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A new concept on the control kernel of an application is also introduced and some conclusions are drafted.
The new concept of the control kernel of an application is introduced, making easier the design of general purpose applications.
In this paper, we investigate on two approaches: a novel profiling-based adaptive kernel mapping algorithm to assign each kernel of an application to the proper device, and a Mixed-Integer Programming (MIP) implementation to determine optimal mapping.
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The DATE system can be effectively used for expanding individual kernels of an application and also for the generation of interfaces between various kernels to implement a complete system architecture.
The implementation of the presented solution is based on open technologies whereby the kernel of the application is formed by SciLab/Xcos environment.
The parallel sections of an application are executed as kernels in a SIMD (single instruction multiple data) fashion, that is, with all threads running the same code.
A specifically designed kernel is expressed as an application of the well-known Gaussian kernel via feature spaces defined for our problem.
This results in a kernel speedup of six and an application speedup of 3.3 on a single compute node.
To do that, specific algorithms for finding the data shared among the different computation kernels of the application have been developed.
That might be the kernel of a solution.
A kernel of a fascinating play is here.
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