Asymptotic Peak Utilisation in Heterogeneous Parallel CPU/GPU Pipelines: A Decentralised Queue Monitoring Strategy
Robert Gordon University, UK
High-level programming for heterogeneous and hierarchical parallel systems (HLPGPU), 2012
@article{garba2012asymptotic,
title={Asymptotic Peak Utilisation in Heterogeneous Parallel CPU/GPU Pipelines: A Decentralised Queue Monitoring Strategy},
author={Garba, M.T.},
year={2012}
}
Heterogeneous parallel computing has become an unavoidable consequence of the emergence of GeneralPurpose 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 geared towards optimal utilisation. This paper considers the simple case of a divisible workload based on widely-used numerical linear algebra routines and considers the challenges that present themselves when an attempt is made to efficiently use all resources available with a view in balancing the CPU and GPU utilisation. We suggest a possible queue monitoring strategy that facilitates resource usage for applications that fit the pipeline parallel architectural pattern on heterogeneous multicore/multi-node CPU and GPU systems.
January 19, 2012 by hgpu
