high performance computing on graphics processing units: hgpu.org

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Linpack evaluation on a supercomputer with heterogeneous accelerators

Toshio Endo, Akira Nukada, Satoshi Matsuoka, Naoya Maruyama

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Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla S1070

July 17, 2011 by hgpu

Large-scale transient stability simulation on graphics processing units

Vahid Jalili-Marandi, Venkata Dinavahi

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Tags: Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 280, Power Systems Simulation

July 14, 2011 by hgpu

K-nearest neighbor search: Fast GPU-based implementations and application to high-dimensional feature matching

Vincent Garcia, Eric Debreuve, Frank Nielsen, Michel Barlaud

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Tags: Computer vision, CUBLAS, CUDA, Image processing, Nearest neighbour, nVidia, nVidia Quadro FX 3700 M, Package, SIFT

May 5, 2011 by hgpu

A pseudospectral matrix method for time-dependent tensor fields on a spherical shell

Bernd Bruegmann

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Tags: Computational Physics, CUBLAS, CUDA, FFT, General Relativity and Quantum Cosmology, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Tesla C2050, Tesla M2070

April 19, 2011 by hgpu

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems Using GPU

Jun-ichi Muramatsu, Shao-Liang Zhang, Yusaku Yamamoto

Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C1060

March 28, 2011 by hgpu

Algebraic 3D Reconstruction of Planetary Nebulae

Stephan Wenger, Juan Aja Fernandez, Christophe Morisset, Marcus Magnor

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Tags: Astrophysics, CUBLAS, CUDA, Image reconstruction, nVidia, Physics

February 24, 2011 by hgpu

Parallel Cloth Simulation Using OpenMP and CUDA

Gillian David Sims

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Tags: Computer science, Conjugate gradient solver, CUBLAS, CUDA, nVidia, nVidia GeForce 9800 GTX, OpenMP, Rendering, Thesis

February 24, 2011 by hgpu

Sparse systems solving on GPUs with GMRES

Raphael Couturier, Stephane Domas

Tags: Computer science, CUBLAS, CUDA, nVidia, Sparse linear iterative solvers, Sparse matrix

February 18, 2011 by hgpu

EigenCFA: accelerating flow analysis with GPUs

Tarun Prabhu, Shreyas Ramalingam, Matthew Might, Mary Hall

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Tags: Computer science, CUBLAS, Flow analysis, nVidia, nVidia GeForce GTX 480, Optimization

February 11, 2011 by hgpu

Evaluating multi-core platforms for HPC data-intensive kernels

Alexander S. van Amesfoort, Ana Lucia Varbanescu, Henk J. Sips, Rob V. van Nieuwpoort

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Tags: Algorithms, Cell processor, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Programming techniques, Tesla C1060

February 6, 2011 by hgpu

Uncontracted Rys Quadrature Implementation of up to G Functions on Graphical Processing Units

Andrey Asadchev, Veerendra Allada, Jacob Felder, Brett M. Bode, Mark S. Gordon and Theresa L. Windus

Tags: Chemistry, CUBLAS, CUDA, Molecular modeling, Molecular simulation, nVidia, nVidia GeForce GTX 275, Tesla T10

February 1, 2011 by hgpu

Fast development of dense linear algebra codes on graphics processors

M. Jesus Zafont, Alberto F. Martin, Francisco Igual, Enrique S. Quintana-Orti

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 Ultra

January 20, 2011 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

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

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

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

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

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high performance computing on graphics processing units: hgpu.org

Linpack evaluation on a supercomputer with heterogeneous accelerators

Large-scale transient stability simulation on graphics processing units

K-nearest neighbor search: Fast GPU-based implementations and application to high-dimensional feature matching

A pseudospectral matrix method for time-dependent tensor fields on a spherical shell

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems Using GPU

Algebraic 3D Reconstruction of Planetary Nebulae

Parallel Cloth Simulation Using OpenMP and CUDA

Sparse systems solving on GPUs with GMRES

EigenCFA: accelerating flow analysis with GPUs

Evaluating multi-core platforms for HPC data-intensive kernels

Uncontracted Rys Quadrature Implementation of up to G Functions on Graphical Processing Units

Fast development of dense linear algebra codes on graphics processors

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

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

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

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