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Work Efficient Parallel Algorithms for Large Graph Exploration

Dip Sankar Banerjee, Shashank Sharma, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

October 21, 2013 by hgpu

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Sivaramakrishna Bharadwaj Indarapu, Manoj Maramreddy, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, Sparse matrix

October 21, 2013 by hgpu

Multi-Scale Scheduling Techniques for Signal Processing Systems

Zheng Zhou

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Tags: Algorithms, CUDA, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Particle swarm optimization, Signal processing, Thesis

October 19, 2013 by hgpu

An Incompressible Navier-Stokes Equations Solver on the GPU Using CUDA

Niklas Karlsson

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Tags: Algorithms, CUDA, Fluid dynamics, Laplace and Poisson equation, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 660 Ti, Poisson equation, Thesis

October 19, 2013 by hgpu

VDBSCAN+: Performance Optimization Based on GPU Parallelism

Carlos Roberto Valencio, Guilherme Priolli Daniel, Camila Alves de Medeiros, Adriano Mauro Cansian

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Tags: Algorithms, Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GT 525 M

October 18, 2013 by hgpu

Efficient SVM Training Using Parallel Primal-Dual Interior Point Method on GPU

Jing Jin, Xianggao Cai, Xiaola Lin

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Tesla C2050

October 18, 2013 by hgpu

Using CUDA GPU to Accelerate the Ant Colony Optimization Algorithm

Kai-Cheng Wei, Chao-Chin Wu, Chien-Ju Wu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 520

October 18, 2013 by hgpu

Empirical performance modeling of GPU kernels using active learning

Prasanna Balaprakash, Karl Rupp, Azamat Mametjanov, Robert B. Gramacy, Paul D. Hovland, Stefan M. Wild

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 470, OpenCL, Performance, Tesla C2050, Tesla K20

October 17, 2013 by hgpu

GPU-acceleration of parallel unconditionally stable group explicit finite difference method

K. Parand, Saeed Zafarvahedian, Sayyed A. Hossayni

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Tags: Algorithms, Computer science, CUDA, Finite difference, Numerical Analysis, nVidia, nVidia GeForce GT 335 M

October 15, 2013 by hgpu

GPU-Specfic Kalman Filtering and Retrodiction for Large-Scale Target Tracking

Sean Tager

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Tags: Algorithms, Computer science, Filtering, Thesis

October 13, 2013 by hgpu

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Jonathan Passerat-Palmbach

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Tags: Algorithms, Computer science, CUDA, Java, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Pseudo-random number generators, Software Engineering, Stochastic simulation, Tesla C2050, Tesla C2075, Tesla K20, Thesis

October 13, 2013 by hgpu

High performance sequence mining using pairwise statistical significance

Yuhong Zhang, Feng Chen

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Source codes

Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C2050

October 12, 2013 by hgpu

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

EnergyUCB-Bandit

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Work Efficient Parallel Algorithms for Large Graph Exploration

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Multi-Scale Scheduling Techniques for Signal Processing Systems

An Incompressible Navier-Stokes Equations Solver on the GPU Using CUDA

VDBSCAN+: Performance Optimization Based on GPU Parallelism

Efficient SVM Training Using Parallel Primal-Dual Interior Point Method on GPU

Using CUDA GPU to Accelerate the Ant Colony Optimization Algorithm

Empirical performance modeling of GPU kernels using active learning

GPU-acceleration of parallel unconditionally stable group explicit finite difference method

GPU-Specfic Kalman Filtering and Retrodiction for Large-Scale Target Tracking

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

High performance sequence mining using pairwise statistical significance

Recent source codes

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

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

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

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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

EnergyUCB-Bandit

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