Formalization of Phase Ordering

Phasers pose an interesting synchronization mechanism that generalizes many collective synchronization patterns seen in parallel programming languages, including barriers, clocks, and point-to-point synchronization using latches or semaphores. This work characterizes scheduling constraints on phaser operations, by relating the execution state of two tasks that operate on the same phaser. We propose a formalization of Habanero phasers, May-Happen-In-Parallel, and Happens-Before relations for phaser operations, and show that these relations conform with the semantics. Our formalization and proofs are fully mechanized using the Coq proof assistant, and are available online.Comment: In Proceedings PLACES 2016, arXiv:1606.0540

Deterministic Consistency: A Programming Model for Shared Memory Parallelism

The difficulty of developing reliable parallel software is generating interest in deterministic environments, where a given program and input can yield only one possible result. Languages or type systems can enforce determinism in new code, and runtime systems can impose synthetic schedules on legacy parallel code. To parallelize existing serial code, however, we would like a programming model that is naturally deterministic without language restrictions or artificial scheduling. We propose "deterministic consistency", a parallel programming model as easy to understand as the "parallel assignment" construct in sequential languages such as Perl and JavaScript, where concurrent threads always read their inputs before writing shared outputs. DC supports common data- and task-parallel synchronization abstractions such as fork/join and barriers, as well as non-hierarchical structures such as producer/consumer pipelines and futures. A preliminary prototype suggests that software-only implementations of DC can run applications written for popular parallel environments such as OpenMP with low (<10%) overhead for some applications.Comment: 7 pages, 3 figure

Communicating Java Threads

The incorporation of multithreading in Java may be considered a significant part of the Java language, because it provides udimentary facilities for concurrent programming. However, we belief that the use of channels is a fundamental concept for concurrent programming. The channel approach as described in this paper is a realization of a systematic design method for concurrent programming in Java based on the CSP paradigm. CSP requires the availability of a Channel class and the addition of composition constructs for sequential, parallel and alternative processes. The Channel class and the constructs have been implemented in Java in compliance with the definitions in CSP. As a result, implementing communication between processes is facilitated, enabling the programmer to avoid deadlock more easily, and freeing the programmer from synchronization and scheduling constructs. The use of the Channel class and the additional constructs is illustrated in a simple application

Contract-Based General-Purpose GPU Programming

Using GPUs as general-purpose processors has revolutionized parallel computing by offering, for a large and growing set of algorithms, massive data-parallelization on desktop machines. An obstacle to widespread adoption, however, is the difficulty of programming them and the low-level control of the hardware required to achieve good performance. This paper suggests a programming library, SafeGPU, that aims at striking a balance between programmer productivity and performance, by making GPU data-parallel operations accessible from within a classical object-oriented programming language. The solution is integrated with the design-by-contract approach, which increases confidence in functional program correctness by embedding executable program specifications into the program text. We show that our library leads to modular and maintainable code that is accessible to GPGPU non-experts, while providing performance that is comparable with hand-written CUDA code. Furthermore, runtime contract checking turns out to be feasible, as the contracts can be executed on the GPU