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Demand is mounting in the industry for scalable GPU-based deep learning systems. Unfortunately, existing training applications built atop popular deep learning frameworks, including Caffe, Theano, and Torch, etc, are incapable of conducting distributed GPU training over large-scale clusters.To remedy such a situation, this paper presents Nexus, a platform that allows existing deep learning frameworks...
The recent adoption of OpenCL programming model by FPGA vendors has realized the function portability of OpenCL workloads on FPGA. However, the poor performance portability prevents its wide adoption. To harness the power of FPGAs using OpenCL programming model, it is advantageous to design an analytical performance model to estimate the performance of OpenCL workloads on FPGAs and provide insights...
We extend and optimize the axisymmetric 2.5-D eigensolver to calculate the far-field results of axisymmetric structures in stratified backgrounds (SBs), which is useful and practical for optical design and engineering. Two kinds of near-field-to-far-field transformations (NFFFTs) are proposed. One is called closed-surface transformation which is based on the dipole radiations in SBs. The other is...
According to Moore's law the complexity of VLSI circuits has doubled approximately every two years, resulting in simulation becoming the major bottleneck in the circuit design process. Parallel and distributed simulations can be applied as fast, cost effective approaches to the simulation of large, complex circuits. In this paper, a simple yet effective simulated annealing-based approach is proposed...
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