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Simulations of Complex and Microscopic Models of Cardiac Electrophysiology Powered by Multi-GPU Platforms

Bruno Gouvea de Barros, Rafael Sachetto Oliveira, Wagner Meira Jr., Marcelo Lobosco, Rodrigo Weber dos Santos

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Tags: Cluster computing, CUDA, Heterogeneous systems, Medicine, nVidia, ODEs, Ordinary differential equations, Partial differential equations, PDEs, Tesla C1060

December 3, 2012 by hgpu

GPU-based Space Situational Awareness Simulation utilising parallelism for enhanced multi-sensor management

Tyler A. Hobson, I. Vaughan L. Clarkson

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Tags: CUDA, Earth and Space Sciences, nVidia

December 3, 2012 by hgpu

Non-steady relaxation and critical exponents at the depinning transition

Ezequiel E. Ferrero, Sebastian Bustingorry, Alejandro B. Kolton

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Tags: Condensed matter, CUDA, Numerical simulation, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, Physics, Statistical Mechanics, Tesla C2075

December 3, 2012 by hgpu

Parallelism in Database Operations

Kalle Karkkainen

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

December 2, 2012 by hgpu

FIELA: A Fast Image Encryption with Lorenz Attractor using Hybrid Computing

P Kranthi Kumar, B V Nagendra Prasad, Gelli MBSS Kumar, V. Chandrasekaran, P.K.Baruah

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Tags: Computer science, CUDA, Hybrid computing, nVidia, Security, Tesla M2070

December 2, 2012 by hgpu

Numerical resolution of conservation laws with OpenCL

Anais Crestetto, Philippe Helluy, Jonathan Jung

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Tags: ATI, ATI Radeon HD 5850, Mathematics, Maxwell's equations, Numerical simulation, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 320 M, nVidia GeForce GTX 470, OpenCL, Particle-in-cell methods

December 2, 2012 by hgpu

Developing Extensible Lattice-Boltzmann Simulators for General-Purpose Graphics-Processing Units

Stuart D. C. Walsh, Martin O. Saar

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Tags: Code generation, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla C1060

December 1, 2012 by hgpu

OpenCL Numerical Simulations of Two-Fluid Compressible Flows With a 2D Random Choice Method

Philippe Helluy, Jonathan Jung

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Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 7970, Fluid dynamics, Numerical simulation, nVidia, nVidia GeForce GTX 320 M, OpenCL

December 1, 2012 by hgpu

CUDA-OpenGL Interoperability to Visualize Electromagnetic Fields Calculated by FDTD

Veysel Demir, Atef Z. Elsherbeni

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Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, OpenGL, Tesla C1060, Visualization

December 1, 2012 by hgpu

CPUless PCs inside networked control systems

Peter Fodrek, Tomas Murgas, Michal Blaho

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Tags: Algorithms, Computer science, nVidia, OpenCL, Operating systems

December 1, 2012 by hgpu

Multidimensional Dataflow Graph Modeling and Mapping for Efficient GPU Implementation

Lai-Huei Wang, Chung-Ching Shen, Gunasekaran Seetharaman, Kannappan Palaniappan, Shuvra S. Bhattacharyya

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Tags: Computer science, CUDA, Design space exploration, DSP, nVidia, nVidia GeForce GTX 260

December 1, 2012 by hgpu

Using GPUs for Realtime Prediction of Optical Forces on Microsphere Ensembles

Sujal Bista, Sagar Chowdhury, Satyandra K. Gupta, Amitabh Varshney

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Tags: CUDA, nVidia, nVidia GeForce GTX 470, Optical trapping, Physics, Raytracing

November 29, 2012 by hgpu

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

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

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

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high performance computing on graphics processing units: hgpu.org

Simulations of Complex and Microscopic Models of Cardiac Electrophysiology Powered by Multi-GPU Platforms

GPU-based Space Situational Awareness Simulation utilising parallelism for enhanced multi-sensor management

Non-steady relaxation and critical exponents at the depinning transition

Parallelism in Database Operations

FIELA: A Fast Image Encryption with Lorenz Attractor using Hybrid Computing

Numerical resolution of conservation laws with OpenCL

Developing Extensible Lattice-Boltzmann Simulators for General-Purpose Graphics-Processing Units

OpenCL Numerical Simulations of Two-Fluid Compressible Flows With a 2D Random Choice Method

CUDA-OpenGL Interoperability to Visualize Electromagnetic Fields Calculated by FDTD

CPUless PCs inside networked control systems

Multidimensional Dataflow Graph Modeling and Mapping for Efficient GPU Implementation

Using GPUs for Realtime Prediction of Optical Forces on Microsphere Ensembles

Recent source codes

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++

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

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