Automatic Multi-GPU Code Generation applied to Simulation of Electrical Machines

TL;DR

This paper presents a model-driven approach using OpenCL and MARTE to automatically generate multi-GPU code for electrical machine simulations, simplifying parallel programming for non-experts and improving performance.

Contribution

It introduces a novel MDE-based method for automatic multi-GPU code generation, enhancing usability and adaptability for heterogeneous architectures.

Findings

Performance improvements with multi-GPU environments

Reduced development complexity for parallel applications

Enhanced flexibility through model reuse

Abstract

The electrical and electronic engineering has used parallel programming to solve its large scale complex problems for performance reasons. However, as parallel programming requires a non-trivial distribution of tasks and data, developers find it hard to implement their applications effectively. Thus, in order to reduce design complexity, we propose an approach to generate code for hybrid architectures (e.g. CPU + GPU) using OpenCL, an open standard for parallel programming of heterogeneous systems. This approach is based on Model Driven Engineering (MDE) and the MARTE profile, standard proposed by Object Management Group (OMG). The aim is to provide resources to non-specialists in parallel programming to implement their applications. Moreover, thanks to model reuse capacity, we can add/change functionalities or the target architecture. Consequently, this approach helps industries to achieve their time-to-market constraints and confirms by experimental tests, performance improvements using multi-GPU environments.