• Intelligent Software Systems
• Department of Computer Science
• The University of Texas at Austin

The goal of our research is to build intelligent software systems for automatically enhancing the efficiency and survivability of programs, thereby enabling applications programmers to focus on high-level algorithmic issues. We work in several areas, ranging from restructuring and optimizing compilers to protocols for fault-tolerant computing systems.

Our group is best known for its contributions to automatic parallelism and locality enhancement of programs. These advances are used in software products from Intel, IBM, Hewlett-Packard, Silicon Graphics and Digital Equipment Corporation, among other companies.

We are currently working in the following areas:

• Parallelism for Multicore systems: We are investigating the compiler techniques, runtime support and programming models which will be necessary to make parallel programming more accessible, to take advantage of the increasing prevalence of multicore systems.
• Self-optimizing high-performance library generation: We want to understand how model-driven optimization and AI-based search techniques can be combined in systems for producing self-tuned high-performance libraries.
• Automatic application-level fault tolerance: We are building a pre-compiler and a runtime coordination layer for implementing non-blocking, coordinated, application-level check-pointing of MPI/OpenMP programs.
• Web-services for grid-computing: We are implementing a coupled thermal/mechanical/fluid simulation system that uses web-services based on SOAP and XML for communication and co-ordination.

Recent Publications

• Milind Kulkarni, Martin Burstcher, Calin Cascaval and Keshav Pingali Lonestar: A Suite of Parallel Irregular Programs International Symposium on Performance Analysis of Software and Systems (ISPASS), April, 2009
• Milind Kulkarni, Martin Burtscher, Rajasekhar Inkulu, Keshav Pingali and Calin Cascaval How Much Parallelism is There in Irregular Applications? Principles and Practices of Parallel Programming (PPoPP), February, 2009
• Bruce Walter, Kavita Bala, Milind Kulkarni and Keshav Pingali Fast Agglomerative Clustering for Rendering Symposium on Interactive Ray Tracing (RT), August, 2008
• Martin Burtscher, Milind Kulkarni, Dimitrios Prountzos and Keshav Pingali On the Scalability of an Automatically Parallelized Irregular Application 21st International Workshop on Languages and Compilers for Parallel Computing (LCPC), July, 2008
• Milind Kulkarni, Keshav Pingali, Patrick Carribault, Ganesh Ramanarayanan, Bruce Walter, Kavita Bala and L. Paul Chew Scheduling Strategies for Optimistic Parallel Execution of Irregular Programs 20th Annual ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), June, 2008
• Milind Kulkarni and Keshav Pingali An Experimental Study of Self-Optimizing Dense Linear Algebra Software Proceedings of IEEE [Invited Paper], 96(5):832-848, May 2008
• Milind Kulkarni, Keshav Pingali, Ganesh Ramanarayanan, Bruce Walter, Kavita Bala and L. Paul Chew Optimistic Parallelism Benefits From Data Partitioning Architectural Support for Programming Languages and Operating Systems (ASPLOS), March 2008
• Milind Kulkarni, Keshav Pingali, Bruce Walter, Ganesh Ramanarayanan, Kavita Bala and L. Paul Chew Optimistic Parallelism Requires Abstractions Programming Languages Design and Implementation (PLDI), June 2007
• Kamen Yotov, Tom Roeder, Keshav Pingali, John Gunnels and Fred Gustavson An Experimental Comparison of Cache-oblivious and Cache-aware Programs 19th Annual ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2007
• Greg Bronevetsky, Keshav Pingali and Paul Stodghill Experimental Evaluation of Application-Level Checkpointing for OpenMP Programs 20th ACM International Conference on Supercomputing (ICS), 2006

Our group is supported by NSF grants 0719966, 0702353, 0615240, 0541193, 0509307, 0509324, 0426787 and 0406380, as well as grants from IBM and Intel Corporation.