Asymptotic Peak Utilisation in Heterogeneous Parallel CPU/GPU Pipelines: A Decentralised Queue Monitoring Strategy

Garba, Michael T. and González-Vélez, Horacio (2012) Asymptotic Peak Utilisation in Heterogeneous Parallel CPU/GPU Pipelines: A Decentralised Queue Monitoring Strategy. Parallel Processing Letters (ppl), 22 (2). ISSN 0129-6264

Full text not available from this repository.

Abstract

Widespread heterogeneous parallelism is unavoidable given the emergence of General-Purpose computing on graphics processing units (GPGPU). The characteristics of a Graphics Processing Unit (GPU)—including significant memory transfer latency and complex performance characteristics—demand new approaches to ensuring that all available computational resources are efficiently utilised. This paper considers the simple case of a divisible workload based on widely-used numerical linear algebra routines and the challenges that prevent efficient use of all resources available to a naive SPMD application using the GPU as an accelerator. We suggest a possible queue monitoring strategy that facilitates resource usage with a view to balancing the CPU/GPU utilisation for applications that fit the pipeline parallel architectural pattern on heterogeneous multicore/multi-node CPU and GPU systems. We propose a stochastic allocation technique that may serve as a foundation for heuristic approaches to balancing CPU/GPU workloads.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions:	School of Computing > Staff Research and Publications
Depositing User:	Caoimhe Ní Mhaicín
Date Deposited:	28 Feb 2014 13:39
Last Modified:	11 Jun 2014 16:09
URI:	https://norma.ncirl.ie/id/eprint/955

Actions (login required)

View Item