Fast data-locality profiling of native execution

Author:

Berg Erik1,Hagersten Erik1

Affiliation:

1. Uppsala University, Uppsala, Sweden

Abstract

Performance tools based on hardware counters can efficiently profile the cache behavior of an application and help software developers improve its cache utilization. Simulator-based tools can potentially provide more insights and flexibility and model many different cache configurations, but have the drawback of large run-time overhead.We present StatCache, a performance tool based on a statistical cache model. It has a small run-time overhead while providing much of the flexibility of simulator-based tools. A monitor process running in the background collects sparse memory access statistics about the analyzed application running natively on a host computer. Generic locality information is derived and presented in a code-centric and/or data-centric view.We evaluate the accuracy and performance of the tool using ten SPEC CPU2000 benchmarks. We also exemplify how the flexibility of the tool can be used to better understand the characteristics of cache-related performance problems.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference38 articles.

Cited by 28 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. DroidPerf: Profiling Memory Objects on Android Devices;Proceedings of the 29th Annual International Conference on Mobile Computing and Networking;2023-07-10

2. Precise event sampling‐based data locality tools for AMD multicore architectures;Concurrency and Computation: Practice and Experience;2023-04-03

3. DJXPerf: Identifying Memory Inefficiencies via Object-Centric Profiling for Java;Proceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization;2023-02-17

4. ReuseTracker : Fast Yet Accurate Multicore Reuse Distance Analyzer;ACM Transactions on Architecture and Code Optimization;2022-03-31

5. A Study on Modeling and Optimization of Memory Systems;Journal of Computer Science and Technology;2021-01

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