ZeroSpy: Exploring Software Inefficiency with Redundant Zeros
ZeroSpy: Exploring Software Inefficiency with Redundant Zeros
复制标题
ZeroSpy：通过冗余零探索软件效率低下
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Xu Liu
中科院分区：
文献类型：
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作者：
Xin You;Hailong Yang;Zhongzhi Luan;D. Qian;Xu Liu
冗余零会导致效率低下，其中零值被重复加载和计算，从而导致不必要的内存流量和标识计算，浪费内存带宽和CPU资源。由于静态分析中的限制，优化编译器难以消除这些零相关的低效率。相比之下，硬件方法可以在不修改代码的情况下优化低效率，但在商品处理器中并没有被广泛采用。在本文中，我们提出了ZeroSpy -一个细粒度的分析器，以确定冗余零所造成的数据结构和无用的计算使用不当。ZeroSpy还通过揭示源代码行和调用上下文中冗余零的位置来提供直观的优化指导。实验结果表明，ZeroSpy能够识别经过多年高度优化的程序中的冗余零。基于ZeroSpy揭示的优化指导，我们可以在消除冗余零点后实现显著的加速。
Redundant zeros cause inefficiencies in which the zero values are loaded and computed repeatedly, resulting in unnecessary memory traffic and identity computation that waste memory bandwidth and CPU resources. optimizing compilers is difficult in eliminating these zero-related inefficiencies due to limitations in static analysis. Hardware approaches, in contrast, optimize inefficiencies without code modification, but are not widely adopted in commodity processors. In this paper, we propose ZeroSpy - a fine-grained profiler to identify redundant zeros caused by both inappropriate use of data structures and useless computation. ZeroSpy also provides intuitive optimization guidance by revealing the locations where the redundant zeros happen in source lines and calling contexts. The experimental results demonstrate ZeroSpy is capable of identifying redundant zeros in programs that have been highly optimized for years. Based on the optimization guidance revealed by ZeroSpy, we can achieve significant speedups after eliminating redundant zeros.
影响因子：
6.3
作者：
Li, Wu;Carrete, Jesus;Mingo, Natalio
通讯作者：
Mingo, Natalio