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The booklet provides the cutting-edge in excessive functionality computing and simulation on sleek supercomputer architectures. It covers developments in and software program improvement normally and in particular the way forward for vector-based structures and heterogeneous architectures. the applying contributions hide computational fluid dynamics, fabric technological know-how, scientific purposes and weather learn. leading edge fields like coupled multi-physics or multi-scale simulations are provided. All papers have been selected from displays given on the thirteenth Teraflop Workshop held in October 2010 at Tohoku collage, Japan.
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Extra resources for High Performance Computing on Vector Systems 2011
5 gives concluding remarks of this paper. 2 OpenCL OpenCL is a new programming standard for heterogeneous computing of different processors . Using OpenCL, a programmer can access various processors in a unified way. OpenCL assumes that a CPU works as a host to control a compute device such as a GPU. A Prototype Implementation of OpenCL for SX Vector Systems 43 A host and a compute device have their own memory spaces, which are host memory and device memory, respectively. A typical OpenCL application running on a host first initializes a compute device, allocates device memory chunks, copies host memory data to the allocated chunks, invokes a special “kernel” function to process the device memory data, and retrieves the computation results from the device memory.
Technol. 2, 20–31 (1994) 16. : The ghost in the machine: observing the effects of kernel operation on parallel application performance. In: Proceedings of the 2007 ACM/IEEE conference on Supercomputing, SC ’07, pp. 29:1–29:12. ACM, New York, NY, USA (2007) 17. : The case of the missing supercomputer performance: Achieving optimal performance on the 8,192 processors of ASCI Q. In: Proceedings of the 2003 ACM/IEEE conference on Supercomputing, SC ’03, pp. 55. ACM, New York, NY, USA (2003) 18. : Analysis of microbenchmarks for performance tuning of clusters.
24 J. Moˇcnik et al. A fixed amount of computation takes a fixed amount of time in complete absence of noise, as all the CPU cycles are strictly dedicated to execution of the computation alone. In presence of noise, however, the amount of time required to finish computation varies in time, depending on the amount of system activities that were executed while the computation was being performed. Noise can thus be defined as the variance of time required to perform a constant amount of computation or variance of “useful” computation performed in a fixed time interval.