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• W1540412851 abstract "The gap between a supercomputer's theoretical maximum (peak) oatingpointperformance and that actually achieved by applications has grown widerover time. Today, a typical scientific application achieves only 5{20% of anygiven machine's peak processing capability, and this gap leaves room for significantimprovements in execution times.This problem is most pronounced for modern accelerator architectures{ collections of hundreds of simple, low-clocked cores capable of executing thesame instruction on dozens of pieces of data simultaneously. This is a significantchange from the low number of high-clocked cores found in traditional CPUs,and effective utilisation of accelerators typically requires extensive code andalgorithmic changes. In many cases, the best way in which to map a parallelworkload to these new architectures is unclear.The principle focus of the work presented in this thesis is the evaluationof emerging parallel architectures (specifically, modern CPUs, GPUs and IntelMIC) for two benchmark codes { the LU benchmark from the NAS ParallelBenchmark Suite and Sandia's miniMD benchmark { which exhibit complexparallel behaviours that are representative of many scientific applications. Usingcombinations of low-level intrinsic functions, OpenMP, CUDA and MPI, wedemonstrate performance improvements of up to 7x for these workloads.We also detail a code development methodology that permits application developersto target multiple architecture types without maintaining completelyseparate implementations for each platform. Using OpenCL, we develop performanceportable implementations of the LU and miniMD benchmarks that arefaster than the original codes, and at most 2x slower than versions highly-tunedfor particular hardware.Finally, we demonstrate the importance of evaluating architectures at scale(as opposed to on single nodes) through performance modelling techniques,highlighting the problems associated with strong-scaling on emerging acceleratorarchitectures." @default.
• W1540412851 created "2016-06-24" @default.
• W1540412851 creator A5077643825 @default.
• W1540412851 date "2012-12-31" @default.
• W1540412851 modified "2023-09-24" @default.
• W1540412851 title "Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures" @default.
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