Rajeev Barua

Funding Agency

National Science Foundation




Accelerating single programs on multicore processors remains an outstanding challenge in computer systems design. Unfortunately, existing parallel systems achieve little speedup on programs other than regular dense-matrix codes. And, most of the world's programs are in this category, broadly termed non-regular code. Of course some non-regular codes have little parallelism beyond instruction level parallelism (ILP); hence no speedup is possible on multicores. However in other non-regular code, parallelism is present but is not exploitable. Reasons include high synchronization costs, non-loop parallelism, non-array data structures, recursively expressed parallelism and parallelism that is too fine-grained to be exploitable.

This project is developing new compiler technologies for XMT to achieve scalable performance in the face of architecture decisions made for scalability. It is studying better compiler techniques to achieve scalable performance for UMA architectures such as XMT.

CSR-PSCE,SM: Compiler-Directed System Optimization of a Highly-Parallel Fine-Grained Chip Multiprocessor is a four-year, $400,000 grant.