A software-only scheme for managing heap data on limited local memory(LLM) multicore processors

Ke Bai, Aviral Shrivastava
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引用次数: 5

Abstract

This article presents a scheme for managing heap data in the local memory present in each core of a limited local memory (LLM) multicore architecture. Although managing heap data semi-automatically with software cache is feasible, it may require modifications of other thread codes. Crossthread modifications are very difficult to code and debug, and will become more complex and challenging as we increase the number of cores. In this article, we propose an intuitive programming interface, which is an automatic and scalable scheme for heap data management. Besides, for embedded applications, where the maximum heap size can be profiled, we propose several optimizations on our heap management to significantly decrease the library overheads. Our experiments on several benchmarks from MiBench executing on the Sony Playstation 3 show that our scheme is natural to use, and if we know the maximum size of heap data, our optimizations can improve application performance by an average of 14%.
本文介绍了一种管理本地内存中的堆数据的方案,这些堆数据存在于有限本地内存(LLM)多核架构的每个核心中。尽管使用软件缓存半自动管理堆数据是可行的,但它可能需要修改其他线程代码。交叉线程修改非常难以编码和调试,并且随着内核数量的增加将变得更加复杂和具有挑战性。在本文中,我们提出了一个直观的编程接口,这是一个自动和可扩展的堆数据管理方案。此外,对于可以分析最大堆大小的嵌入式应用程序,我们建议对堆管理进行若干优化,以显著降低库开销。我们在索尼Playstation 3上执行MiBench的几个基准测试中进行的实验表明,我们的方案可以很自然地使用,如果我们知道堆数据的最大大小,我们的优化可以将应用程序性能平均提高14%。
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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