high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Exploiting Segmentation for Robust 3D Object Matching

Michael Krainin, Kurt Konolige, Dieter Fox

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTS 450, OpenGL, Package

February 18, 2012 by hgpu

A stereoscopic movie player with real-time content adaptation to the display geometry

Sylvain Duchene, Martin Lambers, Frederic Devernay

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Tags: Computer science, Image processing, nVidia, nVidia GeForce GTX 480, OpenGL, Package, Real-time graphics

February 17, 2012 by hgpu

Graph Coarsening and Clustering on the GPU

B. O. Fagginger Auer, R. H. Bisseling

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Tags: Algorithms, Clustering, Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

February 15, 2012 by hgpu

Robust Real-Time Multiprocessor Interrupt Handling Motivated by GPUs

Glenn A. Elliott, James H. Anderson

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 470, Package

February 14, 2012 by hgpu

LAMMPScuda – a new GPU accelerated Molecular Dynamics Simulations Package and its Application to Ion-Conducting Glasses

Christian Robert Trott

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Tags: Biology, Computational Physics, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 470, Package, Physics, Polymer Systems, Tesla C1060, Thesis

February 13, 2012 by hgpu

Automatic Performance Optimization in ViennaCL for GPUs

Karl Rupp, Josef Weinbub, Florian Rudolf

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Computer science, Linear Algebra, nVidia, nVidia GeForce 8500 GT, nVidia GeForce GTX 470, OpenCL, Optimization, Package, Performance, Programming techniques

February 10, 2012 by hgpu

Implementing Molecular Dynamics on Hybrid High Performance Computers – Particle-Particle Particle-Mesh

W. Michael Brown, Axel Kohlmeyer, Steven J. Plimpton, Arnold N. Tharrington

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Tags: Algorithms, Chemistry, CUDA, Electrostatics, GPU cluster, Heterogeneous systems, Molecular dynamics, nVidia, OpenCL, OpenMPI, Package, Physics, Tesla M2070

February 10, 2012 by hgpu

Real-Time SAH BVH Construction for Ray Tracing Dynamic Scenes

Dmitry Sopin, Denis Bogolepov, Danila Ulyanov

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Raytracing, Real-time graphics, Rendering

February 10, 2012 by hgpu

Symbolic Testing of OpenCL Code

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

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Tags: Benchmarking, Code generation, Computer science, nVidia, OpenCL, Package, PTX, Tesla C1060

February 8, 2012 by hgpu

Verifiable Computation with Massively Parallel Interactive Proofs

Justin Thaler, Mike Roberts, Michael Mitzenmacher, Hanspeter Pfister

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Tags: Benchmarking, Cloud, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 480, Package, Security

February 8, 2012 by hgpu

The Virtual OpenCL (VCL) Cluster Platform

Amnon Barak, Amnon Shiloh

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Tags: ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

January 31, 2012 by hgpu

CUDA Expression Templates

Paul Wiemann, Stephan Wenger, Marcus Magnor

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTS 250, Package

January 30, 2012 by hgpu

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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

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high performance computing on graphics processing units: hgpu.org

Applications

Exploiting Segmentation for Robust 3D Object Matching

A stereoscopic movie player with real-time content adaptation to the display geometry

Graph Coarsening and Clustering on the GPU

Robust Real-Time Multiprocessor Interrupt Handling Motivated by GPUs

LAMMPScuda – a new GPU accelerated Molecular Dynamics Simulations Package and its Application to Ion-Conducting Glasses

Automatic Performance Optimization in ViennaCL for GPUs

Implementing Molecular Dynamics on Hybrid High Performance Computers – Particle-Particle Particle-Mesh

Real-Time SAH BVH Construction for Ray Tracing Dynamic Scenes

Symbolic Testing of OpenCL Code

The Virtual OpenCL (VCL) Cluster Platform

CUDA Expression Templates

Recent source codes

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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

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