Ken Kennedy Award

Vivek Sarkar, Georgia Institute of Technology

Winner of the 2020 Award

An ACM Fellow and an IEEE Fellow, Vivek Sarkar is Chair of the School of Computer Science and the Stephen Fleming Chair in the College of Computing at Georgia Institute of Technology. Sarkar started his career in IBM Research in 1987 after obtaining his PhD from Stanford University, which was supervised by John Hennessy. His research projects at IBM include the PTRAN automatic parallelization system led by Fran Allen, the ASTI optimizer for IBM’s XL Fortran product compilers, the open source Jikes Research Virtual Machine for the Java language, and the X10 programming language developed in the DARPA HPCS program. He was a member of the IBM Academy of Technology from 1995-2007.

After moving to academia, Sarkar has mentored over 30 PhD students and postdoctoral researchers in the Habanero Extreme Scale Software Research Laboratory, first at Rice University since 2007, and now at Georgia Tech since 2017. While at Rice, Sarkar was the E. D. Butcher Chair in Engineering, and served as Chair of the Department of Computer Science. Researchers in his lab have developed the Habanero- C/C++ and Habanero-Java programming systems for parallel, heterogeneous, and distributed platforms. These systems introduced new constructs for homogeneous and heterogeneous intra-node parallelism, as well as their integration with scalable inter-node communication libraries.

The Kennedy Award recognizes Sarkar’s leadership in several areas. Sarkar has made foundational technical contributions to programmability and productivity in parallel computing, and has developed innovative programming-model, compiler, and runtime technologies for parallel computing that have influenced other researchers, as well as industry products and standards. Sarkar has led open source software projects that have had significant impact on the research community, he has created new pedagogic materials to make parallel programming more accessible to undergraduate students using the Coursera learner community, and has mentored junior colleagues at IBM and several PhD students after moving to academia. He has also demonstrated leadership in community service by serving as program chair and general chair for major conferences in his research area, serving on US Department of Energy’s Advanced Scientific Computing Advisory Committee (ASCAC) advisory committee since 2009, and on the Computing Research Association (CRA) Board of Directors since 2015.

Geoffrey Fox, Indiana University

Winner of the 2019 Award

Through a long and distinguished career, Fox has made several important technical contributions to high performance computing. Fox identified the principles behind the use of decomposition and efficient message passing in early MIMD (multiple instruction, multiple data) hypercubes., which pioneered application development on parallel machines. In several well-received papers, Fox demonstrated the synergies between Message Passing Interface (MPI) and MapReduce. In one paper, for instance, he introduced the programming model and architecture of Twister, an enhanced map-reduce runtime that supports iterative MapReduce computations efficiently. His more recent Twister 2 system systematically provides HPC performance with functionalities similar to Apache Spark, Flink, Storm, and Heron. His recent work at the interface of HPC and data-intensive computing has resulted in the SPIDAL (Scalable Parallel and Interoperable Data-intensive Application Library) project. SPIDAL supports a very diverse collection of data-intensive applications on high performance computing platforms.

Fox’s service to the community includes involvement with several organizations, including the National Association for Equal Opportunity in Higher Education which identifies research opportunities in computing for the students and staff of minority serving institutions (MSIs). Since 1997, he has also taught Java and parallel computing courses across the internet to historically black colleges and universities and MSIs. Fox’s MOOC (massive online open course), “Big Data Applications,” was cited byComputerworld as one of the “7 Great MOOCs for Techies,” and he has made important contributions to computing standards through leadership roles with the Open Grid Forum and the Java Grande Forum.

Fox has also taken on many volunteer roles, including General Chair, of several conferences and workshops.

Fox is Director of the Digital Science Center and a distinguished professor at Indiana University’s Luddy School of Informatics, Computing, and Engineering. He was principal investigator of FutureGrid, a new cyberinfrastructure test to enable development of new approaches to scientific computing. He has published more than 1,200 publications in physics and computer science. Fox has previously held positions at the California Institute of Technology, Syracuse University, and Florida State University. He received his PhD in Theoretical Physics from Cambridge University.

Sarita Adve, University of Illinois

Winner of the 2018 Award

Sarita Adve co-developed the memory models for the C++ and Java programming languages (with Hans Boehm, Bill Pugh, and others) based on her early work on data-race-free (DRF) models (with Mark Hill). The memory model specifies what value a read of a memory address will return, and lies at the heart of the correctness and performance of threaded programs, languages, compilers, and hardware. By impacting the models of the most widely-used programming languages, Adve’s work has influenced the worldwide software community and hardware design.

