high performance computing on graphics processing units: hgpu.org

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A Distributed GPU-based Framework for real-time 3D Volume Rendering of Large Astronomical Data Cubes

A.H. Hassan, C.J. Fluke, D.G. Barnes

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Rendering, Tesla C1060, Tesla C2050, Visualization

May 3, 2012 by hgpu

Diderot: A Parallel DSL for Image Analysis and Visualization

Charisee Chiw, Gordon Kindlmann, John Reppy, Lamont Samuels, Nick Seltzer

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Tags: Image processing, nVidia, OpenCL, Package, Programming Languages, Visualization

May 2, 2012 by hgpu

Real-time Visualization of Streaming Text with Force-Based Dynamic System

Jamal Alsakran, Yang Chen, Dongning Luo, Ye Zhao, Jing Yang, Wenwen Dou, Shixia Liu

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Tags: Computer science, CUDA, nVidia, nVidia Quadro NVS 295, Visualization

April 11, 2012 by hgpu

Dynamic Scheduling for Large-Scale Distributed-Memory Ray Tracing

Paul A. Navratil, Donald S. Fussell, Calvin Lin, Hank Childs

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Tags: Algorithms, Computer science, N-body simulation, Raytracing, Visualization

April 6, 2012 by hgpu

Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU

Masato Yoshimi, Takuya Kuhara, Kaname Nishimoto, Mitsunori Miki, Tomoyuki Hiroyasu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8400 GS, nVidia GeForce GTX 280, Optimization, Self-organizing map, Tesla C1060, Visualization

April 5, 2012 by hgpu

Analyzing CUDA’s Compiler through the Visualization of Decoded GPU Binaries

Cedric Nugteren, Bart Mesman, Henk Corporaal

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Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, Performance, Visualization

March 13, 2012 by hgpu

PISTON: A Portable Cross-Platform Framework for Data-Parallel Visualization Operators

Li-ta Lo, Christopher Sewell, James Ahrens

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 6000, OpenCL, Package, Visualization

March 8, 2012 by hgpu

Ray Tracing Visualization Toolkit

Christiaan Gribble, Jeremy Fisher, Daniel Eby, Ed Quigley, Gideon Ludwig

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Tags: 3D Graphics and Realism, Algorithms, Computer science, OpenCL, OpenGL, Raytracing, Rendering, Visualization

March 2, 2012 by hgpu

A Fast and Efficient Simulation Framework for Modeling Heat Transport

Joshua Gordon Clark

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Tags: CUDA, nVidia, nVidia GeForce GT 330 M, Optimization, Physics, Raytracing, Thesis, Visualization

February 29, 2012 by hgpu

High Performance N-Body Simulation and Visualization through CUDA Architecture

Edgar Josafat Martinez Noriega, Tetsu Narumi

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Tags: CUDA, Molecular dynamics, N-body simulation, nVidia, nVidia GeForce GTX 280, OpenGL, Physics, Rendering, Visualization

February 22, 2012 by hgpu

Spatial interpolation of scattered geoscientific data

Florian Hanzer

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Tags: Algorithms, Earth and Space Sciences, Geoscience, nVidia, nVidia GeForce GTX 580, OpenCL, Visualization

February 14, 2012 by hgpu

Real-time simulation of a spiking neural network model of the basal ganglia circuitry using general purpose computing on graphics processing units

Jun Igarashi, Osamu Shouno, Tomoki Fukai, Hiroshi Tsujino

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce GTX 280, Visualization

February 9, 2012 by hgpu

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

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high performance computing on graphics processing units: hgpu.org

A Distributed GPU-based Framework for real-time 3D Volume Rendering of Large Astronomical Data Cubes

Diderot: A Parallel DSL for Image Analysis and Visualization

Real-time Visualization of Streaming Text with Force-Based Dynamic System

Dynamic Scheduling for Large-Scale Distributed-Memory Ray Tracing

Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU

Analyzing CUDA’s Compiler through the Visualization of Decoded GPU Binaries

PISTON: A Portable Cross-Platform Framework for Data-Parallel Visualization Operators

Ray Tracing Visualization Toolkit

A Fast and Efficient Simulation Framework for Modeling Heat Transport

High Performance N-Body Simulation and Visualization through CUDA Architecture

Spatial interpolation of scattered geoscientific data

Real-time simulation of a spiking neural network model of the basal ganglia circuitry using general purpose computing on graphics processing units

Recent source codes

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

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