In this book we give an overview of modeling techniques used to describe computer systems to mathematical optimization tools. We give a brief introduction to various classes of mathematical optimization frameworks with special focus on mixed integer linear programming which provides a good balance between solver time and expressiveness. We present four detailed case studies -- instruction set customization, data center resource management, spatial architecture scheduling, and resource allocation in tiled architectures -- showing how MILP can be used and quantifying by how much it outperforms traditional design exploration techniques. This book should help a skilled systems designer to learn techniques for using MILP in their problems, and the skilled optimization expert to understand the types of computer systems problems that MILP can be applied to.
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Karthikeyan Sankaralingam is an Associate Professor at the University of Wisconsin-Madison in the department of computer sciences. He leads the Vertical Research group at UW-Madison, exploring a vertically integrated approach to microprocessor design. His research has developed widely cited results on Dark Silicon, hardware specialization in the DySER architecture, and novel generalizations of GPUs. He is a recipient of the NSF Career Award in 2009 and the IEEE TCCA Young Computer Architect Award in 2011. He is an IEEE Senior Member. He got his PhD and MS from the University of Texas at Austin, and his Bachelor's degree from the Indian Institute of Technology, Madras.
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