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HJ integrates a wide range of parallel programming constructs (e.g., async tasks, futures, data-driven tasks, forall, barriers, phasers, transactions, actors) in a single programming model that enables unique combinations of these constructs (e.g., nested combinations of task and actor parallelism). The orthogonal classes of parallel constructs enables programmers with a basic knowledge of Java to get started quickly with expressing a wide range of parallel patterns. HJ is capable of expressing many different forms of parallel patterns including data parallelism, pipeline parallelism, stream parallelism, loop parallelism, and divide-and-conquer parallelism.
HJ-lib is built using Java 8 closures lambda expressions and can run on any Java 8 JVM. Older JVMs can be targeted by relying on external bytecode transformations tools for compatibility. The HJ runtime is responsible for orchestrating the creation, execution, and termination of HJ tasks, and features both work-sharing and work-stealing schedulers. HJ is used at Rice University as an introductory parallel programming language for second-year undergraduate students. A wide variety of benchmarks have been ported to HJ, including a full application that was originally written in Fortran 90. Being a pedagogic programming model, HJ-lib is also an attractive tool for educators with numerous educational resources available from the sophomore-level COMP 322 course offered at Rice University.
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