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K-Means on GPU: A Review

Vidya Dhamdhere, Rahul G. Ghudji

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, Review

May 13, 2014 by hgpu

Atmospheric Chemistry

Istvan Lagzi, Robert Meszaros, Gyorgyi Gelybo, Adam Leelossy

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Tags: Book, Chemistry, CUDA, Earth and Space Sciences, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, Review

April 30, 2014 by hgpu

Analysis and Review of Sorting Algorithms

Gaurav Kocher, Nikita Agrawa

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Tags: Algorithms, Computer science, OpenCL, Review, Sorting

April 12, 2014 by hgpu

Literature Review: Parallel Computing on linear equations of linear elastic FEM stimulation with CUDA

Zheng Xia

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Tags: Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Review

April 9, 2014 by hgpu

Data Mining Techniques in Parallel and Distributed Environment – A Comprehensive Survey

S. Masih, S. Tanwani

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Tags: CUDA, Data mining, Databases, Review

March 31, 2014 by hgpu

Literature review: Build and Travel KD-Tree with CUDA

M. Zhou

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Tags: CUDA, Graphics, KD-tree, Raytracing, Review

March 29, 2014 by hgpu

GPU-based high-performance computing for radiation therapy

Xun Jia, Peter Ziegenhein, Steve B Jiang

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Tags: CUDA, Medicine, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 570, nVidia GeForce GTX 580, nVidia GeForce GTX 590, Physics, Radiotherapy, Review, Tesla C1060, Tesla C2050, Tesla C2070

February 9, 2014 by hgpu

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Ani Anciaux-Sedrakian, Peter Gottschling, Jean-Marc Gratien, Thomas Guignon

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Review, Tesla M2070, Tesla M2090

February 1, 2014 by hgpu

Clustering on GPU – A Brief Survey

V.Saveetha, S.Sophia, V.Anusha Sowbarnika

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Review

September 27, 2013 by hgpu

Recent progress and challenges in exploiting graphics processors in computational fluid dynamics

Kyle E Niemeyer, Chih-Jen Sung

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Source codes

Tags: Algorithms, Computational Physics, CUDA, Fluid dynamics, Lattice Boltzmann model, Navier-Stokes equations, NSEs, nVidia, OpenACC, Package, Review, Tesla C2075

September 13, 2013 by hgpu

Memory transfer optimization for a lattice Boltzmann solver on Kepler architecture nVidia GPUs

Mark Mawson, Alistair Revell

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia Quadro K5000, Performance, Review, Tesla K20

September 11, 2013 by hgpu

GPU-based simulation of brain neuron models

H. A. Du Nguyen

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Tags: CUDA, Neural networks, Neuroscience, nVidia, nVidia GeForce GT 640, Review, Tesla C2075, Thesis

September 7, 2013 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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

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high performance computing on graphics processing units: hgpu.org

K-Means on GPU: A Review

Atmospheric Chemistry

Analysis and Review of Sorting Algorithms

Literature Review: Parallel Computing on linear equations of linear elastic FEM stimulation with CUDA

Data Mining Techniques in Parallel and Distributed Environment – A Comprehensive Survey

Literature review: Build and Travel KD-Tree with CUDA

GPU-based high-performance computing for radiation therapy

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Clustering on GPU – A Brief Survey

Recent progress and challenges in exploiting graphics processors in computational fluid dynamics

Memory transfer optimization for a lattice Boltzmann solver on Kepler architecture nVidia GPUs

GPU-based simulation of brain neuron models

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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

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