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X10 is a modern object-oriented programming language designed for high performance, high productivity programming of parallel and multi-core computer systems. Compared to the lower-level thread-based concurrency model in the Java TM language, X10 has higher-level concurrency constructs such as async, atomic and finish built into the language to simplify creation, analysis and optimization of parallel programs. In this paper, we introduce a new algorithm for May-Happen-in-Parallel (MHP) analysis of X10 programs. The analysis algorithm is based on simple path traversals in the Program Structure Tree, and does not rely on pointer alias analysis of thread objects as in MHP analysis for Java programs. We introduce a more precise definition of the MHP relation than in past work by adding condition vectors that identify execution instances for which the MHP relation holds, instead of just returning a single true/false value for all pairs of executing instances. Further, MHP analysis is refined in our approach by using the observation that two statement instances which occur in atomic sections that execute at the same X10 place must have MHP = false. We expect that our MHP analysis algorithm will be applicable to any language that adopts the core concepts of places, async, finish, and atomic sections from the X10 programming model. We also believe that this approach offers the best of two worlds to programmers and parallel programming tools -higher-level abstractions of concurrency coupled with simple and efficient analysis algorithms.

Abstract. In this paper, we extend past work on Linear Scan register allocation, and propose two Extended Linear Scan (ELS) algorithms that retain the compiletime efficiency of past Linear Scan algorithms while delivering performance that can match or surpass that of Graph Coloring. Specifically, this paper makes the following contributions:-We highlight three fundamental theoretical limitations in using Graph Coloring as a foundation for global register allocation, and introduce a basic Extended Linear Scan algorithm, ELS 0 , which addresses all three limitations for the problem of Spill-Free Register Allocation. -We introduce the ELS 1 algorithm which extends ELS 0 to obtain a greedy algorithm for the problem of Register Allocation with Total Spills. -Finally, we present experimental results to compare the Graph Coloring and Extended Linear Scan algorithms. Our results show that the compile-time speedups for ELS 1 relative to GC were significant, and varied from 15× to 68×. In addition, the resulting execution time improved by up to 5.8%, with an average improvement of 2.3%.Together, these results show that Extended Linear Scan is promising as an alternate foundation for global register allocation, compared to Graph Coloring, due to its compile-time scalability without loss of execution time performance.

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Multiple programming models are emerging to address an increased need for dynamic task parallelism in multicore sharedmemory multiprocessors. This poster describes the main components of Rice University's Habanero Multicore Software Research Project, which proposes a new approach to multicore software enablement based on a two-level programming model consisting of a higher-level coordination language for domain experts and a lowerlevel parallel language for programming experts.