Wen-mei Hwu Receives the ACM-IEEE CS Eckert-Mauchly Award
ACM and the IEEE Computer Society have named Wen-mei Hwu, a Senior Distinguished Research Scientist at NVIDIA and Professor Emeritus at the University of Illinois Urbana-Champaign, the recipient of the ACM-IEEE CS Eckert-Mauchly Award.
Hwu is recognised for pioneering and foundational contributions to the design and adoption of multiple generations of processor architectures. His fundamental and pioneering contributions have had a broad impact on three generations of processor architectures: superscalar, VLIW, and throughput-oriented manycore processors (GPUs). Hwu was one of the original architects of the High-Performance Substrate (HPS) model that pioneered superscalar microarchitecture, introducing the concepts of dynamic scheduling, branch prediction, speculative execution, a post-decode cache, and in-order retirement.
The Eckert-Mauchly Award is known as the computer architecture community’s most prestigious award. It is co-sponsored by ACM and the IEEE Computer Society and comes with a $5,000 prize.
ACM ByteCast: Ramón Cáceres
In this episode of ACM ByteCast, Bruke Kifle hosts ACM Fellow Ramón Cáceres, a computer science researcher and software engineer. His areas of focus have included systems and networks, mobile and edge computing, mobility modeling, security, and privacy. Most recently he was at Google, where he built large-scale privacy infrastructure.
Here, Caceres shares how he started in computer engineering but grew more interested in software, and how his strong background in hardware helped throughout his scientific and engineering career. He identifies some of the most significant challenges facing privacy and security and sheds lights on his work with the Google team that developed Zanzibar, Google’s global authorisation system supporting services used by billions of people. In the wide-ranging interview, he also reflects on growing up in the Dominican Republic and later discovering a love of sailing while in Silicon Valley, shares his efforts to bring underrepresented groups into the field of computing, and offers advice for aspiring software engineers.
Featured ACM Member: Fedor Fomin
Fedor V. Fomin is a Professor of Computer Science at the University of Bergen. Within the broad discipline of theoretical computer science, his research interests include graph algorithms, parameterised complexity, algorithmic fairness, algorithmic foundations of machine learning and combinatorial games.
Fomin is a member of the Norwegian Academy of Science and Letters, the Norwegian Academy of Technological Sciences, the Academia Europaea and a Fellow of the European Association for Theoretical Computer Science (EATCS). He was recently named an ACM Fellow for contributions to the development of parameterised complexity and exact exponential algorithms.
In his interview, Fomin discusses receiving the Nerode Prize, bidimensional problems, the algorithmic foundations of machine learning and more.
Featured ACM Member: Shaundra Daily
Shaundra Daily is the Cue Family Professor of the Practice in Electrical and Computer Engineering & Computer Science at Duke University. Her research focuses on designing, implementing, and evaluating technologies, programs and curricula to support inclusive excellence in STEM fields. Daily has garnered over $40M in funding from public and private sources to support her collaborative research activities.
She was recently named a Co-Recipient (along with Nicki Washington) of the ACM Karl V. Karlstrom Outstanding Educator Award. Daily and Washington were cited for their work towards changing the national computing education system to be more equitable and to combat unjust impacts of computing on society.
In her interview, she discusses barriers to DEI, the Alliance for Identity Inclusive Education Program, its key policy goals and more.
Featured ACM Member: Torsten Hoefler
Torsten Hoefler is a Professor at the Swiss Federal Institute of Technology (ETH) Zurich, where he serves as Director of the Scalable Parallel Computing Laboratory. He is also the Chief Architect for Machine Learning at the Swiss National Computing Center and a long-term consultant to Microsoft in areas including large-scale AI and networking. His research interests include performance-centric system design, which includes scalable networks, parallel programming techniques, and performance modeling for large-scale simulations and AI systems.
In his interview, he discusses ETH Zurich’s Scalable Parallel Computing Laboratory, the exascale computer Frontier, MPI and high performance computing, and more.
