Department of Computer Science & Engineering

In this paper, we propose a novel set of techniques that allows multicore programmers and architects alike to rapidly estimate the availability of parallelism in their target programs. We present p-ray, which, given an application and the input, shows the nested relationship and availability of parallelism across different regions in complex programs, using a parallelism chart, or p-chart. P-ray also prioritizes the regions, suggesting the ordering that the programmer should attack them in, based on the estimated parallelism and the code complexity. P-ray can also estimate the kind of parallelism (TLP, DLP or ILP) that is found in each region, which allows the user to determine the available techniques are likely to work. In this paper, we show three case studies, including SpecInt's gzip, and Mat2C's capacitor, and Nasa7's Vpenta, and follow up with results which compare actual parallelization results of a benchmark suite against the results predicted by p-ray.

Pre-2018 CSE ID: CS2009-0950