More recently, with her students, Johnathan Alsop and Matthew Sinclair, Adve questioned the conventional wisdom of memory models for heterogeneous systems and showed that DRF is a superior model, even for such systems. Her group’s recent work on DRFrlx provides semantics for a large class of relaxed atomics within the DRF framework, a longstanding open problem in the specification of modern memory models.

Adve is also recognized for her service to the computing community. As current chair of the ACM Special Interest Group on Computer Architecture (SIGARCH), she instituted many changes inspiring new energy in the functioning of the executive committee, leading to new effective programs in communications, research visioning, and mentoring. With colleagues, she made diversity and inclusion a key focus and led the creation of CARES, a committee to provide support to those who experienced harassment at SIGARCH- and SIGMICRO-sponsored events. Other communities have begun to emulate these activities. Adve also serves on the DARPA ISAT study group and previously served on the board of the Computing Research Association and the NSF CISE advisory committee.

Sarita Adve is the Richard T. Cheng Professor in the Department of Computer Science at University of Illinois at Urbana-Champaign. Her honors include being named a Woman of Vision in innovation by the Anita Borg Institute for Women in Technology in 2012, an IEEE Fellow in 2012, and an ACM Fellow in 2010. She also received the SIGARCH Maurice Wilkes Award in 2008. For three of the last five years, the University of Illinois has selected her students' PhD theses as one of two nominations for the ACM Doctoral Dissertation Award.

Jesus Labarta, Barcelona Supercomputer Center

Winner of the 2017 Award

Throughout his career, Jesus Labarta has developed tools for scientists and engineers working in parallel programming. In the programming models area, he made fundamental contributions to the concept of asynchronous task-based models and intelligent runtime systems. With Labarta’s approach, by using pragma directives that specify the region of code that constitutes tasks and the directionality of the data used by them, the programmer has a unified mechanism to allow intelligent runtime systems to detect and exploit concurrency as well as to manage locality. These ideas have been developed by Labarta’s team on the OmpSs model and Nanos runtime. His team’s work has also enhanced the interoperability between OmpSs (later Open multi-processing (MP)) and message passing interface (MPI).

In the performance tools area, Labarta’s team develops and distributes Open Source Barcelona Supercomputer Center (BSC) tools that are employed throughout the field. These BSC tools are designed to analyze an application’s behavior and identify issues that may impact performance. Paraver, the most widely used BSC tool, is a trace-based performance analyzer that processes and extracts information. Other tools like Dimemas or the Performance Analytics modules developed by Labarta’s team help squeeze relevant insight and perform predictive analyses from the raw performance data captured by the instrumentation packages.

Labarta is Director of the Computer Science Department at the Barcelona Supercomputing Center and a Professor of Computer Architecture at the Universitat Politècnica de Catalunya. From 1996 to 2004 he served as the Director of the European Center of Parallelism of Barcelona (CEPBA). He has published more than 250 articles in conferences and journals in areas including high performance architectures and systems software. He has been involved in research and cooperation with many leading companies on HPC- related topics. Currently Labarta is the leader of the Performance Optimization and Productivity EU Center of Excellence where more than 100 users (both academic and SMEs) from a very wide range of application sectors receive performance assessments and suggestions for code refactoring efforts.

William Gropp, University of Illinois at Urbana-Champaign

Winner of the 2016 Award

William Gropp was one of the leaders in the development of the Message Passing Interface (MPI) standard. MPI has become the de facto standard for programming distributed-memory computers in scientific applications, and has enabled a wide range of scientists and engineers to use the enormous performance potential of highly parallel computer systems for over two decades. He was a key author in the development of MPI-I, MPI-2, and MPI-3. As part of the standardization process, Gropp also designed and developed MPICH, the first functional implementation of MPI. This freely available software remains one of the most widely used implementations of MPI, with nearly 2,000 downloads per month.

Along with collaborators David Keyes and Xiao-Chuan Cai, Gropp developed and analyzed key scalable parallel algorithms for adaptive mesh refinement and domain decomposition methods, which are now widely used in parallel applications. This work led to the development of a numerical library, the Portable, Extensible Toolkit for Scientific Computation (PETSc), which Gropp developed in collaboration with Barry Smith. PETSc has been used in a variety of applications, including nano-simulations, biology, fusion, geosciences, environmental modeling, fluid dynamics and software engineering, among others.

