high performance computing on graphics processing units: hgpu.org

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Improving the Performance of Fully Connected Neural Networks by Out-of-Place Matrix Transpose

Shaohuai Shi, Pengfei Xu, Xiaowen Chu

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Tags: Algorithms, BLAS, Caffe, Computer science, CUBLAS, CUDA, Deep learning, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1080, Package, Performance

February 14, 2017 by hgpu

cellGPU: massively parallel simulations of dynamic vertex models

Daniel M. Sussman

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Tags: Biological Physics, CUDA, nVidia, Package, Physics, Tesla K40

February 14, 2017 by hgpu

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC

Eriko Nurvitadhi, David Sheffield, Jaewoong Sim, Asit Mishra, Ganesh Venkatesh, Debbie Marr

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Tags: Algorithms, ASIC, Computer science, CUDA, Deep learning, FPGA, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Performance

February 14, 2017 by hgpu

Backpropagation Training for Fisher Vectors within Neural Networks

Patrick Wieschollek, Fabian Groh, Hendrik P.A. Lensch

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan X

February 10, 2017 by hgpu

Acceleration of low-latency gravitational wave searches using Maxwell-microarchitecture GPUs

Xiangyu Guo, Qi Chu, Shin Kee Chung, Zhihui Du, Linqing Wen

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Tags: Astrophysics, CUDA, Filtering, Gravitation, Gravitational waves, nVidia, nVidia GeForce GTX 980

February 10, 2017 by hgpu

Machines and Algorithms

Peter A Boyle

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Tags: Algorithms, Computational Physics, CUDA, HEP, High Energy Physics - Lattice, Intel Xeon Phi, nVidia, Physics, QCD, Review

February 7, 2017 by hgpu

Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets

Maciej Wielgosz, Andrzej Skoczen, Matej Mertik

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Tags: CUDA, Deep learning, Instrumentation and Detectors, Keras, LSTM, Machine learning, Neural networks, nVidia, Physics, RNN, Tesla K80, Theano

February 7, 2017 by hgpu

Introduction to the Special Issue on Digital Signal Processing in Radio Astronomy

Danny C. Price, Jonathon Kocz, Matthew Bailes, Lincoln J. Greenhill

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Tags: Astrophysics, CUDA, DSP, FPGA, nVidia, Overview, Signal processing

February 7, 2017 by hgpu

A Dynamic Programming Model To Solve Optimisation Problems Using GPUs

Jonathan Francis O'Connell

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 960, nVidia GeForce GTX Titan, Optimisation, Thesis

February 7, 2017 by hgpu

Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Yuan Yuan

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Thesis

February 7, 2017 by hgpu

Spark-GPU: An Accelerated In-Memory Data Processing Engine on Clusters

Yuan Yuan, Meisam Fathi Salmi, Yin Huai, Kaibo Wang, Rubao Lee, Xiaodong Zhang

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 770, Spark, Task scheduling

February 5, 2017 by hgpu

Fast Fourier Transforms over Prime Fields of Large Characteristic and their Implementation on Graphics Processing Units

Davood Mohajerani

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 760 M, Security, Thesis

February 5, 2017 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

Improving the Performance of Fully Connected Neural Networks by Out-of-Place Matrix Transpose

cellGPU: massively parallel simulations of dynamic vertex models

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC

Backpropagation Training for Fisher Vectors within Neural Networks

Acceleration of low-latency gravitational wave searches using Maxwell-microarchitecture GPUs

Machines and Algorithms

Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets

Introduction to the Special Issue on Digital Signal Processing in Radio Astronomy

A Dynamic Programming Model To Solve Optimisation Problems Using GPUs

Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Spark-GPU: An Accelerated In-Memory Data Processing Engine on Clusters

Fast Fourier Transforms over Prime Fields of Large Characteristic and their Implementation on Graphics Processing Units

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