high performance computing on graphics processing units: hgpu.org

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Performance Comparison for Neuroscience Application Benchmarks

Andreas Herten, Thorsten Hater, Wouter Klijn, Dirk Pleiter

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Tags: Benchmarking, Computer science, CUDA, Neuroscience, nVidia, Performance, Tesla P100, Tesla V100

August 11, 2019 by hgpu

GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU

Carl Yang, Aydin Buluc, John D. Owens

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

August 11, 2019 by hgpu

Parallelization of Coherent Point Drift for patient registration

Erik Smistad

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Computer science, OpenCL, Package, Thesis

August 5, 2019 by hgpu

Mapping a Guided Image Filter on the HARP Reconfigurable Architecture Using OpenCL

Thomas Faict, Erik H. D'Hollander, Bart Goossens

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Tags: Algorithms, Benchmarking, Computer science, FPGA, Heterogeneous systems, OpenCL

August 5, 2019 by hgpu

Incremental Bounded Model Checking of Artificial Neural Networks in CUDA

Luiz H. Sena, Iury V. Bessa, Mikhail R. Gadelha, Lucas C. Cordeiro, Edjard Mota

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Tags: Computer science, CUDA, Neural networks, nVidia, Package

August 5, 2019 by hgpu

A Survey of Convolutional Neural Networks on Edge with Reconfigurable Computing

Mario P. Vestias

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Tags: CNN, Computer science, Deep learning, FPGA, Neural networks

August 5, 2019 by hgpu

GLU3.0: Fast GPU-based Parallel Sparse LU Factorization for Circuit Simulation

Shaoyi Peng, Sheldon X.-D. Tan

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX Titan X, Sparse matrix

August 5, 2019 by hgpu

FBLAS: Streaming Linear Algebra on FPGA

Tiziano De Matteis, Johannes de Fine Licht, Torsten Hoefler

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Tags: Computer science, FPGA, HLS, Linear Algebra, Package

July 28, 2019 by hgpu

A Power Efficient Neural Network Implementation on Heterogeneous FPGA and GPU Devices

Yuexuan Tu, Saad Sadiq, Yudong Tao, Mei-Ling Shyu, Shu-Ching Chen

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Tags: Computer science, Deep learning, Energy-efficient computing, FPGA, Neural networks, nVidia, nVidia Jetson TX2

July 28, 2019 by hgpu

NNS: The Case For Neural Network-based Sorting

Xiao-ke Zhu, Tai-ning Chen, Jing He, Wei Zhou

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Tags: Algorithms, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Sorting, TensorFlow

July 28, 2019 by hgpu

GPU-Accelerated Atari Emulation for Reinforcement Learning

Steven Dalton, Iuri Frosio, Michael Garland

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan V, Package, Tesla V100

July 28, 2019 by hgpu

Benchmarking TPU, GPU, and CPU Platforms for Deep Learning

Yu (Emma)Wang, Gu-Yeon Wei, David Brooks

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Tags: Benchmarking, Cloud, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Performance, Tesla V100, TPU

July 28, 2019 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

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high performance computing on graphics processing units: hgpu.org

Applications

Performance Comparison for Neuroscience Application Benchmarks

GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU

Parallelization of Coherent Point Drift for patient registration

Mapping a Guided Image Filter on the HARP Reconfigurable Architecture Using OpenCL

Incremental Bounded Model Checking of Artificial Neural Networks in CUDA

A Survey of Convolutional Neural Networks on Edge with Reconfigurable Computing

GLU3.0: Fast GPU-based Parallel Sparse LU Factorization for Circuit Simulation

FBLAS: Streaming Linear Algebra on FPGA

A Power Efficient Neural Network Implementation on Heterogeneous FPGA and GPU Devices

NNS: The Case For Neural Network-based Sorting

GPU-Accelerated Atari Emulation for Reinforcement Learning

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