high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Realtime phase-based optical flow on the GPU

K Pauwels, M M Van Hulle

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GTX, Optical flow

March 10, 2011 by hgpu

An Efficient SAR Processor Based on GPU via CUDA

Bin Liu, Kaizhi Wang, Xingzhao Liu, Wenxian Yu

Tags: CUDA, nVidia, Signal processing

March 10, 2011 by hgpu

Using a GPU to accelerate die and mold fabrication

Masatomo Inui, Atsushi Ohta

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Tags: Algorithms, CAD, Computer science

March 10, 2011 by hgpu

A Predictive Shutdown Technique for GPU Shader Processors

Po-Han Wang, Yen-Ming Chen, Chia-Lin Yang, Yu-Jung Cheng

Tags: Computer science, Energy-efficient computing, Hardware Architecture

March 10, 2011 by hgpu

Performance analysis and optimization strategies for a D3Q19 lattice Boltzmann kernel on nVIDIA GPUs using CUDA

J. Habich, T. Zeiser, G. Hager, G. Wellein

Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia

March 10, 2011 by hgpu

Fast exhaustive search for polynomial systems in F2

Charles Bouillaguet, Hsieh C. Chen, Chen M. Cheng, Tung Chou, Ruben Niederhagen, Adi Shamir, Bo Y. Yang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Security

March 9, 2011 by hgpu

Ocelot: a dynamic optimization framework for bulk-synchronous applications in heterogeneous systems

Gregory F. Diamos, Andrew R. Kerr, Sudhakar Yalamanchili, Nathan Clark

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Programming Languages, PTX

March 9, 2011 by hgpu

Comparison of FPGA and GPU implementations of real-time stereo vision

R. Kalarot, J. Morris

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Tags: Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia GeForce GTX 280

March 9, 2011 by hgpu

Benchmarking GPU and CPU codes for Heisenberg spin glass overrelaxation

M. Bernaschi, G. Parisi, L. Parisi

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Tags: Condensed matter, CUDA, nVidia, nVidia GeForce GTX 480, Package, Physics, Spin Systems, Tesla C1060, Tesla C2050

March 9, 2011 by hgpu

GPU Computing Gems: Emerald Edition

edited by: W. W. Hwu

Tags: Algorithms, Book, Computer science, CUDA, nVidia, Programming techniques

March 9, 2011 by hgpu

Visualization of level-of-detail meshes on the GPU

Oscar Ripolles, Miguel Chover, Francisco Ramos

Tags: Computer science, Real-time graphics, Rendering, Visualization

March 9, 2011 by hgpu

GPU-RMAP: Accelerating Short-Read Mapping on Graphics Processors

Ashwin M. Aji, Liqing Zhang, Wu C. Feng

Tags: Bioinformatics, Biology, Next-Generation sequencing, nVidia

March 9, 2011 by hgpu

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

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high performance computing on graphics processing units: hgpu.org

Applications

Realtime phase-based optical flow on the GPU

An Efficient SAR Processor Based on GPU via CUDA

Using a GPU to accelerate die and mold fabrication

A Predictive Shutdown Technique for GPU Shader Processors

Performance analysis and optimization strategies for a D3Q19 lattice Boltzmann kernel on nVIDIA GPUs using CUDA

Fast exhaustive search for polynomial systems in F2

Ocelot: a dynamic optimization framework for bulk-synchronous applications in heterogeneous systems

Comparison of FPGA and GPU implementations of real-time stereo vision

Benchmarking GPU and CPU codes for Heisenberg spin glass overrelaxation

GPU Computing Gems: Emerald Edition

Visualization of level-of-detail meshes on the GPU

GPU-RMAP: Accelerating Short-Read Mapping on Graphics Processors

Recent source codes

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

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