Booz Allen Hamilton Colloquium: "The Resurgence of Software Performance Engineering"
Friday, April 26, 2019
3:30 p.m.-4:30 p.m.
1110 Kim Engineering Building
301 405 4471
The Resurgence of Software Performance Engineering
Charles E. Leiserson
MIT Computer Science and Artificial Intelligence Laboratory
Today, most application developers write code without much regard for how quickly it will run. Moreover, once the code is written, it is rare for it to be reengineered to run faster. But two technology trends of historic proportions are instigating a resurgence in software performance engineering, the art of making code run fast. The first is the emergence of cloud computing, where the economics of renting computation, as opposed to buying it, heightens the utility of application speed. The second is the end of Moore's Law, the 50-year technology trend which has, until recently, relentlessly doubled the number of transistors on a semiconductor chip every two years. With the attenuation of this major source of computing performance, application programmers will increasingly find themselves turning to software performance engineering in order to develop innovative products and applications.
Charles E. Leiserson received his B.S. from Yale University in 1975 and his Ph.D. from Carnegie Mellon University in 1981. He joined the faculty of the Massachusetts Institute of Technology in 1981, where he is now the Edwin Sibley Webster Professor in MIT’s Electrical Engineering and Computer Science (EECS) Department. He is Associate Director and Chief Operating Officer of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), the largest on-campus laboratory at MIT, where he also leads the Supertech research group. He is a Margaret MacVicar Faculty Fellow, the highest recognition at MIT for undergraduate teaching. He is a Fellow of four professional societies — AAAS, ACM, IEEE, and SIAM — and he is a member of the National Academy of Engineering. He has received many Best Paper awards at prestigious conferences, as well as major awards, including the ACM-IEEE Computer Society Ken Kennedy Award, the IEEE Computer Society Taylor L. Booth Education Award, ACM Paris Kanellakis Theory and Practice Award, and the ACM and Hertz Foundation Doctoral Dissertation Awards.