high performance computing on graphics processing units: hgpu.org

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Adaptable particle-in-cell algorithms for graphical processing units

Viktor K. Decyk, Tajendra V. Singh

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Tags: CUDA, nVidia, Particle-in-cell methods, Physics, Presentation, Tesla C1060

January 26, 2011 by hgpu

Data-parallel algorithms and data structures

John Owens

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Tags: Algorithms, Computer science, Data parallelism, Presentation

January 6, 2011 by hgpu

NVIDIA CUDA software and gpu parallel computing architecture

David Kirk

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Tags: Computer science, CUDA, High-level Languages, nVidia, Presentation

December 28, 2010 by hgpu

A low-power handheld GPU using logarithmic arithmetic and triple DVFS power domains

Byeong-Gyu Nam, Jeabin Lee, Kwanho Kim, Seung Jin Lee, and Hoi-Jun Yoo

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Tags: 3D Graphics and Realism, Computer science, Energy-efficient computing, OpenGL, Presentation

December 28, 2010 by hgpu

Simulation of deformable environment with haptic feedback on GPU

Marco Altomonte, Davide Zerbato, Debora Botturi, Paolo Fiorin

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Tags: Computer science, CUDA, nVidia, Presentation, Surgical simulation

December 28, 2010 by hgpu

Performance analysis of memory transfers and GEMM subroutines on NVIDIA Tesla GPU cluster

Veerendra Allada, Troy Benjegerdes, Brett Bode

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Tags: Computer science, CUDA, GPU cluster, nVidia, Performance, Presentation, Tesla S1070, Tesla T10

December 27, 2010 by hgpu

GPU Parallelization of Algebraic Dynamic Programming

Peter Steffen, Robert Giegerich, Mathieu Giraud

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Source codes

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Package, Presentation, Programming techniques

December 17, 2010 by hgpu

GPU-Assisted High Quality Particle Rendering

Deukhyun Cha, Sungjin Son, Insung Ihm

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Tags: 3D Graphics and Realism, Cg, Computer science, nVidia, nVidia GeForce GTX 280, OpenGL, Presentation

December 14, 2010 by hgpu

GPU architecture overview

John Owens

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Tags: Computer science, Hardware, Presentation, Review

December 5, 2010 by hgpu

GPU physics

Mark Harris

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Tags: Computer science, CUDA, nVidia, OpenGL, Presentation, Review

December 5, 2010 by hgpu

Issues and challenges in compiling for graphics processors

Norm Rubin

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Tags: Computer science, High-level Languages, Presentation, Review

November 4, 2010 by hgpu

Implementation of a Lattice–Boltzmann method for numerical fluid mechanics using the nVIDIA CUDA technology

E. Riegel, T. Indinger, N. Adams

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, LBUltra, nVidia, nVidia GeForce 8800 GTS, Presentation, Tesla C1060, Tesla S1070

November 2, 2010 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

Adaptable particle-in-cell algorithms for graphical processing units

Data-parallel algorithms and data structures

NVIDIA CUDA software and gpu parallel computing architecture

A low-power handheld GPU using logarithmic arithmetic and triple DVFS power domains

Simulation of deformable environment with haptic feedback on GPU

Performance analysis of memory transfers and GEMM subroutines on NVIDIA Tesla GPU cluster

GPU Parallelization of Algebraic Dynamic Programming

GPU-Assisted High Quality Particle Rendering

GPU architecture overview

GPU physics

Issues and challenges in compiling for graphics processors

Implementation of a Lattice–Boltzmann method for numerical fluid mechanics using the nVIDIA CUDA technology

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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