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of the Dissertation Unified Tasks and Conduits for Programming on Heterogeneous Computing Platforms by Chao Liu Doctor of Philosophy in Computer Engineering Northeastern University, December 2017 Dr. Miriam Leeser, Advisor Computing platforms for high performance and parallel applications have changed from traditional Central Processing Units (CPUs) to hybrid systems which combine CPUs with accelerators such as Graphics Processing Units (GPUs), Intel Xeon Phi, etc. These developments bring more and more challenges to application developers, especially to maintain a high performance application across various platforms. Traditional parallel programming methods are usually low-level. They focus more on data distribution and communications, aiming to generate high performance and scalable applications. The programs are usually closely related to the underlying platform. Once the platform changes or programs are ported to different environments, lots of effort is needed to modify or reprogram. To reduce development effort and improve portability of applications we need a programming method that can hide low-level platform hardware features to ease the programming of parallel applications as well as maintain good performance. In this research, we propose a lightweight and flexible parallel programming framework, Unified Tasks and Conduits (UTC), for heterogeneous computing platforms. In this framework, we provide high level program components, tasks and conduits, for a user to easily construct parallel applications. In a program, computational workloads are abstracted as task objects and different tasks make use of conduit objects for communication. Multiple tasks can run in parallel on different devices and each task can launch a group of threads for execution. In this way, we can separate an applications’ high-level structure from low-level task implementations. When porting such a parallel application to utilize different computing resources on different platforms, the applications’ main structure can remain unchanged and only adopt appropriate task implementations, easing the development effort. Also, the explicit task components can

United tasks and conduits for programming on heterogeneous computing platforms