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We develop a microbenchmark-based performance model for NVIDIA GeForce 200-series GPUs. Our model identifies GPU program bottlenecks and quantitatively analyzes performance, and thus allows programmers and architects to predict the benefits of potential program optimizations and architectural improvements. In particular, we use a microbenchmark-based approach to develop a throughput model for three major components of GPU execution time: the instruction pipeline, shared memory access, anddoi:10.1109/hpca.2011.5749745 dblp:conf/hpca/ZhangO11 fatcat:34wri3iysbhzlgft567adb3afa