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Multiprovision: a Design Space Exploration tool for multi-tenant resource provisioning in CPU–GPU environments

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Abstract

Cloud warehouses are increasingly adopting CPU–GPU collaborative systems to leverage diverse types and levels of parallelism in applications. These environments are shared among multiple clients to achieve maximum resource utilization with energyf efficiency and scalability. While OpenCL simplifies resource provisioning in such heterogeneous systems, ensuring the effective distribution of tasks remains challenging as CPU–GPU available architectures and workload characteristics can vary significantly. This study addresses the challenge of efficiently provisioning resources in OpenCL-based CPU–GPU cloud environments. To tackle this challenge, we introduce MultiProvision, a Design Space Exploration tool for multi-tenant resource provisioning in CPU–GPU environments. MultiProvision facilitates the identification of the most suitable provisioning strategy for a given workload and architecture scenario in a transparent manner. Through comprehensive evaluations encompassing various architecture combinations and workloads, we demonstrate that the choice of the most efficient provisioning strategy depends on the target architecture, workload characteristics, and optimization objectives, such as makespan or energy. We show that the appropriate strategy can achieve remarkable gains of up to 13.15\(\times \) in makespan and 4.52\(\times \) in energy compared to a GPU-only execution.

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Availability of data and materials

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Notes

  1. The repository is available on GitHub under the following link: https://github.com/MultiProvision/MultiProvision.

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Acknowledgements

This study was financed in part by the Coordenaşão de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, São Paulo Research Foundation (FAPESP) Grant #2021/06825-8, FAPERGS, and CNPq.

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Authors and Affiliations

  1. PPGC - Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil

    Michael G. Jordan, Tiago Knorst, Guilherme Korol & Antonio Carlos Schneider Beck

  2. PGMICRO - Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil

    Julio Costella Vicenzi & Antonio Carlos Schneider Beck

  3. Electronics and Computing Department, Universidade Federal de Santa Maria (UFSM), Santa Maria, Brazil

    Mateus Beck Rutzig

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  1. Michael G. Jordan
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  2. Julio Costella Vicenzi
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Correspondence to Michael G. Jordan.

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Jordan, M.G., Vicenzi, J.C., Knorst, T. et al. Multiprovision: a Design Space Exploration tool for multi-tenant resource provisioning in CPU–GPU environments. Des Autom Embed Syst 27, 241–273 (2023). https://doi.org/10.1007/s10617-023-09279-3

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