Titlebook: High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation; 4th International Wo Stephen A. Jarvis,Steven A. Wri

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Performance Evaluation of the Intel Sandy Bridge Based NASA Pleiades Using Scientific and Engineerinnd compare it with the previous third generation Nehalem architecture. Several architectural features have been incorporated in Sandy Bridge: (a) four memory channels as opposed to three in Nehalem; (b) memory speed increased from 1333 MHz to 1600 MHz; (c) ring to connect on-chip L3 cache with cores

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Analysis of Data Reuse in Task-Parallel Runtimese method called . Reuse Distance (KRD). The metric is a low-overhead alternative designed to analyze data reuse at the socket level while minimizing perturbation to the parallel schedule. Using the KRD metric we show that reuse depends considerably on the system configuration (sockets, cores) and on

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Performance Modeling of Gyrokinetic Toroidal Simulations for a Many-Tasking Runtime Systemiency and scalability for many algorithms in scientific computing. One possible solution for improving efficiency and scalability in applications on this class of machines is the use of a many-tasking runtime system employing many lightweight, concurrent threads. Yet a priori estimation of the poten

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Toward Better Simulation of MPI Applications on Ethernet/TCP Networksxt-generation exascale systems, and correctly modeling network behavior is essential for creating realistic simulations. In this article we describe an implementation of a flow-based hybrid network model that accounts for factors such as network topology and contention, which are commonly ignored by

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SESH Framework: A Space Exploration Framework for GPU Application and Hardware Codesignptive architecture and a variety of optimization options, it is often desirable to understand the dynamics between . application transformations and . hardware features when designing future GPUs for scientific workloads. However, current codesign efforts have been limited to manual investigation of

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Optimal Checkpointing Period: Time vs. Energyde a model and detailed formulas for total execution time and consumed energy. We characterize the optimal period for both objectives, and we assess the range of time/energy trade-offs to be made?by instantiating the model with a set of realistic scenarios for Exascale systems. We give a particular

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