The Supersized Science podcast highlights research and discoveries nationwide enabled by advanced computing technology and expertise at the Texas Advanced Computing Center of the University of Texas at Austin. TACC science writer Jorge Salazar hosts Supersized Science. Supersized Science is part of the Texas Podcast Network, brought to you by The University of Texas at Austin. Podcasts are produced by faculty members and staffers at UT Austin who work with University Communications to craft content that adheres to journalistic best practices. The University of Texas at Austin offers these podcasts at no charge. Podcasts appearing on the network and this webpage represent the views of the hosts and not of The University of Texas at Austin.
02-12-2016
Podcast host Jorge Salazar interviews Sadasivan Shankar, the Margaret and Will Hearst Visiting Lecturer in Computational Science and Engineering at the John A. Paulson School of Engineering and Applied Sciences at Harvard University.
Computers hardware speeds have grown exponentially for the past 50 years. We call this Moore's Law. But we haven't seen a Moore's Law for software. That's according to Sadasivan Shankar of Harvard University. He said that the reason for that is a lack of communication and close collaboration between hardware developers and the users trying to solve problems in fields like social networking, cancer modeling, personalized medicine, or designing the next generation battery for electrical storage.
Dr. Shankar proposes a new paradigm in which the software applications should be part of the design of new computer architectures. He calls this paradigm Co-Design 3.0. Shankar was invited to speak about it at the SC16 conference.
Sadasivan Shankar: We want to see what will make high performance computing personalizable. How can we train the upcoming workforce on different aspects of all the components, the architecture, hardware, algorithms, and software? This is why I think universities play an important role in this, as much as the national labs have been playing on high performance computing. We want to be able to solve the real problems – cancer cures, personalized medicine, new battery materials, new catalysts, eliminate toxic materials. Both research and development are needed to enable this paradigm. Can we essentially do them faster and economically? The computing has brought us very far. But can we take it even farther? That's the question that we should ask ourselves.
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Filetype: MP3 - Size: 29.64MB - Duration: 21:19 m (192 kbps 44100 Hz)
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