Advancement of parallel systems skeletons

设计模式的思想在并行应用的设计和开发中得到了广泛的研究和应用。在大多数现有的关于并行编程模式的工作中，重点是在应用程序的设计和开发阶段帮助应用程序开发人员。除了模式的传统应用之外，本研究还将模式的使用扩展到(I)并行程序的系统、可靠性和性能特定方面，面向两类用户：应用程序和系统设计人员/开发人员；以及(Ii)在非平凡、实用和有用的并行应用领域提供帮助。更具体地说，拟议的研究侧重于以下系统和可靠性特定方面：(A)容错：容错策略针对不同的模式而有所不同，以将开销降至最低。例如，工人之间没有交互的主-工人模式的容错策略将与工人形成不同的通信子组的场景不同。这就需要对特定于模式的策略进行适当的设计；(B)原子性：因为模式抽象了应用程序的行为需求，所以可以通过使用模式来促进并行程序的原子性需求检查；这需要广泛的研究。在性能方面：(C)在不同的计算环境中，针对不同模式的调度策略不同，以最大限度地减少空闲时间，降低通信成本，从而提高效率。例如，具有独立动态任务的任务场需要与流水线或脉动数组不同地进行调度。因此，设计合适的调度策略对系统的性能至关重要。在重要应用领域：(D)最近正在调查两个这样的应用领域，并将在主要提案中报告。在这些工作中，目标硬件平台是一个商品化的异构并行计算环境，由具有多核CPU的节点和不同架构的GPU通过高速网络互连组成，其中通过合理利用资源来实现效率是一个挑战，而可靠性是所开发的应用程序的要求。

The idea of design patterns has been widely researched and applied in parallel application design and development. In most existing works on patterns in parallel programming, the emphasis is on aiding an application developer during the design and development phases of an application. In addition to the traditional applications of patterns, this proposed research extends the use of patterns towards (i) systems, dependability and performance specific aspects of parallel programs, targeting two categories of users: application and system designers/developers; and (ii) assisting in non-trivial, practical, and useful parallel application domains. More specifically, the proposed research focuses on the following systems and dependability specific aspects: (a) fault-tolerance: fault-tolerance strategies differ for different patterns in order to minimize overhead. For example, fault-tolerance strategy for a master-worker pattern with no interaction among workers will differ from the scenario where workers form distinct communication subgroups. This necessitates proper design of strategies specific to patterns; (b) atomicity: since patterns abstract the behavioral requirements of an application, atomicity requirement checking of parallel programs could be facilitated by the use of patterns; this needs extensive research. From the performance side: (c) scheduling strategies for different patterns differ on a heterogeneous computing environment in order to minimize idling time, reduce communication cost and thus enhance efficiency. For example, a task farm with independent dynamic tasks needs to be scheduled differently from a pipeline or a systolic array. Hence designing of appropriate scheduling strategies is crucial for performance. In the non-trivial applications category: (d) two such application domains are recently being investigated and will be reported in the main proposal. In all of these works, the targeted hardware platform is a commodity heterogeneous parallel computing environment, consisting of nodes with multi-core CPUs and GPUs of dissimilar architectures interconnected via high-speed network, where achieving efficiency through proper utilization of resources is a challenge and dependability is a requirement for the developed application.