high performance computing on graphics processing units: hgpu.org

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PARRAY: A Unifying Array Representation for Heterogeneous Parallelism

Yifeng Chen, Xiang Cui, Hong Mei

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Tags: Code generation, Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, MPI, nVidia, Optimization, Performance, Programming techniques, Pthreads, Tesla C1060

January 5, 2012 by hgpu

Programming of shared memory GPUs shared memory systems

Jean-Philippe Bergeron

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, Optimization, Programming techniques

January 2, 2012 by hgpu

OpenCL in Action: How to Accelerate Graphics and Computations

Matthew Scarpino

Tags: Book, Computer science, OpenCL, Programming techniques, Tutorial

December 26, 2011 by hgpu

Reducing the Size of Nurbs Controls Nets Using Genetic Algorithms and CUDA

Matthew J. O'Neal, Cameron J. Turner

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Programming techniques

December 23, 2011 by hgpu

Parallel programming with inductive synthesis

Shaon Barman, Rastislav Bodik, Sagar Jain, Yewen Pu, Saurabh Srivastava, Nicholas Tung

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Performance, Programming techniques

December 19, 2011 by hgpu

Leveraging Parallelism with CUDA and OpenCL

S. Park, D. Shires, J. Ross, D. Richie

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Tags: AMD FireStream 9250, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Programming techniques, Tesla C1060

December 18, 2011 by hgpu

Code Optimization Techniques for Graphics Processing Units

Fernando Magno Quintao Pereira

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Tags: Algorithms, Book, Code generation, Computer science, CUDA, nVidia, nVidia GeForce 9400 M, Optimization, Package, Programming techniques, PTX, Tutorial

December 17, 2011 by hgpu

Customizable Memory Schemes for Data Parallel Accelerators

Chunyang Gou

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques, Thesis

December 17, 2011 by hgpu

Evaluating graph coloring on GPUs

A.V. Pascal Grosset, Peihong Zhu, Shusen Liu, Suresh Venkatasubramanian, Mary Hall

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Programming techniques

December 11, 2011 by hgpu

Directives Based Programming of GPU Accelerated Systems

Saif Mulla

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Tags: Computer science, CUDA, Molecular dynamics, nVidia, Programming techniques, Tesla C2050, Thesis

November 29, 2011 by hgpu

Parallelized agent-based simulation on CPU and graphics hardware for spatial and stochastic models in biology

Martin Falk, Michael Ott, Thomas Ertl, Michael Klann, Heinz Koeppl

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Tags: Biology, CUDA, nVidia, nVidia GeForce GTX 465, Programming techniques

November 24, 2011 by hgpu

Exploiting concurrent kernel execution on graphic processing units

Lingyuan Wang, Miaoqing Huang, Tarek El-Ghazawi

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques, Tesla C2070

November 19, 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

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high performance computing on graphics processing units: hgpu.org

PARRAY: A Unifying Array Representation for Heterogeneous Parallelism

Programming of shared memory GPUs shared memory systems

OpenCL in Action: How to Accelerate Graphics and Computations

Reducing the Size of Nurbs Controls Nets Using Genetic Algorithms and CUDA

Parallel programming with inductive synthesis

Leveraging Parallelism with CUDA and OpenCL

Code Optimization Techniques for Graphics Processing Units

Customizable Memory Schemes for Data Parallel Accelerators

Evaluating graph coloring on GPUs

Directives Based Programming of GPU Accelerated Systems

Parallelized agent-based simulation on CPU and graphics hardware for spatial and stochastic models in biology

Exploiting concurrent kernel execution on graphic processing units

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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