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Kernel-Centric Optimizations for Deep Neural Networks on GPGPU

Zhaodong Chen

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Tags: Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia A100, nVidia V100, Thesis

May 26, 2024 by hgpu

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

Keller Jordan

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Tags: Computer science, Computer vision, Image processing, Machine learning, nVidia

April 7, 2024 by hgpu

Training a Vision Transformer from scratch in less than 24 hours with 1 GPU

Saghar Irandoust, Thibaut Durand, Yunduz Rakhmangulova, Wenjie Zi, Hossein Hajimirsadeghi

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Tags: Benchmarking, Computer science, Computer vision, Deep learning

November 20, 2022 by hgpu

Domain-Specific On-Device Object Detection Method

Seongju Kang, Jaegi Hwang, Kwangsue Chung

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce RTX 2060

January 9, 2022 by hgpu

FLOWER: A Comprehensive Dataflow Compiler for High-Level Synthesis

Puya Amiri, Arsene Perard-Gayot, Richard Membarth, Philipp Slusallek, Roland Leißa, Sebastian Hack

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Tags: Computer science, Computer vision, FPGA, HLS, Image processing, OpenCL

November 21, 2021 by hgpu

Progressive Semantic Segmentation

Chuong Huynh, Anh Tran, Khoa Luu, Minh Hoai

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Tags: Computer vision, Image processing, nVidia, Tesla V100

April 11, 2021 by hgpu

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera, Maurizio Martina, Muhammad Shafique

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Tags: Artificial intelligence, Benchmarking, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Medicine, Neural networks, nVidia, Tesla V100

December 27, 2020 by hgpu

Transparent Acceleration of Java-based Deep Learning Engines

Athanasios Stratikopoulos, Mihai-Cristian Olteanu, Ian Vaughan, Zoran Sevarac, Nikos Foutris, Juan Fumero, Christos Kotselidis

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Tags: AMD RX Vega 64, ATI, Computer science, Computer vision, Deep learning, Java, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

October 4, 2020 by hgpu

Applications of Deep Neural Networks

Jeff Heaton

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Tags: Book, Computer science, Computer vision, Deep learning, Neural networks, NLP, Package, Python, Security

September 20, 2020 by hgpu

A Distributed Architecture for Smart Recycling Using Machine Learning

Dimitris Ziouzios, Dimitris Tsiktsiris, Nikolaos Baras, Minas Dasygenis

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Tags: Algorithms, Cloud, Computer science, Computer vision, CUDA, Machine learning, nVidia, Security

September 6, 2020 by hgpu

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

Aditya Agarwal, Yupeng Han, Maxim Likhachev

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 1070, Package, Robotics, Tesla P100, Tesla V100

August 9, 2020 by hgpu

EDSSA: An Encoder-Decoder Semantic Segmentation Networks Accelerator on OpenCL-Based FPGA Platform

Hongzhi Huang, Yakun Wu, Mengqi Yu, Xuesong Shi, Fei Qiao, Li Luo, Qi Wei, Xinjun Liu

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Tags: Algorithm optimization, Computer science, Computer vision, FPGA, Neural networks, OpenCL

July 26, 2020 by hgpu

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

2domination

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

miniLB: Lattice Botlzmann miniapp w/SYCL

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

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high performance computing on graphics processing units: hgpu.org

Applications

Kernel-Centric Optimizations for Deep Neural Networks on GPGPU

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

Training a Vision Transformer from scratch in less than 24 hours with 1 GPU

Domain-Specific On-Device Object Detection Method

FLOWER: A Comprehensive Dataflow Compiler for High-Level Synthesis

Progressive Semantic Segmentation

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Transparent Acceleration of Java-based Deep Learning Engines

Applications of Deep Neural Networks

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

EDSSA: An Encoder-Decoder Semantic Segmentation Networks Accelerator on OpenCL-Based FPGA Platform

Recent source codes

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

EnergyUCB-Bandit

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

2domination

miniLB: Lattice Botlzmann miniapp w/SYCL

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