Speculative synchronization and thread management for fine granularity threads

Performance of multithreaded programs is heavily influenced by the latencies of the thread management and synchronization operations. Improving these latencies becomes especially important when the parallelization is performed at fine granularity. In this work we examine the interaction of speculative execution with the thread-related operations. We develop a unified framework which allows all such operations to be executed speculatively and provides efficient recovery mechanisms to handle misspeculation of branches which affect instructions in several threads. The framework was evaluated in the context of Inthreads, a programming model designed for very fine grain parallelization. Our measurements show that the speedup obtained by speculative execution of the threads-related instructions can reach 25%.