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The original PARSEC benchmark suite consists of a diverse and representative set of benchmark applications which are useful in evaluating shared-memory multicore architectures. However, it supports only three programming models: Pthreads (SPMD), OpenMP (parallel for), TBB (parallel for, pipeline), lacking support for emerging and widespread task parallel programming models. In this work, we present a task-parallelized PARSEC (TP-PARSEC) in which we have added translations for five different task parallel programming models (Cilk Plus, MassiveThreads, OpenMP Tasks, Qthreads, TBB). Task parallelism enables a more intuitive description of parallel algorithms compared with the direct threading SPMD approach, and ensures a better load balance on a large number of processor cores with the proven work stealing scheduling technique. TP-PARSEC is not only useful for task parallel system developers to analyze their runtime systems with a wide range of workloads from diverse areas, but also enables them to compare performance differences between systems. TP-PARSEC is integrated with a task-centric performance analysis and visualization tool which effectively helps users understand the performance, pinpoint performance bottlenecks, and especially analyze performance differences between systems.

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