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In this paper, we introduce the architecture of Phi Coprocessor, programming techniques and acceleration techniques in the finite different time domain (FDTD) methods. Phi Coprocessor can be used as a regular CPU and run the EM code optimized for regular CPUs such as Intel Xeon E5 or AMD Opteron 6300 with slight code modifications. The examples will be for the acceleration of the parallel FDTD methods.
The utilization of vector-arithmetic logic units is a promising way to speed up FDTD computations from the viewpoint of hardware acceleration. This paper studies how a streaming SIMD extensions (SSE) implementation can be effi ciently developed, and the situation where SSE is benefi cial for FDTD computations.
Sparse coding has high-performance encoding and ability to express images, sparse encoding basis vector plays a crucial role. The computational complexity of the most existing sparse coding basis vectors of is relatively large. In order to reduce the computational complexity and save the time to train basis vectors. A new Hebbian rules based method for computation of sparse coding basis vectors is...
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