high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

Scout: a data-parallel programming language for graphics processors

Patrick McCormick, Jeff Inman, James Ahrens, Jamaludin M. Yusof, Greg Roth, Sharen Cummins

Tags: Computer science, High-level Languages, Visualization

December 5, 2010 by hgpu

Implementing a GPU-Enhanced Cluster for Large-Scale Simulations

Robert Lucas, Gene Wagenbreth, Dan Davis

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Programming techniques

December 5, 2010 by hgpu

An adaptive framework for visualizing unstructured grids with time-varying scalar fields

F. Bernardon, S. Callahan, J. Comba, C. Silva

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Tags: Computer science, nVidia, nVidia GeForce 7800 GTX, Package, Rendering, Visualization

December 5, 2010 by hgpu

GPU-accelerated affordance cueing based on visual attention

S. May, M. Klodt, E. Rome, R. Breithaupt

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Tags: ATI, ATI Radeon 9800 XT, Computer science, Computer vision, nVidia, nVidia GeForce 7800 GT, nVidia GeForce 8800 GTX, OpenGL

December 5, 2010 by hgpu

GPU-based particle simulation with inter-collisions

Jeronimo S. Venetillo, Waldemar Celes

Tags: 3D Graphics and Realism, Computer science, Particle simulation

December 4, 2010 by hgpu

In-memory grid files on graphics processors

Ke Yang, Bingsheng He, Rui Fang, Mian Lu, Naga Govindaraju, Qiong Luo, Pedro Sander, Jiaoying Shi

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce 8800 GTX

December 4, 2010 by hgpu

GPUQP: query co-processing using graphics processors

Rui Fang, Bingsheng He, Mian Lu, Ke Yang, Naga K. Govindaraju, Qiong Luo, Pedro V. Sander

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Package, Review

December 4, 2010 by hgpu

GPU Computing: Programming a Massively Parallel Processor

Ian Buck

Tags: Computer science, CUDA, High-level Languages, nVidia, Review

December 4, 2010 by hgpu

Parallel processing between GPU and CPU: Concepts in a game architecture

Marcelo Panaro de Moraes Zamith, Esteban W. G. Clua, Aura Conci, Anselmo Montenegro, Paulo A. Pagliosa, Luis Valente

Tags: Computer science, Games

December 4, 2010 by hgpu

Dynamic Warp Formation and Scheduling for Efficient GPU Control Flow

Wilson W. L. Fung, Ivan Sham, George Yuan, Tor M. Aamodt

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Tags: Computer science, Hardware, Performance

December 4, 2010 by hgpu

Shared Sampling for Real-Time Alpha Matting

Eduardo S. L. Gastal, Manuel M. Oliveira

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Tags: Computer vision, GLSL, Image processing, nVidia, nVidia GeForce GTX 280

December 4, 2010 by hgpu

Abstract shade trees

Morgan McGuire, George Stathis, Hanspeter Pfister, Shriram Krishnamurthi

Tags: Artificial intelligence, Computer science, Data Structures and Algorithms, Shaders

December 4, 2010 by hgpu

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

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

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high performance computing on graphics processing units: hgpu.org

Applications

Scout: a data-parallel programming language for graphics processors

Implementing a GPU-Enhanced Cluster for Large-Scale Simulations

An adaptive framework for visualizing unstructured grids with time-varying scalar fields

GPU-accelerated affordance cueing based on visual attention

GPU-based particle simulation with inter-collisions

In-memory grid files on graphics processors

GPUQP: query co-processing using graphics processors

GPU Computing: Programming a Massively Parallel Processor

Parallel processing between GPU and CPU: Concepts in a game architecture

Dynamic Warp Formation and Scheduling for Efficient GPU Control Flow

Shared Sampling for Real-Time Alpha Matting

Abstract shade trees

Recent source codes

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

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

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