high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Adapting a message-driven parallel application to GPU-accelerated clusters

James C. Phillips, John E. Stone, Klaus Schulten

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Tags: Computer science, CUDA, GPU cluster, Molecular dynamics, nVidia, nVidia Quadro FX 5600

October 28, 2010 by hgpu

The gputools package enables GPU computing in R

Joshua Buckner, Justin Wilson, Mark Seligman, Brian Athey, Stanley Watson, Fan Meng

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Tags: Computer science, CUBLAS, CUDA, nVidia, Package

October 28, 2010 by hgpu

Accelerating Large Graph Algorithms on the GPU Using CUDA

Pawan Harish, P. Narayanan

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia GeForce 8800 GTX

October 28, 2010 by hgpu

Adaptive Mesh Fluid Simulations on GPU

Peng Wang, Tom Abel, Ralf Kaehler

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, nVidia, nVidia GeForce 8800 GT

October 28, 2010 by hgpu

GPU-accelerated large-scale quantum molecular dynamics simulation of 3-dimensional C60 polymers

Toshiaki Iitaka

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Tags: Computational Physics, CUDA, Materials Science, Molecular dynamics, nVidia, nVidia GeForce 8800 GTX, Physics

October 28, 2010 by hgpu

GAMER: a GPU-Accelerated Adaptive Mesh Refinement Code for Astrophysics

Hsi-Yu Schive, Yu-Chih Tsai, Tzihong Chiueh

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, GPU cluster, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia

October 28, 2010 by hgpu

High performance cellular level agent-based simulation with FLAME for the GPU

Paul Richmond, Dawn Walker, Simon Coakley, Daniela Romano

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Tags: Bioinformatics, Cellular modelling, Computational modelling, Computer science, CUDA, nVidia, Package

October 28, 2010 by hgpu

CrystalGPU: Transparent and Efficient Utilization of GPU Power

Abdullah Gharaibeh, Samer Al-Kiswany, Matei Ripeanu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, Package, Performance

October 28, 2010 by hgpu

Fast CGH computation using S-LUT on GPU

Yuechao Pan, Xuewu Xu, Sanjeev Solanki, Xinan Liang, Ridwan B. Tanjung, Chiwei Tan, Tow-Chong Chong

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Tags: Algorithms, Computer holography, Physics

October 28, 2010 by hgpu

All-pairs shortest-paths for large graphs on the GPU

Gary J. Katz, Joseph T. Kider

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Tags: CUDA, Graph theory, Mathematics, nVidia, nVidia Quadro FX 5600

October 28, 2010 by hgpu

An integrated GPU power and performance model

Sunpyo Hong, Hyesoon Kim

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Tags: Analytical model, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 280, Performance

October 28, 2010 by hgpu

GPU as a General Purpose Computing Resource

Qihang Huang, Zhiyi Huang, Paul Werstein, Martin Purvis

Tags: Computer science, CUDA, nVidia, Performance, Programming techniques

October 27, 2010 by hgpu

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

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

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

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high performance computing on graphics processing units: hgpu.org

Programming

Adapting a message-driven parallel application to GPU-accelerated clusters

The gputools package enables GPU computing in R

Accelerating Large Graph Algorithms on the GPU Using CUDA

Adaptive Mesh Fluid Simulations on GPU

GPU-accelerated large-scale quantum molecular dynamics simulation of 3-dimensional C60 polymers

GAMER: a GPU-Accelerated Adaptive Mesh Refinement Code for Astrophysics

High performance cellular level agent-based simulation with FLAME for the GPU

CrystalGPU: Transparent and Efficient Utilization of GPU Power

Fast CGH computation using S-LUT on GPU

All-pairs shortest-paths for large graphs on the GPU

An integrated GPU power and performance model

GPU as a General Purpose Computing Resource

Recent source codes

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

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

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

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

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

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