Efficient Race Detection for Reducer Hyperobjects

Author:

Lee I-Ting Angelina1,Schardl Tao B.2

Affiliation:

1. Washington University in St. Louis, MO

2. MIT CSAIL, Cambridge, MA

Abstract

A multithreaded Cilk program that is ostensibly deterministic may nevertheless behave nondeterministically due to programming errors in the code. For a Cilk program that uses reducers—a general reduction mechanism supported in various Cilk dialects—such programming errors are especially challenging to debug, because the errors can expose the nondeterminism in how the Cilk runtime system manages reducers. We identify two unique types of races that arise from incorrect use of reducers in a Cilk program, and we present two algorithms to catch these races. The first algorithm, called the Peer-Set algorithm, detects view-read races, which occur when the program attempts to retrieve a value out of a reducer when the read may result in a nondeterministic value, such as before all previously spawned subcomputations that might update the reducer have necessarily returned. The second algorithm, called the SP+ algorithm, detects determinacy races—instances where a write to a memory location occurs logically in parallel with another access to that location—even when the raced-on memory locations relate to reducers. Both algorithms are provably correct, asymptotically efficient, and can be implemented efficiently in practice. We have implemented both algorithms in our prototype race detector, Rader. When running Peer-Set, Rader incurs a geometric-mean multiplicative overhead of 2.56 over running the benchmark without instrumentation. When running SP+, Rader incurs a geometric-mean multiplicative overhead of 16.94.

Funder

MIT Akamai Fellowship

NSF Graduate Research Fellowship

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Modelling and Simulation,Software

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