TY - GEN
T1 - Zerospy
T2 - 2020 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2020
AU - You, Xin
AU - Yang, Hailong
AU - Luan, Zhongzhi
AU - Qian, Depei
AU - Liu, Xu
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - 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.
AB - 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.
KW - Performance Profiling and optimization
KW - Redundant Zero
KW - Software Inefficiency
UR - https://www.scopus.com/pages/publications/85102370061
U2 - 10.1109/SC41405.2020.00033
DO - 10.1109/SC41405.2020.00033
M3 - 会议稿件
AN - SCOPUS:85102370061
T3 - International Conference for High Performance Computing, Networking, Storage and Analysis, SC
BT - Proceedings of SC 2020
PB - IEEE Computer Society
Y2 - 9 November 2020 through 19 November 2020
ER -