Communication Patterns in Cloud Haskell (Part 2)
Posted on October 8, 2012Performance
In Part 1 of this series we introduced a number of basic Cloud Haskell communication patterns. All these patterns will work fine for modest numbers of work items; in this blog post we’re going to look at the performance and memory use for much larger numbers of work items, so we can see how each pattern scales up. We will see that scalability improves as we move from master-slave to work-pushing to work-stealing, and that many further improvements can still be made. More importantly, we hope to help you to predict runtime behaviour from your code, so that you can write more scalable and high-performance code.