Vivek Sakar
Rice University

Programming Challenges for Petascale and Multicore Parallel Systems

This decade marks a resurgence for parallel computing with high-end systems moving to petascale and mainstream systems moving to multi-core processors. Unlike previous generations of hardware evolution, this shift will have a major impact on existing software. For petascale, it is widely recognized by application experts that past approaches based on domain decomposition will not scale to exploit the parallelism available in future high-end systems. For multicore, it is acknowledged by hardware vendors that enablement of mainstream software for execution on multiple cores is the major open problem that needs to be solved in support of this hardware trend. These software challenges are further compounded by an increased adoption of high performance computing in new application domains that may not fit the patterns of parallelism that have been studied by the community thus far.

In this talk, we compare and contrast the software stacks that are being developed for petascale and multicore parallel systems, and the challenges that they pose to the programmer. We discuss ongoing work on high productivity languages and tools that can help address these challenges for petascale applications on high-end systems. We also discuss ongoing work on concurrency in virtual machines (managed runtimes) to support lightweight concurrency for mainstream applications on multicore systems. Examples will be give from research projects under way in these areas including PGAS languages (UPC, CAF), Eclipse Parallel Tools Platform, Java Concurrency Utilities, and the X10 language. Finally, we outline a new long-term research project being initiated at Rice University that aims to unify elements of the petascale and multicore software stacks so as to produce portable software that can run unchanged on petascale systems as well as a range of homogeneous and heterogeneous multicore systems.

About Vivek Sarkar
Professor Sarkar conducts research in programming languages, program analysis, compiler optimizations and virtual machines for parallel and high performance computer systems. His past projects include the X10 programming language, the Jikes Research Virtual Machine for the Java language, the ASTI optimizer used in IBM’s XL Fortran product compilers, the PTRAN automatic parallelization system, and profile-directed partitioning and scheduling of Sisal programs. He is in the process of starting up three new research projects at Rice: the Habanero Virtual Machine project for homogeneous & heterogeneous multicore processors, optimization of high-productivity languages for high-end parallel systems, and foundations of program analysis and compilers for parallel software. Professor Sarkar became a member of the IBM Academy of Technology in 1995, an ACM Distinguished Scientist in 2006, and the E.D. Butcher Professor of Computer Science at Rice University in 2007.

Prior to joining Rice University in July 2007, Professor Sarkar was Senior Manager of Programming Technologies at IBM Research. The projects under way in his department at IBM spanned the areas of 1) Programming Models and Language Design: PERCS/X10, XJ/DALI, Collage, 2) Programming Tools: Continuous Software Quality (including SAFE, Security Analysis, Scripting Analysis, WALA), PERCS Parallel Tools (including contributions to Eclipse Parallel Tools Platform), SAFARI, Advanced Refactoring, and 3) Deployment, Optimization and Execution: Metronome, PDS/Mirage, Jikes RVM. His responsibilities at IBM also included leading IBM's research efforts in Programming Model, Tools, and Productivity in the PERCS project during 2002 - 2007 as part of the DARPA-funded program on High Productivity Computing Systems. Professor Sarkar holds a B.Tech. degree from the Indian Institute of Technology, Kanpur, an M.S. degree from University of Wisconsin-Madison, and a Ph.D. from Stanford University. In 1997, he was on sabbatical as a visiting associate professor at MIT, where he was a founding member of the MIT RAW multicore project.