Co-Design for Exascale General Purpose computing on Graphics Processing Units (GPGPU)

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As computing systems move to exascale, they will be dominated by energy-efficiency. This project investigates three aspects related to enabling graphics procesing units (GPUs) to do general purpose computing under this energy-dominated regime. First, simple architectural innovations allow inter-processor communication. Second, this mechanism is exposed to the programming API. Finally, we address domain specific compilation of dense stencil computations. The project advances architecture, programmability and compilation for energy constrained computation, and also contributes to the foundations of compiling domain specific languages (DSLs) for these platforms through the mathematically rigorous program transformation techniques known as the polyhedral model. The research also makes secondary contributions to other broad areas relevant to exascale: end-user programmer productivity through the use of DSLs, impacting the future architecture of exascale computers, and exploration of the tradeoff between special-purpose vs general purpose computing.