Coven: A computational model and problem solving environment framework for supporting optimization of parallel applications

As high performance computers continue to gain in acceptance and presence globally, more people are beginning to use them. This increase in use has brought parallel computing to groups seeking its performance benefits but who may not be trained in parallel computing. Problem solving environments (PSEs) have long been a software mechanism to ease programming complexity and are also gaining in popularity in the high performance computing realm. However, while PSEs have been useful in simplifying parallel program implementation, most lack the ability to optimize an application to perform with efficiency on the target architecture.; This work details a model of computation for parallel computing called the Coven model and the Coven PSE which implements the model. The Coven model makes it possible for the PSE to optimize applications implemented in it by understanding the application's computational structure, including data and control flow. The design and implementation of the Coven PSE is detailed and includes a suite of features that ease parallel programming by exploiting properties of the Coven model.; Three optimizations (multi-threading, dynamic load balancing, and checkpoint/recovery) are detailed and analyzed to study the performance benefits they provide to Coven applications. Using real applications such as the FFT, fractal generation, N-Body simulation, and a heat transfer simulation, this work examines both the performance improvement by employing these optimizations as well as the complexity of implementing the optimization outside of Coven. We conclude that Coven can provide these optimizations with almost no programming cost to the user and can be used to achieve performance gains. Most importantly, this work makes accessible these optimizations to users without the need for them to possess parallel computing expertise.