Computer Architecture Podcast

• Ep 19: Arkaprava Basu - Memory Management and Software Reliability with Dr. Arkaprava Basu, Indian Institute of Science

  Dr. Arkaprava Basu is an Associate Professor at the Indian Institute of Science, where he mentors students in the Computer Systems Lab. Arka's research focuses on pushing the boundaries of memory management and software reliability for both CPUs and GPUs. His work spans diverse areas, from optimizing memory systems for chiplet-based GPUs to developing innovative techniques to eliminate synchronization bottlenecks in GPU programs. He is also a recipient of the Intel Rising Star Faculty Award, ACM India Early Career Award,  and multiple other accolades, recognizing his innovative approaches to enhancing GPU performance, programmability, and reliability.

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• Ep 18: Codesign for Industrial Robotics and the Startup Pivot with Dr. Dan Sorin, Duke University

  Dr. Dan Sorin is a Professor of Electrical and Computer Engineering at Duke University, and a co-founder of Realtime Robotics. Dan is widely known for his pioneering work in memory systems. He has co-authored the seminal Primer on Memory Consistency and Cache Coherence, which has become a foundational resource for students and researchers alike. Dan’s contributions span from developing resilient systems that tolerate hardware faults to innovations in cache coherence protocols, and has been recognized by multiple best paper awards and patents. His work at Realtime Robotics has pushed the boundaries of autonomous motion planning, enabling real-time decision-making in dynamic environments.

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• Ep 17: Architecture 2.0 and AI for Computer Systems Design with Dr. Vijay Janapa Reddi, Harvard University

  Dr. Vijay Janapa Reddi is an Associate Professor at Harvard University, and Vice President and Co-founder of MLCommons. He has made substantial contributions to mobile and edge computing systems, and played a key role in developing the MLPerf Benchmarks. Vijay has authored the machine learning systems book mlsysbook.ai, as part of his twin passions of education and outreach. He received the IEEE TCCA Young Computer Architect Award in 2016, has been inducted in the MICRO and HPCA Halls of Fame, and is a recipient of multiple best paper awards. 

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• Ep 16: Sustainability in a Post-AI World with Dr. Carole-Jean Wu, Meta

  Dr. Carole-Jean Wu is a Director of AI Research at Meta. She is a founding member and a Vice President of MLCommons – a non-profit organization that aims to accelerate machine learning innovations for the benefits of all. Dr. Wu also serves on the MLCommons Board as a Director, chaired the MLPerf Recommendation Benchmark Advisory Board, and co-chaired for MLPerf Inference. Prior to Meta/Facebook, Dr. Wu was a professor at ASU. She earned her M.A. and Ph.D. degrees in Electrical Engineering from Princeton University and a B.Sc. degree in Electrical and Computer Engineering from Cornell University.  Dr. Wu’s expertise sits at the intersection of computer architecture and machine learning. Her work spans across datacenter infrastructures and edge systems, such as developing energy- and memory-efficient systems and microarchitectures, optimizing systems for machine learning execution at-scale, and designing learning-based approaches for system design and optimization. She is passionate about pathfinding and tackling system challenges to enable efficient and responsible AI technologies.

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• Ep 15: The Hardware Startup Experience from Business Case to Software with Dr. Karu Sankaralingam, University of Wisconsin-Madison/Nvidia

  Dr. Karu Sankaralingam is a Professor at the University of Wisconsin-Madison, an entrepeneur, inventor, as well as a Principal Research Scientist at NVIDIA.  His work has been featured in industry forums of Mentor and Synopsys, and has been covered by the New York Times, Wired, and IEEE Spectrum. He founded the hardware startup SimpleMachines in 2017 which developed chip designs applying dataflow computing to push the limits of AI generality in hardware and built the Mozart chip. In his career, he has led three chip projects: Mozart (16nm, HBM2 based design), MIAOW open source GPU on FPGA, and the TRIPS chip as a student during his PhD. In his research he has pioneered the principles of dataflow computing, focusing on the role of architecture, microarchitecture and the compiler. He has published over 100 research papers, has graduated 9 PhD students, is an inventor on 21 patents, and 9 award papers. He is a Fellow of IEEE.

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