high performance computing on graphics processing units: hgpu.org

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A Moving Least Squares Based Approach for Contour Visualization of Multi-Dimensional Data

Chris W. Muelder, Nick Leaf, Carmen Sigovan, Kwan-Liu Ma

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Tags: Computer science, CUDA, Graphics, nVidia, nVidia GeForce GTX 285, Visualization

August 5, 2014 by hgpu

Integrating Profiling into MDE Compilers

Vincent Aranega, A. Wendell O. Rodrigues, Anne Etien, Frederic Guyomarch, Jean-Luc Dekeyser

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Tags: Compilers, Computer science, nVidia, OpenCL, Tesla S1070, Tesla T10

August 3, 2014 by hgpu

Accelerating Krylov Subspace Solvers on Graphics Processing Units

Hartwig Anzt, Stanimire Tomov, Piotr Luszczek, Ichitaro Yamazaki, Jack Dongarra, William Sawyer

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Sparse matrix, Tesla K20

August 3, 2014 by hgpu

Extending Lyapack for the Solution of Band Lyapunov Equations on Hybrid CPU-GPU Platforms

Peter Benner, Ernesto Dufrechou, Pablo Ezzatti, Enrique S. Quintana-Orti, Alfredo Remon

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Tags: CUDA, Linear Algebra, Mathematics, nVidia, Tesla K20, Tesla S2070

August 3, 2014 by hgpu

Multi-Threaded Automatic Integration Using OpenMP and CUDA

Rida Assaf

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Tags: Computational finance, Computer science, CUDA, Finance, Monte Carlo integration, nVidia, OpenMP, Physics, Tesla K20, Thesis

August 3, 2014 by hgpu

Design of an FPGA-Based FDTD Accelerator Using OpenCL

Yasuhiro Takei, Hasitha Muthumala Waidyasooriya, Masanori Hariyama, Michitaka Kameyama

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Tags: Electrodynamics, Electromagnetics simulation, FDTD, Finite-difference time-domain, FPGA, nVidia, nVidia GeForce GTX 580, OpenCL

August 2, 2014 by hgpu

An Analysis of OpenACC Programming Model: Image Processing Algorithms as a Case Study

M. J. Misic, D. D. Dasic, M. V. Tomasevic

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GT 335 M, OpenACC

August 2, 2014 by hgpu

Extracting Maximal Exact Matches on GPU

Anas Abu-Doleh, Kamer Kaya, Mohamed Abouelhoda, Umit V. Catalyurek

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Tags: Algorithms, Bioinformatics, Computer science, CUDA, Indexing, nVidia, Suffix trees, Tesla K20

August 2, 2014 by hgpu

Integrated Arrival and Departure Schedule Optimization Under Uncertainty

Min Xue, Shannon Zelinski

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Tags: CUDA, Earth and Space Sciences, Monte Carlo simulation, nVidia, nVidia GeForce GTX 690, Optimization

August 2, 2014 by hgpu

CUDA Accelerated Entropy Constrained Vector Quantization and Multiple K-Means

John Ashley, Amy J. Braverman

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Tags: Compression, Computer science, CUDA, nVidia, Tesla K40, Vector quantization, Visualization

August 1, 2014 by hgpu

Scalable and High Performance Betweenness Centrality on the GPU

Adam McLaughlin, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Graph theory, Numerical simulation, nVidia, nVidia GeForce GTX Titan, Package, Tesla M2090

August 1, 2014 by hgpu

A Scalable Approach to Solving Dense Linear Algebra Problems on Hybrid CPU-GPU Systems

Fengguang Song, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K20

August 1, 2014 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

A Moving Least Squares Based Approach for Contour Visualization of Multi-Dimensional Data

Integrating Profiling into MDE Compilers

Accelerating Krylov Subspace Solvers on Graphics Processing Units

Extending Lyapack for the Solution of Band Lyapunov Equations on Hybrid CPU-GPU Platforms

Multi-Threaded Automatic Integration Using OpenMP and CUDA

Design of an FPGA-Based FDTD Accelerator Using OpenCL

An Analysis of OpenACC Programming Model: Image Processing Algorithms as a Case Study

Extracting Maximal Exact Matches on GPU

Integrated Arrival and Departure Schedule Optimization Under Uncertainty

CUDA Accelerated Entropy Constrained Vector Quantization and Multiple K-Means

Scalable and High Performance Betweenness Centrality on the GPU

A Scalable Approach to Solving Dense Linear Algebra Problems on Hybrid CPU-GPU Systems

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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