HiCOO: همکاری سلسله مراتبی برای ارتباط مقیاس پذیر در مدل های برنامه نویسی فضای آدرس جهانی بر روی سیستم های Cray XT
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|78509||2012||12 صفحه PDF||سفارش دهید||8949 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Parallel and Distributed Computing, Volume 72, Issue 11, November 2012, Pages 1481–1492
Global Address Space (GAS) programming models enable a convenient, shared-memory style addressing model. Typically this is realized through one-sided operations that can enable asynchronous communication and data movement. With the size of petascale systems reaching 10,000s of nodes and 100,000s of cores, the underlying runtime systems face critical challenges in (1) scalably managing resources (such as memory for communication buffers), and (2) gracefully handling unpredictable communication patterns and any associated contention. For any solution that addresses these resource scalability challenges, equally important is the need to maintain the performance of GAS programming models. In this paper, we describe a Hierarchical COOperation (HiCOO) architecture for scalable communication in GAS programming models. HiCOO formulates a cooperative communication architecture: with inter-node cooperation amongst multiple nodes (a.k.a multinode) and hierarchical cooperation among multinodes that are arranged in various virtual topologies. We have implemented HiCOO for a popular GAS runtime library, Aggregate Remote Memory Copy Interface (ARMCI). By extensively evaluating different virtual topologies in HiCOO in terms of their impact to memory scalability, network contention, and application performance, we identify MFCG as the most suitable virtual topology. The resulting HiCOO architecture is able to realize scalable resource management and achieve resilience to network contention, while at the same time maintaining or enhancing the performance of scientific applications. In one case, it reduces the total execution time of an NWChem application by 52%.