Maryam Sadooghi-Alvandi

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Graphics processors (GPU) offer the promise of more than an order of magnitude speedup over conventional processors for certain non-graphics computations. Because the GPU is often presented as a C-like abstraction (e.g., Nvidia's CUDA), little is known about the characteristics of the GPU's architecture beyond what the manufacturer has documented. This work(More)
This work introduces a new branch predictor design that increases the perceived predictor capacity without increasing its delay by using a large virtual second-level table allocated in the second-level caches. Virtualization is applied to a state-of-the-art multi-table branch predictor. We evaluate the design using instruction count as proxy for timing on a(More)
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