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Advisor(s)
Abstract(s)
Graphics processors were originally developed for rendering graphics but have recently evolved towards being an
architecture for general-purpose computations. They are also expected to become important parts of embedded systems
hardware -- not just for graphics. However, this necessitates the development of appropriate timing analysis techniques
which would be required because techniques developed for CPU scheduling are not applicable. The reason is that we
are not interested in how long it takes for any given GPU thread to complete, but rather how long it takes for all of them
to complete. We therefore develop a simple method for finding an upper bound on the makespan of a group of GPU
threads executing the same program and competing for the resources of a single streaming multiprocessor (whose
architecture is based on NVIDIA Fermi, with some simplifying assunptions). We then build upon this method to
formulate the derivation of the exact worst-case makespan (and corresponding schedule) as an optimization problem.
Addressing the issue of tractability, we also present a technique for efficiently computing a safe estimate of the worstcase
makespan with minimal pessimism, which may be used when finding an exact value would take too long.
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Citation
Publisher
IEEE
