high performance computing on graphics processing units: hgpu.org

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MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 980, Package

December 8, 2015 by hgpu

Scaling Deep Learning on Multiple In-Memory Processors

Lifan Xu, Dong Ping Zhang, Nuwan Jayasena

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Tags: ATI, ATI Radeon HD 7970, Computer science, Deep learning, Machine learning, OpenCL

December 8, 2015 by hgpu

The Genetic Convolutional Neural Network Model Based on Random Sample

You Zhining, Pu Yunming

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Tags: Algorithms, CNN, Computer science, CUDA, Deep learning, Genetic algorithm, Neural networks, nVidia, nVidia GeForce GTX 770

December 4, 2015 by hgpu

Auxiliary Image Regularization for Deep CNNs with Noisy Labels

Samaneh Azadi, Jiashi Feng, Stefanie Jegelka, Trevor Darrell

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia

December 1, 2015 by hgpu

Neural GPUs Learn Algorithms

Lukasz Kaiser, Ilya Sutskever

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K40

December 1, 2015 by hgpu

Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation

Philipp Kainz, Michael Pfeiffer, Martin Urschler

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Tags: Algorithms, CUDA, Deep learning, Image processing, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan Black

November 29, 2015 by hgpu

GPU-based Acceleration of Deep Convolutional Neural Networks on Mobile Platforms

Seyyed Salar Latifi Oskouei, Hossein Golestani, Mohamad Kachuee, Matin Hashemi, Hoda Mohammadzade, Soheil Ghiasi

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Tags: ARM, Computer science, Computer vision, Deep learning, Machine learning, Neural networks, RenderScript

November 25, 2015 by hgpu

Learning Representation for Scene Understanding: Epitomes, CRFs, and CNNs

Liang-Chieh Chen

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Tags: Caffe, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 650 M, OpenCV, Tesla K40, Thesis

November 24, 2015 by hgpu

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, Dongjun Shin

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Tags: ARM, Bayesian, Caffe, CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

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Tags: Caffe, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Large Scale Artificial Neural Network Training Using Multi-GPUs

Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan X, Tesla K40

November 20, 2015 by hgpu

Supervised Hashing with Deep Neural Networks

Ziming Zhang, Yuting Chen, Venkatesh Saligrama

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Tags: Computer science, CUDA, Deep learning, Hashing, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan

November 20, 2015 by hgpu

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

Scaling Deep Learning on Multiple In-Memory Processors

The Genetic Convolutional Neural Network Model Based on Random Sample

Auxiliary Image Regularization for Deep CNNs with Noisy Labels

Neural GPUs Learn Algorithms

Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation

GPU-based Acceleration of Deep Convolutional Neural Networks on Mobile Platforms

Learning Representation for Scene Understanding: Epitomes, CRFs, and CNNs

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Large Scale Artificial Neural Network Training Using Multi-GPUs

Supervised Hashing with Deep Neural Networks

Recent source codes

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

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