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Suppose one is considering purchase of a computer equipped with accelerators. Or suppose one has access to such a computer and is considering porting code to take advantage of the accelerators. Is there a reason to suppose the purchase cost or programmer effort will be worth it? It would be nice to able to estimate the expected improvements in advance of paying money or time. We exhibit an analytical framework and tool-set for providing such estimates: the tools first look for user-defined idioms that are patterns of computation and data access identified in advance as possibly being able to benefit from accelerator hardware. A performance model is then applied to estimate how much faster these idioms would be if they were ported and run on the accelerators, and a recommendation is made as to whether or not each idiom is worth the porting effort to put them on the accelerator and an estimate is provided of what the overall application speedup would be if this were done.As a proof-of-concept we focus our investigations on Gather/Scatter (G/S) operations and means to accelerate these available on the Convey HC-1 which has a special-purpose "personality" for accelerating G/S. We test the methodology on two large-scale HPC applications. The idiom recognizer tool saves weeks of programmer effort compared to having the programmer examine the code visually looking for idioms; performance models save yet more time by rank-ordering the best candidates for porting; and the performance models are accurate, predicting G/S runtime speedup resulting from porting to within 10% of speedup actually achieved. The G/S hardware on the Convey sped up these operations 20x, and the overall impact on total application runtime was to improve it by as much as 21%.

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Virtual organizations (VOs), communities that enable coordinated resource sharing among multiple sites, are becoming more prevalent in the high-performance computing community. In order to promote cross-site resource usability, most VOs prepare service agreements that include a minimum set of common resource functionality, starting with a common software stack and evolving into more complicated service and interoperability agreements. VO service agreements are often difficult to verify and maintain, however, because the sites are dynamic and autonomous. Automated verification of service agreements is critical: manual and user tests are not practical on a large scale.The Inca test harness and reporting framework is a generic system for the automated testing, data collection, verification, and monitoring of service agreements. This paper describes Inca's architecture, system impact, and performance. Inca is being used by the TeraGrid project to verify software installations, monitor service availability, and collect performance data.

The primary goal in the creation of Grids is to provide unified and coherent access to distributed computing, data storage and analysis, instruments, and other resources to advance scientific exploration. Grids combine multiple complex and interdependent systems that span several administrative domains. This complexity poses challenges for both the administrators who build and maintain the Grid resources and the scientists who use them. While other Grid monitoring tools provide system-level information on the utilization of Grid resources, the Inca system provides userlevel Grid monitoring with periodic, automated user-level testing of the software and services required to support Grid operation. Inca can be used by Grid operators, system administrators, and application users to identify, analyze, and troubleshoot user-level Grid failures, thereby improving Grid stability. In this paper, we describe the new features of our current Inca release, Inca 2. We then describe the architecture of the Inca 2 system, in addition to use cases that describe two Inca 2 deployments in production environments.