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GPU Acceleration for Hermitian Eigensystems
2013As a recurrent problem in numerical analysis and computational science, eigenvector and eigenvalue determination usually employs high-performance linear algebra libraries. This paper explores the implementation of high-performance routines for the solution of multiple large Hermitian eigenvector and eigenvalue systems on a Graphics Processing Unit (GPU)
Garba, Michael T. +2 more
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Accelerating continuous GRASP with a GPU
The Journal of Supercomputing, 2019This work proposes a GPU-based parallelization for the Continuous GRASP (C-GRASP), a local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints. C-GRASP has demonstrated competitive performance on several well-known multimodal test functions as well as on difficult real-world ...
Bruno C. S. Nogueira +3 more
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Accelerating financial applications on the GPU
Proceedings of the 6th Workshop on General Purpose Processor Using Graphics Processing Units, 2013The QuantLib library is a popular library used for many areas of computational finance. In this work, the parallel processing power of the GPU is used to accelerate QuantLib financial applications. Black-Scholes, Monte-Carlo, Bonds, and Repo code paths in QuantLib are accelerated using hand-written CUDA and OpenCL codes specifically targeted for the ...
Scott Grauer-Gray +3 more
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Acceleration of Word2vec Using GPUs
2016Word2vec is a widely used word embedding toolkit which generates word vectors by training input corpus. Since word vector can represent an exponential number of word cluster and enables reasoning of words with simple algebraic operations, it has become a widely used representation for the subsequent NLP tasks.
Seulki Bae, Youngmin Yi
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Acceleration Techniques for FETI Solvers for GPU Accelerators
2018 International Conference on High Performance Computing & Simulation (HPCS), 2018In this paper we evaluate several approaches to performing simultaneous matrix-vector multiplication of large numbers of matrices on a GPU accelerator. The goal of this evaluation is to develop efficient techniques for massively parallel Hybrid Total FETI solvers in our ESPRESO library. FETI solvers generally use sparse matrices.
Radim Vavrík, Lubomir Riha
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Accelerating sparse Cholesky factorization on GPUs
Parallel Computing, 2014Sparse direct factorization is a critical component of scientific computingGPU acceleration of it is difficult due to algorithmic irregularity and PCIe perf.We present an algorithm for GPU acceleration which resolves these issues.The algorithm shows 2x speedup vs.
Steven C. Rennich +2 more
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DEM–SPH Coupling Method for Landslide Surge Based on a GPU Parallel Acceleration Technique
Computers and Geotechnics, 2023exaly
GPU Acceleration of CFD Algorithm: HSMAC and SIMPLE
Procedia Computer Science, 2017Qing Yuan, Dongliang Sun
exaly
GPU Acceleration in Physical Synthesis
Proceedings of the 2023 International Symposium on Physical Design, 2023openaire +1 more source