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Smart-grid development calls for effective solutions, such as electric vehicles (EVs), to meet the energy and environmental challenges. To facilitate large-scale EV applications, optimal locating and sizing of charging stations in smart grids have become essential. This paper proposes a multiobjective EV charging station planning method which can ensure charging service while reducing power losses...
Heterogeneous parallel systems have become popular in general purpose computing and even high performance computing fields. There are many studies focused on harnessing heterogeneous parallel processing for better performance. However the energy optimization for heterogeneous system has not been well studied. Owing to the differences in performance and energy consumption, the energy optimization technique...
Although general purpose GPUs have relatively high computing capacity, they also introduce high power consumption compared with general purpose CPUs. Therefore low-power techniques targeted for GPUs will be one of the most hot topics in the future. On the other hand, in several application domains, users are unwilling to sacrifice performance to save power. In this paper, we propose an effective kernel...
Recently, GPGPU has been adopted well in the High Performance Computing (HPC) field. The limited global memory bandwidth poses a great challenge to many GPGPU programmers trying to exploit parallelism within the CPU-GPU heterogeneous platform. In this paper, we choose SWIM, a typical memory intensive application from the SPEC OMP 2001 benchmark suite, for case study. We attempt to optimize the performance...
With fast development of transistor technology, Graphic Processing Unit(GPU) is increasingly used in the non-graphics applications, and major GPU hardware vendors have introduced software stacks for their own GPUs, such as Brook+ for AMD GPU. Compared with the traditional parallel systems, heterogeneous systems integerating stream-based multi-threaded GPUs provide higher parallel computing capabilities...
Graphic Processing Unit (GPU), with many light-weight data-parallel cores, can provide substantial parallel computing power to accelerate several general purpose applications. Both the AMD and NVIDIA corps provide their specific high performance GPUs and software platforms. As the floating-point computing capacity increases continually, the problem of ``memory-wall'' becomes more serious, especially...
Graphic Processing Unit (GPU), with many light-weight data-parallel cores, can provide substantial parallel computational power to accelerate general purpose applications. But the powerful computing capacity could not be fully utilized for memory-intensive applications, which are limited by off-chip memory bandwidth and latency. Stencil computation has abundant parallelism and low computational intensity...
Stream processors, developed for the stream programming model, perform well on media applications. In this paper we examine the applicability of a stream processor to scientific computing applications. Eight scientific applications, each having different performance characteristics, are mapped to a stream processor. Due to the novelty of the stream programming model, we show how to map programs in...
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