high performance computing on graphics processing units: hgpu.org

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Implementing Ultrasound Beamforming on the GPU using CUDA

Lars Gronvold

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Tags: Computer science, CUDA, nVidia, Tesla C870, Thesis, Ultrasound

March 10, 2011 by hgpu

Tuned and asynchronous stencil kernels for CPU/GPU systems (thesis)

Sundaresan Venkatasubramanian

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 570, Performance, Tesla C1060, Tesla C870, Thesis

March 6, 2011 by hgpu

An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters

Dana A. Jacobsen, Julien C. Thibault, Inanc Senocak

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Tags: CUDA, Fluid dynamics, GPU cluster, MPI, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260, Tesla C1060, Tesla C870, Tesla S1070, Tesla S870

February 24, 2011 by hgpu

Accelerating Quantum Monte Carlo Simulations with Emerging Architectures

Akila Gothandaraman

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Tags: Computer science, CUDA, FPGA, nVidia, QMC, Tesla C1060, Tesla C870, Thesis

February 24, 2011 by hgpu

Accelerating the Stochastic Simulation Algorithm

David Jenkins, Gregory D. Peterson

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Tags: Biology, CUDA, Monte Carlo simulation, MPI, nVidia, Stochastic simulation, Tesla C870

February 21, 2011 by hgpu

Efficiency Considerations of Cauchy Reed-Solomon Implementations on Accelerator and Multi-Core Platforms

Thomas Steinke, Kathrin Peter, and Sebastian Borchert

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Tags: Cell processor, Computer science, CUDA, Error recovery, FPGA, nVidia, Tesla C1060, Tesla C870

February 19, 2011 by hgpu

Accelerating the Stochastic Simulation Algorithm using Emerging Architectures

David Dewayne Jenkins

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce 8600 M, Stochastic simulation, Tesla C1060, Tesla C870, Thesis

February 16, 2011 by hgpu

Model-driven autotuning of sparse matrix-vector multiply on GPUs

Jee W. Choi, Amik Singh, Richard W. Vuduc

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix, Tesla C1060, Tesla C870, Tesla T10P

February 5, 2011 by hgpu

Data access optimized applications on the GPU using NVIDIA CUDA

Dheevatsa Mudiger

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Tags: Computer science, CUDA, Data Structures and Algorithms, Fluid dynamics, nVidia, Tesla C1060, Tesla C870, Thesis

February 3, 2011 by hgpu

Direct N-body Kernels for Multicore Platforms

Nitin Arora, Aashay Shringarpure, Richard W. Vuduc

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Tags: Computer science, CUDA, N-body simulation, nVidia, Tesla C1060, Tesla C870

January 20, 2011 by hgpu

Blasting through lattice calculations using CUDA

Kipton Barros, Ronald Babich, Richard Brower, Michael A. Clark, Claudio Rebbi

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, Physics, QCD, Tesla C870

January 18, 2011 by hgpu

Power Consumption of GPUs from a Software Perspective

Sylvain Collange, David Defour, Arnaud Tisserand

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 9800 GX2, Tesla C870, Tesla D870, Tesla T10P

January 7, 2011 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

Implementing Ultrasound Beamforming on the GPU using CUDA

Tuned and asynchronous stencil kernels for CPU/GPU systems (thesis)

An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters

Accelerating Quantum Monte Carlo Simulations with Emerging Architectures

Accelerating the Stochastic Simulation Algorithm

Efficiency Considerations of Cauchy Reed-Solomon Implementations on Accelerator and Multi-Core Platforms

Accelerating the Stochastic Simulation Algorithm using Emerging Architectures

Model-driven autotuning of sparse matrix-vector multiply on GPUs

Data access optimized applications on the GPU using NVIDIA CUDA

Direct N-body Kernels for Multicore Platforms

Blasting through lattice calculations using CUDA

Power Consumption of GPUs from a Software Perspective

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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