REDSPY

Abstract

Complex code bases with several layers of abstractions have abundant inefficiencies that affect the execution time. Value redundancy is a kind of inefficiency where the same values are repeatedly computed, stored, or retrieved over the course of execution. Not all redundancies can be easily detected or eliminated with compiler optimization passes due to the inherent limitations of the static analysis. Microscopic observation of whole executions at instruction- and operand-level granularity breaks down abstractions and helps recognize redundancies that masquerade in complex programs. We have developed REDSPY---a fine-grained profiler to pinpoint and quantify redundant operations in program executions. Value redundancy may happen over time at same locations or in adjacent locations, and thus it has temporal and spatial locality. REDSPY identifies both temporal and spatial value locality. Furthermore, REDSPY is capable of identifying values that are approximately the same, enabling optimization opportunities in HPC codes that often use floating point computations. REDSPY provides intuitive optimization guidance by apportioning redundancies to their provenance---source lines and execution calling contexts. REDSPY pinpointed dramatically high volume of redundancies in programs that were optimization targets for decades, such as SPEC CPU2006 suite, Rodinia benchmark, and NWChem---a production computational chemistry code. Guided by REDSPY, we were able to eliminate redundancies that resulted in significant speedups.