In bestowing the Ken Kennedy Award, ACM and IEEE also cited Gropp’s outstanding service to the field. In 2011, Gropp helped launch the ACM Special Interest Group for High-Performance Computing (SIGHPC), the first international group devoted to the needs of students, faculty and practitioners in high-performance computing. He also served as the editor of CONNECT, the newsletter for SIGHPC, as chair of the Gordon Bell Prize Committee, and in various capacities for numerous conference committees.

Gropp holds the Thomas M. Siebel Chair of Computer Science at the University of Illinois at Urbana-Champaign. He is also the Acting Director and Chief Scientist of the National Center for Supercomputing Applications. He has authored more than 187 technical publications, including the book Using MPI, which is in its third edition and has sold over 18,000 copies. Gropp received the 2014 SIAM/ACM Prize in Computational Science and Engineering, along with the PETSc Core Development Team (Satish Balay, Jed Brown, Matthew Knepley, Lois Curfman McInnes, Barry Smith and Hong Zhang). He was elected an ACM Fellow, IEEE Fellow, and SIAM Fellow, and is a member of the US National Academy of Engineering.

Katherine Yelick, University of California at Berkeley and Lawrence Berkely National Laboratory

Winner of the 2015 Award

Katherine Yelick, Professor of Electrical Engineering and Computer Sciences at the University of California at Berkeley and the Associate Laboratory Director for Computing Sciences at Lawrence Berkeley National Laboratory, received the 2015 ACM-IEEE Computer Society Ken Kennedy Award for "advancing the programmability of HPC systems, strategic national leadership, and mentorship in academia and government labs." Her research is in programming languages, compilers, parallel algorithms, and automatic performance tuning. She is well known for her work in Partitioned Global Address Space languages, including co-inventing the Unified Parallel C (UPC) and Titanium languages. She and her students developed program analyses and optimization techniques for these languages and the Berkeley Lab team built compiler and runtime support that is used by several other research and production projects. She led the Sparsity project, the first automatically tuned library for sparse matrix kernels, and she co-led the development of the Optimized Sparse Kernel Interface (OSKI). She has worked on interdisciplinary teams developing scientific applications ranging from simulations of chemistry, fusion, and blood flow in the heart to analysis problems in phylogenetics and genome assembly.

Yelick was Director of the National Energy Research Scientific Computing Center (NERSC) from 2008 to 2012 and currently leads the Computing Sciences Area at Berkeley Lab, which includes the NERSC supercomputing center, the Energy Sciences Network (ESnet) and a research division of scientists and engineers in applied math, computer science, data science and computational science. She earned her Ph.D. in Electrical Engineering and Computer Science from MIT and has been a professor at UC Berkeley since 1991 with a joint research appointment at Berkeley Lab since 1996.

Yelick is an ACM Fellow and recent recipient of the ACM-W Athena award. She is a member of the National Academies Computer Science and Telecommunications Board (CSTB), and previously served on the California Council on Science and Technology and the LLNS/LANS Science and Technology Committee overseeing research at Los Alamos and Lawrence Livermore National Laboratories.

Charles E. Leiserson, Massachusetts Institute of Technology

Winner of the 2014 Award

Charles E. Leiserson of Massachusetts Institute of Technology (MIT) received the 2014 ACM-IEEE Computer Society Ken Kennedy Award for "his influence on parallel computing systems and their adoption into mainstream use through scholarly research and development." He was also cited for his mentoring of computer science leaders and students. Leiserson introduced the notion of cache-oblivious algorithms, which can exploit the memory hierarchy near optimally despite having no tuning parameters for cache size or cache-lie length. He also developed the Cilk multithreaded programming technology, and led the development of several Cilk-based parallel chess-playing programs which won numerous prizes in international competition.

The coauthor of “Introduction to Algorithms,” one of computer science’s most cited publications, Leiserson is also the creator of MIT undergraduate courses on algorithms and on discrete mathematics for computer science. He headed the computer science program for the pioneering Singapore-MIT Alliance distanceeducation program and developed MIT’s undergraduate class on software performance engineering, which teaches parallel programming as one of several techniques for writing fast code. Leiserson’s annual workshop on Leadership Skills for Engineering and Science Faculty has educated hundreds of faculty at MIT and around the world in the human issues involved in leading technical teams in academia. He was the founding Workshop Chair for the MIT Undergraduate Practice Opportunities Program (UPOP), which teaches MIT Engineering sophomores how leadership skills can leverage their technical skills in professional environments. He is a Margaret MacVicar Faculty Fellow at MIT, the highest recognition at MIT for undergraduate teaching.

