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Applied inference
2010
ACM Transactions on Architecture and Code Optimization (TACO)
We propose and apply a new simulation paradigm for microarchitectural design evaluation and optimization. This paradigm enables more comprehensive design studies by combining spatial sampling and statistical inference. Specifically, this paradigm (1) defines a large, comprehensive design space, (2) samples points from the space for simulation, and (3) constructs regression models based on sparse simulations. This approach greatly improves the computational efficiency of microarchitectural
doi:10.1145/1839667.1839670
fatcat:4rwuf5ehqjeitheo6n5e6ecbbm