SCHEDULE: NOV 15-20, 2015

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ScaAnalyzer: A Tool to Identify Memory Scalability Bottlenecks in Parallel Programs

SESSION: Performance Tools and Models

EVENT TYPE: Papers, Best Paper Finalists

EVENT TAG(S): Performance

TIME: 1:30PM - 2:00PM

SESSION CHAIR(S): Kalyan Kumaran

AUTHOR(S):Xu Liu, Bo Wu

ROOM:18AB

ABSTRACT:

It is difficult to scale parallel programs in a system that employs a large number of cores. To identify scalability bottlenecks, existing tools principally pinpoint poor thread synchronization strategies and unnecessary data communication. Memory subsystem is one of the key contributors to poor parallel scaling in multicore machines. State-of-the-art tools, however, either lack sophisticated capabilities or are completely ignorant in pinpointing scalability bottlenecks arising from the memory subsystem. To address this issue, we developed a tool—ScaAnalyzer to pinpoint scaling losses due to poor memory access behaviors of parallel programs. ScaAnalyzer collects, attributes, and analyzes memory-related metrics during program execution while incurring very low overhead. ScaAnalyzer provides high-level, detailed guidance to programmers for scalability optimization. We demonstrate the utility of ScaAnalyzer with case studies of three parallel benchmarks. For each benchmark, ScaAnalyzer identifies scalability bottlenecks caused by poor memory access behaviors and provides optimization guidance that yields significant improvement in scalability.

Chair/Author Details:

Kalyan Kumaran (Chair) - Argonne National Laboratory|

Xu Liu - College of William & Mary

Bo Wu - Colorado School of Mines

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society