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Deep convolutional networks for pancreas segmentation in CT imaging

Holger R. Roth, Amal Farag, Le Lu, Evrim B. Turkbey, Ronald M. Summers

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Tags: Computed tomography, CT, CUDA, Deep learning, Medicine, Neural networks, nVidia, nVidia GeForce GTX Titan Z, Tomography

April 17, 2015 by hgpu

NBODY6++GPU: Ready for the gravitational million-body problem

Long Wang, Rainer Spurzem, Sverre Aarseth, Keigo Nitadori, Peter Berczik, M.B.N. Kouwenhoven, Thorsten Naab

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Tesla K20

April 17, 2015 by hgpu

Collaborative Diffusion on the GPU for Path-Finding in Games

Craig McMillan, Emma Hart, Kevin Chalmers

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Tags: AI, Algorithms, CUDA, Games, Graph, Search

April 15, 2015 by craigmcmillan01

GPU Accelerated Randomized Singular Value Decomposition and Its Application in Image Compression

Hao Ji, Yaohang Li

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Tags: Algorithms, Compression, CUDA, Image processing, nVidia, nVidia GeForce GTX 780

April 14, 2015 by hgpu

A Parallel Tree Pattern Query Processing Algorithm for Graph Databases using a GPGPU

Lila Shnaiderman, Oded Shmueli

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480

April 14, 2015 by hgpu

Image Classification with Pyramid Representation and Rotated Data Augmentation on Torch 7

Keven (Kedao) Wang

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GRID K520

April 14, 2015 by hgpu

GPU-based digital hologram reconstruction and particle detection

Daniel Benjamin Taylor

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Tags: Computer holography, Computer science, CUDA, nVidia, Tesla K20, Thesis

April 12, 2015 by hgpu

Framework for Batched and GPU-resident Factorization Algorithms Applied to Block Householder Transformations

Azzam Haidar, Tingxing "Tim" Dong, Stanimire Tomov, Piotr Luszczek, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, nVidia, Tesla K40

April 12, 2015 by hgpu

Batched Matrix Computations on Hardware Accelerators

Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, Linear Algebra, nVidia, Tesla K40

April 12, 2015 by hgpu

Automated GPU Kernel Transformations in Large-Scale Production Stencil Applications

Mohamed Wahib, Naoya Maruyama

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Tags: CUDA, Stencil computation

April 9, 2015 by wahibium

GPU Accelerated Strong and Branching Bisimilarity Checking

Anton Wijs

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Tags: Algorithms, Computer science, CUDA, nVidia, Package, Tesla K20

April 8, 2015 by hgpu

Enhancing Fluid Modeling with Turbulence and Acceleration

Chen Fan

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla C1060, Thesis

April 8, 2015 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Deep convolutional networks for pancreas segmentation in CT imaging

NBODY6++GPU: Ready for the gravitational million-body problem

Collaborative Diffusion on the GPU for Path-Finding in Games

GPU Accelerated Randomized Singular Value Decomposition and Its Application in Image Compression

A Parallel Tree Pattern Query Processing Algorithm for Graph Databases using a GPGPU

Image Classification with Pyramid Representation and Rotated Data Augmentation on Torch 7

GPU-based digital hologram reconstruction and particle detection

Framework for Batched and GPU-resident Factorization Algorithms Applied to Block Householder Transformations

Batched Matrix Computations on Hardware Accelerators

Automated GPU Kernel Transformations in Large-Scale Production Stencil Applications

GPU Accelerated Strong and Branching Bisimilarity Checking

Enhancing Fluid Modeling with Turbulence and Acceleration

Recent source codes

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Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

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INT v.s. FP: A framework to compare low-bit integer and float-point formats

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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