Leiserson’s research centers on the theory of parallel computing, especially as it relates to engineering reality. His PhD thesis, “Area-Efficient VLSI Computation,” won the 1982 ACM Doctoral Dissertation Award, as well as the Fannie and John Hertz Foundation’s Doctoral Thesis Award. A coauthor of the first paper on systolic architectures, Leiserson invented the retiming method of digitalcircuit optimization, and developed the algorithmic theory behind it. On leave from MIT at Thinking Machines Corp., he designed and led the implementation of the network architecture for the Connection Machine Model CM-5 Supercomputer, which incorporated the fat-tree interconnection network he developed at MIT.

As Director of System Architecture at Akamai Technologies, he led the engineering team that developed a worldwide content distribution network numbering over 20,000 servers. He also founded Cilk Arts Inc., which produced the Cilk++ multicore concurrency platform and was acquired by Intel in 2009. Leiserson joined the MIT faculty in 1981, where he heads the Supertech research group in MIT’s Computer Science and Artificial Intelligence Laboratory. He received a BS degree from Yale University and a Ph.D. degree from Carnegie Mellon University. He is an ACM Fellow, a Fellow of the American Association for the Advancement of Science (AAAS), and a Senior Member of IEEE and the Society for Industrial and Applied Mathematics (SIAM).

Earlier this year, he was recognized with an IEEE Computer Society Taylor L. Booth Education Award for his contributions to computer science education. He is also a co-recipient of the 2013 ACM Paris Kanellakis Theory and Practice Award for contributions to efficient and robust parallel and distributed computing.

Jack Dongarra, University of Tennessee Knowxville

Winner of the 2013 Award

Jack Dongarra of University of Tennessee, Knowxville received the 2013 ACM-IEEE Computer Society Ken Kennedy Award for "his influential contributions to mathematical software, performance measurement, and parallel programming, and significant leadership and service within the HPC community." Dongarra’s influence is felt in the many popular software packages on which he has worked and that include the results of his research. Those software packages include the popular LINPACK library, which has served as the benchmark measure for the 500 fastest computers in the world since 1993, as well as more recent software packages that are used to efficiently and effectively solve the complex equations underpinning many applications of interest in the HPC community. He has also developed parallel processing and programming methods that have been critical in increasing the performance of HPC systems.

In addition to his role as a Distinguished Professor at the University of Tennessee, Dongarra is a Senior Research Staff Scientist at Oak Ridge National Laboratory, a Turing Fellow at the University of Manchester, and an Adjunct Professor at Rice University. He is also the Director of the Innovative Computing Laboratory and the Center for Information Technology Research at the University of Tennessee.

As well as being an elected an ACM Fellow in 2001, Dongarra is also an AAAS, IEEE, and SIAM Fellow, and a member of the National Academy of Engineering. In addition, he received the IEEE Sidney Fernbach Award in 2004 for his innovations in HPC; the IEEE Medal of Excellence in Scalable Computing in 2008; the SIAM Special Interest Group on Supercomputing award for his career achievements in 2010; and the IEEE IPDPS Charles Babbage Award in 2011.

After receiving a bachelor’s in Mathematics from Chicago University in 1972, Dongarra pursued a master’s in Computer Science from the Illinois Institute of Technology in 1973. Dongarra received his Ph.D. in Applied Mathematics from the University of New Mexico in 1980.

Mary Lou Soffa, University of Virginia

Winner of the 2012 Award

Mary Lou Soffa received the ACM-IEEE Computer Society Ken Kennedy Award for "her contributions to detecting and managing software security flaws." She developed software tools for debugging and testing programs to eliminate or reduce false alarms and improve operating efficiency. Her research has produced automatic, practical solutions in software engineering, and systems programming languages for improving software reliability, security and productivity. The Kennedy Award citation for Dr. Soffa recognizes her for “contributions to compiler technology and software engineering, exemplary service to the profession, and life-long dedication to mentoring and improving diversity in computing.” She is currently the Owen R. Cheatham Professor at the University of Virginia.

A leading researcher in programming languages, Dr. Soffa provided analytical and experimental models for understanding, predicting, and verifying the optimization of software. In her recent work, she developed a unifying framework for optimizations which included code, optimization, and resources models. Her model-based strategies enabled optimizing compilers to produce higher-quality code, and to employ different paradigms than those previously in use.