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.
In this paper, we address the problem of guaranteeing the absence of physical deadlock in the execution of a parallel program using the async, finish, atomic and place constructs from the X10 language. First, we extend previous work-stealing memory bound results for fully strict multithreaded computations to terminally strict multithreaded computations in which one activity may wait for completion of a descendant activity (as in X10's async and finish constructs), not just an immediate child (as in Cilk's spawn and sync constructs). This result establishes physical deadlock freedom for SMP deployments. Second, we introduce a new class of X10 deployments for clusters, which builds on an underlying Active Message network and the new concept of Doppelgänger mode execution of X10 activities. Third, we use this new class of deployments to establish physical deadlock freedom for deployments on clusters of uniprocessors.Together these results give the user the ability to execute a rich set of programs written with async, finish, atomic and place constructs without worrying about the possibility of physical deadlock due to computation, memory and communication resources. A major open topic for future work is to extend these results to deployments on clusters of SMPs.
The efficient computation of exact abstractions of a concrete program for a given set of predicates is key to the efficiency of Counter-Example Guided Abstraction-Refinement (CEGAR). Recent work propose the use of DPLL-based SMT solvers, modified into enumerators. This technique has been successfully applied in the realm of software, where a control flow graph is available to direct the exploration. However this approach shows some limitations when the number of models grows: in fact, it intrinsically relies on the enumeration of all the implicants, which basically requires the enumerations of all the disjuncts in the DNF of the abstraction.In this paper, we propose a new technique to improve the construction of abstractions. We complement SMT solvers with the use of BDDs, which enables us to avoid the model explosion. Essentially, we exploit the fact that BDDs are a DAG representations of the space that a DPLL-based enumerator treats as a tree. A preliminary experimental evaluation shows the potential of the approach.
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