247 research outputs found
The future of computing beyond Moore's Law.
Moore's Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon lithography have enabled this exponential miniaturization of electronics, but, as transistors reach atomic scale and fabrication costs continue to rise, the classical technological driver that has underpinned Moore's Law for 50 years is failing and is anticipated to flatten by 2025. This article provides an updated view of what a post-exascale system will look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also discusses the tapering of historical improvements, and how it affects options available to continue scaling of successors to the first exascale machine. Lastly, this article covers the many different opportunities and strategies available to continue computing performance improvements in the absence of historical technology drivers. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'
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GridRun: A lightweight packaging and execution environment forcompact, multi-architecture binaries
GridRun offers a very simple set of tools for creating and executing multi-platform binary executables. These ''fat-binaries'' archive native machine code into compact packages that are typically a fraction the size of the original binary images they store, enabling efficient staging of executables for heterogeneous parallel jobs. GridRun interoperates with existing distributed job launchers/managers like Condor and the Globus GRAM to greatly simplify the logic required launching native binary applications in distributed heterogeneous environments
GridRun: A lightweight packaging and execution environment for compact, multi-architecture binaries
Abstrac
SimpleSSD: Modeling Solid State Drives for Holistic System Simulation
Existing solid state drive (SSD) simulators unfortunately lack hardware
and/or software architecture models. Consequently, they are far from capturing
the critical features of contemporary SSD devices. More importantly, while the
performance of modern systems that adopt SSDs can vary based on their numerous
internal design parameters and storage-level configurations, a full system
simulation with traditional SSD models often requires unreasonably long
runtimes and excessive computational resources. In this work, we propose
SimpleSSD, a highfidelity simulator that models all detailed characteristics of
hardware and software, while simplifying the nondescript features of storage
internals. In contrast to existing SSD simulators, SimpleSSD can easily be
integrated into publicly-available full system simulators. In addition, it can
accommodate a complete storage stack and evaluate the performance of SSDs along
with diverse memory technologies and microarchitectures. Thus, it facilitates
simulations that explore the full design space at different levels of system
abstraction.Comment: This paper has been accepted at IEEE Computer Architecture Letters
(CAL
Performance Evaluation of Plasma and Astrophysics Applications on Modern Parallel Vector Systems
Abstract. The last decade has witnessed a rapid proliferation of superscalar cache-based microprocessors to build high-end computing (HEC) platforms, primarily because of their generality, scalability, and cost effectiveness. However, the growing gap between sustained and peak performance for full-scale scientific applications on such platforms has become major concern in high performance computing. The latest generation of custom-built parallel vector systems have the potential to address this concern for numerical algorithms with sufficient regularity in their computational structure. In this work, we explore two and three dimensional implementations of a plasma physics application, as well as a leading astrophysics package on some of today's most powerful supercomputing platforms. Results compare performance between the the vector-based Cray X1, Earth Simulator, and newly-released NEC SX-8, with the commodity-based superscalar platforms of the IBM Power3, Intel Itanium2, and AMD Opteron. Overall results show that the SX-8 attains unprecedented aggregate performance across our evaluated applications
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Towards Ultra-High Resolution Models of Climate and Weather
We present a speculative extrapolation of the performance aspects of an atmospheric general circulation model to ultra-high resolution and describe alternative technological paths to realize integration of such a model in the relatively near future. Due to a superlinear scaling of the computational burden dictated by stability criterion, the solution of the equations of motion dominate the calculation at ultra-high resolutions. From this extrapolation, it is estimated that a credible kilometer scale atmospheric model would require at least a sustained ten petaflop computer to provide scientifically useful climate simulations. Our design study portends an alternate strategy for practical power-efficient implementations of petaflop scale systems. Embedded processor technology could be exploited to tailor a custom machine designed to ultra-high climate model specifications at relatively affordable cost and power considerations. The major conceptual changes required by a kilometer scale climate model are certain to be difficult to implement. Although the hardware, software, and algorithms are all equally critical in conducting ultra-high climate resolution studies, it is likely that the necessary petaflop computing technology will be available in advance of a credible kilometer scale climate model
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Performance Evaluation of Plasma and Astrophysics Applications onModern Parallel Vector Systems
The last decade has witnessed a rapid proliferation ofsuperscalar cache-based microprocessors to build high-endcomputing (HEC)platforms, primarily because of their generality,scalability, and costeffectiveness. However, the growing gap between sustained and peakperformance for full-scale scientific applications on such platforms hasbecome major concern in highperformance computing. The latest generationof custom-built parallel vector systems have the potential to addressthis concern for numerical algorithms with sufficient regularity in theircomputational structure. In this work, we explore two and threedimensional implementations of a plasma physics application, as well as aleading astrophysics package on some of today's most powerfulsupercomputing platforms. Results compare performance between the thevector-based Cray X1, EarthSimulator, and newly-released NEC SX- 8, withthe commodity-based superscalar platforms of the IBM Power3, IntelItanium2, and AMDOpteron. Overall results show that the SX-8 attainsunprecedented aggregate performance across our evaluatedapplications
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NERSC-6 Workload Analysis and Benchmark Selection Process
This report describes efforts carried out during early 2008 to determine some of the science drivers for the"NERSC-6" next-generation high-performance computing system acquisition. Although the starting point was existing Greenbooks from DOE and the NERSC User Group, the main contribution of this work is an analysis of the current NERSC computational workload combined with requirements information elicited from key users and other scientists about expected needs in the 2009-2011 timeframe. The NERSC workload is described in terms of science areas, computer codes supporting research within those areas, and description of key algorithms that comprise the codes. This work was carried out in large part to help select a small set of benchmark programs that accurately capture the science and algorithmic characteristics of the workload. The report concludes with a description of the codes selected and some preliminary performance data for them on several important systems
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