Heterogeneous GPU Reallocation

James Gleeson, Eyal de Lara

Workshop on Hot Topics in Cloud Computing (HotCloud), San Jose, CA, July 2017

 

Abstract

Emerging cloud markets like spot markets and batch computing services scale up services at the granularity of whole VMs. In this paper, we observe that GPU workloads underutilize GPU device memory, leading us to explore the benefits of reallocating heterogeneous GPUs within existing VMs. We outline approaches for upgrading and downgrading GPUs for OpenCL GPGPU workloads, and show how to minimize the chance of cloud operator VM termination by maximizing the heterogeneous environments in which applications can run.

 

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