2026-04-18T02:04:21Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/1804772024-12-13T09:25:15Zcom_2072_63425com_2072_63424com_2072_63412com_2072_2015col_2072_63426

00925njm 22002777a 4500 dc Gamell Balmanya, Marc author 2012-03-07T15:54:17Z Technological limitations and power constraints are resulting in high-performance parallel computing architectures that are based on large numbers of high-core-count processors. Commercially available processors are now at 8 and 16 cores and experimental platforms, such as the many-core Intel Single-chip Cloud Computer (SCC) platform, provide much higher core counts. These trends are presenting new sets of challenges to HPC applications including programming complexity and the need for extreme energy efficiency.In this work, we first investigate the power behavior of scientific PGAS application kernels on the SCC platform, and explore opportunities and challenges for power management within the PGAS framework. Results obtained via empirical evaluation of Unified Parallel C (UPC) applications on the SCC platform under different constraints, show that, for specific operations, the potential for energy savings in PGAS is large; and power/performance trade-offs can be effectively managed using a cross-layerapproach. We investigate cross-layer power management using PGAS language extensions and runtime mechanisms that manipulate power/performance tradeoffs. Specifically, we present the design, implementation and evaluation of such a middleware for application-aware cross-layer power management of UPC applications on the SCC platform. Finally, based on our observations, we provide a set of recommendations and insights that can be used to support similar power management for PGAS applications on other many-core platforms. En este trabajo se investiga el comportamiento de alimentación de los núcleos de aplicaciones científicas PGAS en la plataforma de SCC y se exploran las oportunidades y desafíos para la administración de energía en el marco PGAS. En aquest treball s'investiga el comportament d'alimentació dels nuclis d'aplicacions científiques PGAS a la plataforma de SCC i s'exploren les oportunitats i desafiaments per a la gestió de l'energia en el marc PGAS. http://hdl.handle.net/10609/11886 PGAS Many-core Intel SCC Unified Parallel C PGAS PGAS Many-core Many-core Intel Intel SCC SCC Unified Parallel C Unified Parallel C Application software -- Development Programari d'aplicació -- Desenvolupament Software de aplicación -- Desarrollo Exploring Cross-layer power management for PGAS applications on the SCC platform