TP-PARSEC: A Task Parallel PARSEC Benchmark Suite

Abstract

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.

An Energy-Efficient Routing Protocol for a Modified Fat-Tree Topology in System-on-Chip Design

“…This particular benchmark is dedicated to tracking the movements and positions of the human body through the processing of multiple camera images. Its relevance lies in its ability to assess and optimize the performance of systems handling real-time visual data [30]. The Fat-Tree topology is compared to 2D-Mesh and Torus topologies with an equal number of cores using power consumption and throughput as the performance parameter.…”