high performance computing on graphics processing units: hgpu.org

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Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

Jinwei Wang, Xirong Ma, Yuanping Zhu, Jizhou Sun

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 650

January 26, 2014 by hgpu

GPU acceleration of Newton’s method for large systems of polynomial equations in double double and quad double arithmetic

Jan Verschelde, Xiangcheng Yu

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Tags: Algorithms, CUDA, Extended precision, Linear Algebra, Mathematics, nVidia, Tesla C2050, Tesla K20

January 26, 2014 by hgpu

GPU Monte Carlo scatter calculations for Cone Beam Computed Tomography

Jonas Adler

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Tags: Computed tomography, CT, CUDA, Filtering, Medicine, nVidia, nVidia Quadro 4000, Thesis, Tomography

January 26, 2014 by hgpu

A High-productivity Framework for Multi-GPU computation of Mesh-based applications

Takashi Shimokawabe, Takayuki Aoki, Naoyuki Onodera

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Tags: Computer science, CUDA, Diffusion equation, MPI, nVidia, Tesla K20

January 25, 2014 by hgpu

Accelerating a Bayesian Phylogenetic Inference Application with OpenACC

Joao Pedro de Matos Neves

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Tags: Bayesian, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 580, OpenACC

January 25, 2014 by hgpu

Performance Evaluation of the Intel Many Integrated Core Architecture for 3D Image Reconstruction in Computed Tomography

Johannes Hofmann

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Tags: Algorithms, Computed tomography, CT, CUDA, Image processing, Image reconstruction, Intel Xeon Phi, Medicine, nVidia, nVidia GeForce GTX 680, Thesis, Tomography

January 25, 2014 by hgpu

Improvement of the fused CUDA kernels performance prediction

Peter Novak

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Performance, Thesis

January 25, 2014 by hgpu

Finite differences numerical method for two-dimensional superlattice Boltzmann transport equation and case comparison of CPU(C) and GPGPU(CUDA) implementations

Dmitri Priimak

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Tags: Algorithms, Computational Physics, CUDA, Finite difference, Lattice Boltzmann model, Materials Science, nVidia, nVidia GeForce GTX 680, Physics

January 25, 2014 by hgpu

OpenSSL acceleration using Graphics Processing Units

Pedro Miguel Costa Saraiva

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, OpenCL, Security, Thesis

January 23, 2014 by hgpu

On the Portability of the OpenCL Dwarfs on Fixed and Reconfigurable Parallel Platforms

Konstantinos Krommydas, Muhsen Owaida, Christos D. Antonopoulos, Nikolaos Bellas, Wu-chun Feng

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Tags: APU, ATI, ATI Radeon HD 7970, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, OpenCL

January 23, 2014 by hgpu

clpeak – peak performance of your opencl device

Krishnaraj Bhat

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Tags: ATI, Benchmarking, Computer science, nVidia, OpenCL, Package, Performance

January 23, 2014 by hgpu

A comparison between parallelization approaches in molecular dynamics simulations on GPUs

Lorenzo Rovigatti, Petr Sulc, Istvan Z. Reguly, Flavio Romano

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, Package, Physics, Soft Condensed Matter, Tesla C2070, Tesla K10, Tesla K20

January 23, 2014 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

Applications

Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

GPU acceleration of Newton’s method for large systems of polynomial equations in double double and quad double arithmetic

GPU Monte Carlo scatter calculations for Cone Beam Computed Tomography

A High-productivity Framework for Multi-GPU computation of Mesh-based applications

Accelerating a Bayesian Phylogenetic Inference Application with OpenACC

Performance Evaluation of the Intel Many Integrated Core Architecture for 3D Image Reconstruction in Computed Tomography

Improvement of the fused CUDA kernels performance prediction

Finite differences numerical method for two-dimensional superlattice Boltzmann transport equation and case comparison of CPU(C) and GPGPU(CUDA) implementations

OpenSSL acceleration using Graphics Processing Units

On the Portability of the OpenCL Dwarfs on Fixed and Reconfigurable Parallel Platforms

clpeak – peak performance of your opencl device

A comparison between parallelization approaches in molecular dynamics simulations on GPUs

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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