Please note: This PhD seminar will take place in DC 2310 and online.
Rosina Kharal, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Trevor Brown, Peter Buhr
Recent decades have witnessed a surge in the development of concurrent data structures with an increasing interest in data structures implementing concurrent sets (CSets). Microbenchmarking tools are frequently utilized to evaluate and compare the performance differences across concurrent data structures. The underlying structure and design of the microbenchmarks themselves can play a hidden but influential role in performance results. However, the impact of microbenchmark design has not been well investigated.
In this work, we illustrate instances where concurrent data structure performance results reported by a microbenchmark can vary 10–100x depending on the microbenchmark implementation details. We investigate factors leading to performance variance across three popular microbenchmarks and outline cases in which flawed microbenchmark design can lead to an inversion of performance results between two concurrent data structure implementations. We further derive a prescriptive approach for best practices in the design and utilization of concurrent data structure microbenchmarks.
To attend this PhD seminar on Zoom, please go to https://uwaterloo.zoom.us/j/91317458011?pwd=ZnhJOUQ3ZjBNY2dpNktubklmOGhDZz09.
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Waterloo, ON N2L 3G1