high performance computing on graphics processing units: hgpu.org

hgpu.org » Multilevel summation

Scalable Multi-GPU Simulation of Long-Range Molecular Dynamics

Marcos Novalbos, Jaime Gonzalez, Miguel A. Otaduy, Roberto Martinez Benito, Alberto Sanchez

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Tags: Algorithms, Biomolecules, Chemistry, CUDA, Electrostatic potential, Electrostatics, FFT, Molecular dynamics, Multilevel summation, N-body simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX Titan

September 15, 2014 by hgpu

Multilevel summation of electrostatic potentials using graphics processing units

David J. Hardy, John E. Stone, Klaus Schulten

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Tags: Chemistry, CUDA, Electrostatics, Molecular dynamics, Molecular modeling, Multilevel summation, nVidia, nVidia GeForce GTX 280, Physics, Tesla C870, Tesla D870

November 2, 2010 by hgpu

Accelerating molecular modeling applications with graphics processors

John E. Stone, James C. Phillips, Peter L. Freddolino, David J. Hardy, Leonardo G. Trabuco, Klaus Schulten

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Tags: Chemistry, Computational chemistry, CUDA, Electrostatic potential, Molecular dynamics, Molecular modeling, Multilevel summation, nVidia, nVidia GeForce 8800 GTX

October 30, 2010 by hgpu

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high performance computing on graphics processing units: hgpu.org

Scalable Multi-GPU Simulation of Long-Range Molecular Dynamics

Multilevel summation of electrostatic potentials using graphics processing units

Accelerating molecular modeling applications with graphics processors

Recent source codes

DITRON: Distributed Compiler based on Triton for Parallel Systems

IntelliKit: Agent-first tooling for AMD hardware

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

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

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

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++

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