUDA over OpenCL, but that this does not hold in general. Our experiments show that performance in general varies more between different GPUs, than between using CUDA and OpenCL. Finally, we show that tuning for performance is a good way of tuning for energy efficiency.