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Register a new userGrid: A next generation data parallel C++ QCD library
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Added by
Peter Boyle
Publication date
2015
fields
Informatics Engineering
and research's language is
English
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In this proceedings we discuss the motivation, implementation details, and performance of a new physics code base called Grid. It is intended to be more performant, more general, but similar in spirit to QDP++cite{QDP}. Our approach is to engineer the basic type system to be consistently fast, rather than bolt on a few optimised routines, and we are attempt to write all our optimised routines directly in the Grid framework. It is hoped this will deliver best known practice performance across the next generation of supercomputers, which will provide programming challenges to traditional scalar codes. We illustrate the programming patterns used to implement our goals, and advances in productivity that have been enabled by using new features in C++11.
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Understanding the earths climate system and how it might be changing is a preeminent scientific challenge. Global climate models are used to simulate past, present, and future climates, and experiments are executed continuously on an array of distributed supercomputers. The resulting data archive, spread over several sites, currently contains upwards of 100 TB of simulation data and is growing rapidly. Looking toward mid-decade and beyond, we must anticipate and prepare for distributed climate research data holdings of many petabytes. The Earth System Grid (ESG) is a collaborative interdisciplinary project aimed at addressing the challenge of enabling management, discovery, access, and analysis of these critically important datasets in a distributed and heterogeneous computational environment. The problem is fundamentally a Grid problem. Building upon the Globus toolkit and a variety of other technologies, ESG is developing an environment that addresses authentication, authorization for data access, large-scale data transport and management, services and abstractions for high-performance remote data access, mechanisms for scalable data replication, cataloging with rich semantic and syntactic information, data discovery, distributed monitoring, and Web-based portals for using the system.
Motivated by the computational demands of our research and budgetary constraints which are common to many research institutions, we built a ``poor mans supercomputer, a cluster of PC nodes which together can perform parallel calculations at a fraction of the price of a commercial supercomputer. We describe the construction, cost, and performance of our cluster.
QPACE is a novel parallel computer which has been developed to be primarily used for lattice QCD simulations. The compute power is provided by the IBM PowerXCell 8i processor, an enhanced version of the Cell processor that is used in the Playstation 3. The QPACE nodes are interconnected by a custom, application optimized 3-dimensional torus network implemented on an FPGA. To achieve the very high packaging density of 26 TFlops per rack a new water cooling concept has been developed and successfully realized. In this paper we give an overview of the architecture and highlight some important technical details of the system. Furthermore, we provide initial performance results and report on the installation of 8 QPACE racks providing an aggregate peak performance of 200 TFlops.
We consider the implementation of a parallel Monte Carlo code for high-performance simulations on PC clusters with MPI. We carry out tests of speedup and efficiency. The code is used for numerical simulations of pure SU(2) lattice gauge theory at very large lattice volumes, in order to study the infrared behavior of gluon and ghost propagators. This problem is directly related to the confinement of quarks and gluons in the physics of strong interactions.
We present the International Lattice Data Grid (ILDG), a loosely federated grid of grids for sharing data from Lattice Quantum Chromodynamics (LQCD) simulations. The ILDG comprises of metadata, file format and web-service standards, which can be used to wrap regional data-grid interfaces, allowing seamless access to catalogues and data in a diverse set of collaborating regional grids. We discuss the technological underpinnings of the ILDG, primarily the metadata and the middleware, and offer a critique of its various aspects with the hindsight of the design work and the first full year of production.
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