high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Data-intensive document clustering on graphics processing unit (GPU) clusters

Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas Potok

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, GPU cluster, nVidia, nVidia GeForce GTX 280, Tesla C1060

September 13, 2011 by hgpu

Lossless data compression on GPGPU architectures

Axel Eirola

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Tags: Algorithms, Compression, Computer science, Data Structures and Algorithms

September 13, 2011 by hgpu

Parallel volume rendering implementation on graphics cards using CUDA

Jens Fangerau, Susanne Kromker

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, OpenGL, Rendering, Visualization

September 13, 2011 by hgpu

Gate-Level Simulation with GPU Computing

Debapriya Chatterjee, Andrew Deorio, Valeria Bertacco

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Tags: Algorithms, CAD, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, Performance

September 13, 2011 by hgpu

Software Challenges for Extreme Scale Computing: Going From Petascale to Exascale Systems

Michael A. Heroux

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Tags: Computer science, Performance, Review, Software Engineering

September 13, 2011 by hgpu

Energy-efficient computing for extreme-scale science

David Donofrio, Leonid Oliker, John Shalf, Michael F. Wehner, Chris Rowen, Jens Krueger, Shoaib Kamil, Marghoob Mohiyuddin

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Tags: Computer science, Energy-efficient computing, Review

September 12, 2011 by hgpu

Intermediate fabrics: virtual architectures for circuit portability and fast placement and routing

James Coole, Greg Stitt

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Tags: CAD, Computer science, FPGA, Performance, Virtualization

September 12, 2011 by hgpu

Task superscalar: using processors as functional units

Yoav Etsion, Alex Ramirez, Rosa M. Badia, Eduard Ayguade, Jesus Labarta, Mateo Valero

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Tags: Benchmarking, Cell processor, Computer science, Performance, Programming techniques

September 12, 2011 by hgpu

Meta-simulation of large WSN on multi-core computers

Adnan Iqbal, Bernard Pottier

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Tags: Algorithms, Computer science, Networks, Optimization

September 12, 2011 by hgpu

A scripting language for Digital Content Creation applications

Mohammed Yousef, Ahmed Hashem, Hassan Saad, Amr Gamal, Osama Galal, Khaled F. Hussain

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Tags: 3D Graphics and Realism, Computer science, GLSL, High-level Languages, nVidia, OpenCL

September 12, 2011 by hgpu

Symbolic crosschecking of floating-point and SIMD code

Peter Collingbourne, Cristian Cadar, Paul H.J. Kelly

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Source codes

Tags: Algorithms, Computer science, Package, Performance, Software Engineering

September 12, 2011 by hgpu

Implementing cartesian genetic programming classifiers on graphics processing units using GPU.NET

Simon Harding, Wolfgang Banzhaf

Tags: Algorithms, Artificial intelligence, Computer science, Genetic programming, Programming techniques

September 12, 2011 by hgpu

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

Data-intensive document clustering on graphics processing unit (GPU) clusters

Lossless data compression on GPGPU architectures

Parallel volume rendering implementation on graphics cards using CUDA

Gate-Level Simulation with GPU Computing

Software Challenges for Extreme Scale Computing: Going From Petascale to Exascale Systems

Energy-efficient computing for extreme-scale science

Intermediate fabrics: virtual architectures for circuit portability and fast placement and routing

Task superscalar: using processors as functional units

Meta-simulation of large WSN on multi-core computers

A scripting language for Digital Content Creation applications

Symbolic crosschecking of floating-point and SIMD code

Implementing cartesian genetic programming classifiers on graphics processing units using GPU.NET

Recent source codes

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

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