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The nonlinear implicit mapping provided by the kernel operation allows us to generate an inner product in the feature space by computing a kernel function that has arguments taken from the input space.
The third level corresponds to a kernel of the algorithm; each kernel operation is implemented on a single SPE within its local store as a sequence of micro-kernel operations.
A prototype approach to leverage the bandwidth and computing power of GPUs for these matrix kernel operation is demonstrated resulting in an overall performance of over 110 GFlops/s on the desktop for large matrices and over 38 GFlops/s for sparse matrices arising in real applications.
The kernel operation yielding the maximum response for a given pixel determined the gradient direction.
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It requires matrix and kernel operations at the same time than multi-node communication management.
The classes encapsulate a subset of the OpenCL and CUDA functions for creating device contexts, memory buffers (including functions to copy data) and kernel operations (loading, compiling, launching).
Given an application, the designer is responsible to properly partition the kernel operations onto the PE components and to explore the data flows among them.
Each macro-kernel operation is implemented within the local store of an SPE core.
A sorting network accelerated the kernel sorting operation at low hardware cost by utilizing the special characteristics of MA4.
The feature set comprising of prediction error, difference between the median value and the center pixel; the median value in the kernel under operation has been used during this study.
In this paper, we propose a partitioning and gating technique for the design of a high performance and low-power multiplier for kernel-based operations such as 2D convolution in video processing applications.
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