high performance computing on graphics processing units: hgpu.org

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Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission

Haicheng Wu, Gregory Diamos, Ashwin Lele, Jin Wang, Srihari Cadambi, Sudhakar Yalamanchili, Srimat Chakradhar

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Tags: Compilers, Computer science, CUDA, Databases, nVidia, Optimization, Tesla C2070

August 9, 2012 by hgpu

Solving the Flexible Job Shop Problem on Multi-GPU

Wojciech Bozejko, Zdzilaw Hejducki, Mariusz Uchronski, Mieczyslaw Wodecki

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Tags: Computer science, CUDA, GPU cluster, Metaheuristics, MPI, nVidia, Optimization, Search, Tesla S2050

August 8, 2012 by hgpu

CUDA-Accelerated HD-ODETLAP: Lossy High Dimensional Gridded Data Compression

W. Randolph Franklin, You Li, Tsz-Yam Lau, Peter Fox

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Tags: Algorithms, Compression, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs

August 8, 2012 by hgpu

Policy-based Tuning for Performance Portability and Library Co-optimization

Duane Merrill, Michael Garland, Andrew Grimshaw

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce 9800 GTX, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Performance

August 8, 2012 by hgpu

Large Scale Finite Element Analysis Using GPU Parallel Computing

Ashkan Akbariyeh

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Tags: Algorithms, Computer science, CUDA, Finite element method, nVidia, nVidia Quadro FX 5000, Sparse matrix, Thesis

August 8, 2012 by hgpu

Using GPU-based Computing To Accelerate Finite Element Problems

Jacob Watt

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Tags: Computer science, CUDA, Finite element method, Linear Algebra, nVidia, nVidia Quadro FX 5000, Thesis, Visualization

August 8, 2012 by hgpu

Efficient Algorithms for Sorting on GPUs

Seema M. Munavalli

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Sorting, Thesis

August 7, 2012 by hgpu

Efficient Monte Carlo sampler for detecting parametric objects in large scenes

Yannick Verdie, Florent Lafarge

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia Quadro FX 4800

August 7, 2012 by hgpu

Accelerating Cryptographic Primitives with GPUs

Patrick Carpenter

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Tags: Computer science, CUDA, Hashing, nVidia, Review, Security

August 6, 2012 by hgpu

Coordinated system level resource management for heterogeneous many-core platforms

Vishakha Gupta

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GTX, Thesis

August 6, 2012 by hgpu

Comparison of OpenMP & OpenCL Parallel Processing Technologies

Krishnahari Thouti, S.R.Sathe

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Tags: Benchmarking, Computer science, nVidia, nVidia Quadro FX 3800, OpenCL, OpenMP, Performance

August 6, 2012 by hgpu

Visualization of Astronomical Nebulae via Distributed Multi-GPU Compressed Sensing Tomography

Stephan Wenger, Marco Ament, Stefan Guthe, Dirk Lorenz, Andreas Tillmann, Daniel Weiskopf, Marcus Magnor

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Tags: Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce GTX 480, Rendering, Sensing, Tomography, Visualization

August 6, 2012 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission

Solving the Flexible Job Shop Problem on Multi-GPU

CUDA-Accelerated HD-ODETLAP: Lossy High Dimensional Gridded Data Compression

Policy-based Tuning for Performance Portability and Library Co-optimization

Large Scale Finite Element Analysis Using GPU Parallel Computing

Using GPU-based Computing To Accelerate Finite Element Problems

Efficient Algorithms for Sorting on GPUs

Efficient Monte Carlo sampler for detecting parametric objects in large scenes

Accelerating Cryptographic Primitives with GPUs

Coordinated system level resource management for heterogeneous many-core platforms

Comparison of OpenMP & OpenCL Parallel Processing Technologies

Visualization of Astronomical Nebulae via Distributed Multi-GPU Compressed Sensing Tomography

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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