L.P.: Optimistic Parallelism Requires Abstractions

The problem of writing software for multicore processors is greatly simplified if we could automatically parallelize sequential programs. Although auto-parallelization has been studied for many decades, it has succeeded only in a few application areas such as dense matrix computations. In particular, auto-parallelization of irregular programs, which are organized around large, pointer-based data struc-tures like graphs, has seemed intractable. The Galois project is taking a fresh look at auto-parallelization. Rather than attempt to parallelize all pro-grams no matter how obscurely they are written, we are designing programming abstractions that permit program-mers to highlight opportunities for exploiting parallelism in sequential programs, and building a runtime syste