Analyzing GPU Performance in Virtualized Environments: A Case Study

Future Internet Pub Date : 2024-02-23 DOI:10.3390/fi16030072

Adel Belkhiri, Michel Dagenais

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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.

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分析虚拟化环境中的 GPU 性能：案例研究

图形处理器（GPU）在提高应用性能和增强计算任务方面发挥着至关重要的作用。凭借其并行架构和能效，图形处理器已成为许多计算场景中必不可少的设备。另一方面，GPU 虚拟化的出现是一项重大突破，因为它为虚拟机提供了可扩展和可调整的 GPU 资源。然而，这项技术在调试和分析 GPU 加速应用程序的性能方面面临挑战。目前的大多数性能工具都不支持虚拟 GPU（vGPU），这凸显了对更先进工具的需求。因此，本文介绍了一种专为使用 vGPU 的系统设计的新型性能分析工具。我们的工具与英特尔 GVT-g 虚拟化解决方案兼容，但其基本原理也适用于许多基于 vGPU 的系统。我们的工具使用软件跟踪技术收集详细的运行时数据，并生成相关的性能指标。它还提供了许多同步图形视图，使从业人员能够深入了解 GVT-g 的运行情况，并帮助他们识别启用了 vGPU 的虚拟机中潜在的性能瓶颈。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Future Internet

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