Characterization of Task-based Benchmarks from the Barcelona OpenMP Task Suite

The parallel programming community is witnessing two main trends - the growing popularity of task-based programming models and the growing complexity of multicore hardware. In order to see how these two trends fit each other, it is important to characterize the behavior of task-based benchmarks on modern multicore hardware. Besides leading to benchmark design optimizations, such characterization enables making educated tradeoffs in the design of task-handling middleware such as compilers and runtime systems. In this thesis work, we characterize task-based benchmarks from the Barcelona OpenMP Tasks Suite (BOTS) at the task-level. We focus on two aspects: how does the task scheduler fare in handling programmer exposed parallelism, and how does the task decomposition make use of the hardware memory hierarchy. Our characterization considers two diverse multicore architectures - one built for server systems, and the other for embedded systems. With respect to middleware, we consider GCC’s implementation of OpenMP tasks. Our contributions are two-fold. First, we complement existing thread and application level characterization of BOTS benchmarks with a finer task and memory hierarchy level characterization. Next, we identify BOTS performance bottlenecks and optimize Sort and FFT benchmarks to reduce their execution time by a factor 2 and 1.65 respectively on the server architecture