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Concurrent Task Execution on the Intel Xeon Phi

Yucheng Zhu

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Tags: Bioinformatics, Biology, Computer science, CUDA, Intel Xeon Phi, nVidia, OpenMP, Sequence alignment, Smith-Waterman algorithm, Tesla K20, Thesis

June 22, 2015 by hgpu

Comparative Study of the Parallelization of the Smith-Waterman Algorithm on OpenMP and Cuda C

Amadou Chaibou, Oumarou Sie

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 670, OpenMP, Sequence alignment, Smith-Waterman algorithm

June 22, 2015 by hgpu

Optimization and Parallelization Methods for the Design of Next-Generation Radio Networks

Lucas Benedicic

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Tags: Algorithms, Cellular automata, Metaheuristics, nVidia, nVidia GeForce GTX 660 Ti, OpenCL, Package, Signal processing, Thesis

June 22, 2015 by hgpu

GPU accelerated spectral finite elements on all-hex meshes

J.-F. Remacle, R. Gandham, T. Warburton

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Tags: Algorithms, Computer science, CUDA, Numerical Analysis, nVidia, nVidia GeForce GTX 980, OpenCL, Spectral elements, Tesla K40

June 22, 2015 by hgpu

Generating Efficient Tensor Contractions for GPUs

Thomas Nelson, Axel Rivera, Prasanna Balaprakash, Mary Hall, Paul D. Hovland, Elizabeth Jessup, Boyana Norris

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Tags: Algorithms, Chemistry, Computer science, CUDA, Fluid dynamics, Machine learning, nVidia, OpenACC, Optimization

June 22, 2015 by hgpu

Autotuning Tensor Contraction Computations on GPUs

Axel Rivera, Mary Hall, Paul D. Hovland, Elizabeth Jessup, Thomas Nelson, Boyana Norris

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Tags: Benchmarking, Code generation, Computer science, CUDA, Matrix multiplication, nVidia, OpenACC, Tesla C2050, Tesla K20

June 19, 2015 by hgpu

Study of Sparse-Matrix Vector Multiplication (SpMV) on Different Architectures and Libraries

Naveen Anand Subramaniam, Omkar Deshmukh, Vennila Megavannan, Dan Negrut

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 770, OpenCL, Performance, Sparse matrix, Tesla K20, Tesla K40

June 19, 2015 by hgpu

Bulk GCD Computation Using a GPU to Break Weak RSA Keys

Toru Fujita, Koji Nakano, Yasuaki Ito

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 780 Ti, Security

June 19, 2015 by hgpu

Parallel BTF Compression with Multi-Level Vector Quantization in OpenCL

P. Egert, V. Havran

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Tags: 3D Graphics and Realism, Algorithms, Compression, Computer science, nVidia, nVidia GeForce GTX 780, OpenCL, Thesis, Vector quantization

June 19, 2015 by hgpu

Accelerated dimension-independent adaptive Metropolis

Yuxin Chen, David Keyes, Kody J.H. Law, Hatem Ltaief

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Tags: CUDA, nVidia, Probability, Statistics, Tesla K40

June 19, 2015 by hgpu

Visualization of OpenCL Application Execution on CPU-GPU Systems

Amir Kavyan Ziabari, Rafael Ubal, Dana Schaa, David Kaeli

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Tags: ARM, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Visualization

June 19, 2015 by hgpu

RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles

Nicholas P. Bailey, Trond S. Ingebrigtsen, Jesper Schmidt Hansen, Arno A. Veldhorst, Lasse Bohling, Claire A. Lemarchand, Andreas E. Olsen, Andreas K. Bacher, Heine Larsen, Jeppe C. Dyre, Thomas B. Schroder

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 780 Ti, Package, Physics, Python

June 17, 2015 by hgpu

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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