Problem Based Benchmark Suite (2020)

This web page is depracated.
The new version of the benchmarks is available on github at


The problem based benchmark suite (PBBS) is designed to be an open source repository to compare different parallel programming methodologies in terms of performance and code quality. The benchmarks define problems in terms of the function they implement and not the particular algorithm or code they use. We encourage people to implement the benchmarks using any algorithm, with any programming language, with any form of parallelism (or sequentially), and for any machine. The problems are selected so they: Each problem supplies:
  1. The definition of the problems in terms of their function specification (the input they take and the required output given the input).
  2. A set of input distributions on which to test and time implementations.
  3. Input generators for each of the input distributions.
  4. Output testers for testing the correctness and/or quality of the output
  5. A sequential and a parallel base implementation for each problem (in some cases the sequential implementation is just the parallel one on a single processor).
  6. A repository of implementations.
Currently the benchmarks include the following: These are described on the
benchmarks Page. The benchmark codebase were updated in 2020 to use the library.
last modified 13:19, 23 Jul 2021

This project has been funded by the following sources:
Intel Labs Academic Research Office for the Parallel Algorithms for Non-Numeric Computing Program,
National Science Foundation, and
IBM Research.