A protocol-centric approach to on-the-fly race detection

We present the design and evaluation of a new data-race-detection technique . Our technique executes at runtime rather than post-mortem, and handles un modified shared-memory applications that run on top of CVM, a software dist ributed shared memory system. We do not assume explicit associations betwee n synchronization and shared data, and require neither compiler support nor program source. Instead, we use a binary code re-writer to instrument inst ructions that may access shared memory. The most novel aspect of our system is that we are able to use information from the underlying memory system i mplementation in order to reduce the number of comparisons made at runtime. We present an experimental evaluation of our techniques by using out syste m to look far data races in five common shared-memory programs. We quantify the effect of several optimizations to the basic technique: data flow anal ysis, instrumentation batching, runtime code modification, and instrumentat ion inlining. Our system correctly found races in three of the five program s, including two from a standard benchmark suite. The slowdown of this debu gging technique averages less than 2.5 for our applications.