Analyzing GPU Performance in Virtualized Environments: A Case Study

Adel Belkhiri () and Michel Dagenais
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Adel Belkhiri: Department of Computer and Software Engineering, École Polytechnique de Montréal, Montréal, QC H3T 1J4, Canada
Michel Dagenais: Department of Computer and Software Engineering, École Polytechnique de Montréal, Montréal, QC H3T 1J4, Canada

Future Internet, 2024, vol. 16, issue 3, 1-18

Abstract: The graphics processing unit (GPU) plays a crucial role in boosting application performance and enhancing computational tasks. Thanks to its parallel architecture and energy efficiency, the GPU has become essential in many computing scenarios. On the other hand, the advent of GPU virtualization has been a significant breakthrough, as it provides scalable and adaptable GPU resources for virtual machines. However, this technology faces challenges in debugging and analyzing the performance of GPU-accelerated applications. Most current performance tools do not support virtual GPUs (vGPUs), highlighting the need for more advanced tools. Thus, this article introduces a novel performance analysis tool that is designed for systems using vGPUs. Our tool is compatible with the Intel GVT-g virtualization solution, although its underlying principles can apply to many vGPU-based systems. Our tool uses software tracing techniques to gather detailed runtime data and generate relevant performance metrics. It also offers many synchronized graphical views, which gives practitioners deep insights into GVT-g operations and helps them identify potential performance bottlenecks in vGPU-enabled virtual machines.

Keywords: GPU virtualization; GVT-g; performance analysis; software tracing (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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