Efficient support of fine-grained futures in Java']Java

A future is a parallel programming language construct that enables programmers to specify potentially asynchronous computations. We present and empirically evaluate a novel implementation of futures for Java. Our futures implementation is a JVM extension that couples estimates of future computational granularity with underlying resource availability to enable automatic and adaptive decisions of when to spawn futures in parallel or to execute them sequentially. Our system builds from, combines. and extends (i) lazy task creation and (ii) a JVM sampling infrastructure previously used solely for dynamic and adaptive compilation. We empirically evaluate our system using different benchmarks, triggers for automatic spawning of futures, processor availability, and JVM configurations. We show that our future implementation for Java is efficient and scalable for fine-grained Java futures without requiring programmer intervention.