GEMM-ArchProfiler：一个模拟框架，用于在异构CPU架构上的真实CNN工作负载中进行通用矩阵乘法的硬件级分析和性能分析

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2025-06-28 DOI:10.1016/j.softx.2025.102243

Binu Ayyappan , G. Santhosh Kumar

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引用次数: 0

摘要

在本文中，作者提出了GEMM-ArchProfiler，一个用于评估卷积神经网络中一般矩阵乘法性能的仿真框架。针对资源受限的边缘和物联网系统，这些系统依赖于基于cpu的架构，该框架通过优化工作负载分析来解决硬件限制。在gem5模拟器的支持下，gem - archprofiler提供了对内存使用、缓存行为、执行延迟和能耗的洞察。它集成了定制的Darknet库来模拟真实的CNN工作负载，并包括一个用户友好的CPU配置机制和事件分析脚本。该工具连接了工作负载分析和部署，帮助在不同CPU架构上高效地实现AI。

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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GEMM-ArchProfiler: A simulation framework for hardware-level profiling and performance analysis of General Matrix Multiplication in real CNN workloads on heterogeneous CPU architectures

In this paper, the authors present GEMM-ArchProfiler, a simulation framework for evaluating General Matrix Multiplication performance in convolutional neural networks. Targeted at resource-constrained edge and IoT systems, which rely on CPU-based architectures, the framework addresses hardware limitations through optimized workload profiling. Powered by the gem5 simulator, GEMM-ArchProfiler provides insights into memory usage, cache behavior, execution latency, and energy consumption. It integrates customized Darknet libraries to simulate realistic CNN workloads and includes a user-friendly CPU configuration mechanism and event analysis script. This tool bridges workload analysis and deployment, aiding efficient AI implementation on diverse CPU architectures.

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.