Efficient System-Enforced Deterministic Parallelism

Amittai Aviram, Shu-Chun Weng, Sen Hu, and Bryan Ford
Yale University

Winner of Jay Lepreau Best Paper Award

9th USENIX Symposium on Operating Systems Design and Implementation (OSDI 10),
October 4-6, 2010, Vancouver, BC, Canada


Deterministic execution offers many benefits for debugging, fault tolerance, and security. Current methods of executing parallel programs deterministically, however, often incur high costs, allow misbehaved software to defeat repeatability, and transform time-dependent races into input- or path-dependent races without eliminating them. We introduce a new parallel programming model addressing these issues, and use Determinator, a proof-of-concept OS, to demonstrate the model's practicality. Determinator's microkernel API provides only “shared-nothing” address spaces and deterministic interprocess communication primitives to make execution of all unprivileged code—well-behaved or not—precisely repeatable. Atop this microkernel, Determinator's user-level runtime adapts optimistic replication techniques to offer a private workspace model for both thread-level and process-level parallel programing. This model avoids the introduction of read/write data races, and converts write/write races into reliably-detected conflicts. Coarse-grained parallel benchmarks perform and scale comparably to nondeterministic systems, on both multicore PCs and across nodes in a distributed cluster.

Paper: PDF (CACM Research Highlights version)

Slides: OpenOffice, PDF

This research is sponsored by the National Science Foundation under grant CNS-1017206.