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The sparse matrix-vector multiplication (SpMV) is a fundamental kernel used in computational science.
Maximum weighted matchings represent a fundamental kernel in massive graph analysis and occur in a wide range of real-life applications.
In this article, we present two case studies to illustrate the design and implementation of parallel combinatorial algorithms on Cell/B.E.: we discuss list ranking, a fundamental kernel for graph problems, and zlib, a data compression and decompression library.
Under the limitation of a 2D disk, we specifically represent the force as a double summation of a convolution of the surface density and a fundamental kernel and employ a fast Fourier transform technique.
The limit process involved is complex because of appearance of a "boundary layer" in the limiting case considered; this boundary layer occurs near the origin in the Fourier space used to determine the unknown components of the fundamental kernel looked for.
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Discrete transforms are of primary importance and fundamental kernels in many computationally intensive scientific applications.
u lk * and P lk * represent the fundamental kernels for displacements and tractions, respectively (Portela et al. 1992).
While there exist early attempts to tackle this problem, for example via ad-hoc strategies embedded in a runtime framework, in this paper we take a different path, which consists in addressing the asymmetry at the library-level by developing a few asymmetry-aware fundamental kernels.
Sparse matrix-vector multiplication (SpMV) is a fundamental computational kernel used in scientific and engineering applications.
We report on our experience with integrating and using graphics processing units (GPUs) as fast parallel floating-point co-processors to accelerate two fundamental computational scientific kernels on the GPU: sparse direct factorization and nonlinear interior-point optimization.
This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families.
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