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UID:submissions.supercomputing.org_SC20_sess141_pap278@linklings.com
SUMMARY:Zerospy: Exploring Software Inefficiency with Redundant Zeros
DESCRIPTION:Paper\n\nZerospy: Exploring Software Inefficiency with Redunda
 nt Zeros\n\nYou, Yang, Luan, Qian, Liu\n\nRedundant zeros cause inefficien
 cies in which the zero values are loaded and computed repeatedly, resultin
 g in unnecessary memory traffic and identity computation that waste memory
  bandwidth and CPU resources. Optimizing compilers is difficult in elimina
 ting these zero-related inefficiencies due to limitations in static analys
 is. 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 comp
 utation. ZeroSpy also provides intuitive optimization guidance by revealin
 g the locations where the redundant zeros happen in source lines and calli
 ng contexts. The experimental results demonstrate ZeroSpy is capable of id
 entifying redundant zeros in programs that have been highly optimized for 
 years. Based on the optimization guidance revealed by ZeroSpy, we can achi
 eve significant speedups after eliminating redundant zeros.\n\nTag: Graph 
 Algorithms, Performance/Productivity Measurement and Evaluation\n\nRegistr
 ation Category: Tech Program Reg Pass
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