high performance computing on graphics processing units: hgpu.org

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OpenCL Programming by Example

Ravishekhar Banger, Koushik Bhattacharyya

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Tags: Book, Computer science, Image processing, Matrix multiplication, Memory model, Nearest neighbour, OpenCL, OpenGL, Pattern recognition, Tutorial

December 27, 2013 by hgpu

BbmTTP: Beat-based Parallel Simulated Annealing Algorithm on GPGPUs for the Mirrored Traveling Tournament Problem

Vijay Menon, Saurabh Jha

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Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, Package, Tesla M2050

December 27, 2013 by hgpu

Multi-GPU Load Balancing for In-Situ Simulation and Visualization

Yong Cao, Robert Hagan

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Tags: Computer science, nVidia, nVidia GeForce GTX 295, Rendering, Task scheduling, Visualization

December 27, 2013 by hgpu

BIDMach: Large-scale Learning with Zero Memory Allocation

John Canny, Huasha Zhao

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Tags: Benchmarking, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 690

December 25, 2013 by hgpu

Building Multiclass Nonlinear Classifiers with GPUs

Ignacio Arnaldo, Kalyan Veeramachaneni, Una-May O'Reilly

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 690

December 25, 2013 by hgpu

Efficiency analysis of a physical problem: Different parallel computational approaches for a dynamical integrator evolution

Adriana Gaudiani, Alejandro Soba, M. Florencia Carusela

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 560 Ti, Performance

December 25, 2013 by hgpu

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

Tetsuya Odajima, Taisuke Boku, Mitsuhisa Sato, Toshihiro Hanawa, Yuetsu Kodama, Raymond Namyst, Samuel Thibault, Olivier Aumage

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Performance, Task scheduling, Tesla M2090

December 25, 2013 by hgpu

A Convex Relaxation Approach to Space Time Multi-view 3D Reconstruction

Martin R. Oswald, Daniel Cremers

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Tags: Computer science, Computer vision, CUDA, nVidia, Tesla C2070

December 25, 2013 by hgpu

Scene Boundary Detection Technique Based on Bottom-Up Attention System and OpenCL Parallel Implementation

S. Axyonov, D. Kovalenko, I. Potapyev

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Tags: Algorithms, ATI, ATI Radeon HD 5850 M, Computer vision, Image processing, OpenCL

December 24, 2013 by hgpu

Transparent Checkpoint-Restart for Hardware-Accelerated 3D Graphics

Samaneh Kazemi, Rohan Garg, Gene Cooperman

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Tags: Computer science, nVidia, nVidia GeForce GT 650 M, OpenGL, Operating systems

December 24, 2013 by hgpu

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

Thomas Paine, Hailin Jin, Jianchao Yang, Zhe Lin, Thomas Huang

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Tags: Computer science, Computer vision, CUDA, Data parallelism, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K20

December 24, 2013 by hgpu

Large-Scale Paralleled Sparse Principal Component Analysis

W. Liu, H. Zhang, D. Tao, Y. Wang, K. Lu

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Tags: Computer science, CUBLAS, CUDA, Machine learning, Numerical Analysis, nVidia, Tesla C2050

December 24, 2013 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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high performance computing on graphics processing units: hgpu.org

Applications

OpenCL Programming by Example

BbmTTP: Beat-based Parallel Simulated Annealing Algorithm on GPGPUs for the Mirrored Traveling Tournament Problem

Multi-GPU Load Balancing for In-Situ Simulation and Visualization

BIDMach: Large-scale Learning with Zero Memory Allocation

Building Multiclass Nonlinear Classifiers with GPUs

Efficiency analysis of a physical problem: Different parallel computational approaches for a dynamical integrator evolution

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

A Convex Relaxation Approach to Space Time Multi-view 3D Reconstruction

Scene Boundary Detection Technique Based on Bottom-Up Attention System and OpenCL Parallel Implementation

Transparent Checkpoint-Restart for Hardware-Accelerated 3D Graphics

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

Large-Scale Paralleled Sparse Principal Component Analysis

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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