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MILJS: Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

Ken Miura, Tetsuaki Mano, Atsushi Kanehira, Yuichiro Tsuchiya, Tatsuya Harada

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Tags: Computer science, Java, Machine learning, Mathematical Software, OpenCL, Package, Python

March 2, 2015 by hgpu

Accelerating Deep Convolutional Neural Networks Using Specialized Hardware

Kalin Ovtcharov, Olatunji Ruwase, Joo-Young Kim, Jeremy Fowers, Karin Strauss, Eric S. Chung

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Tags: Computer science, FPGA, Machine learning, Neural networks, Speech recognition

February 27, 2015 by hgpu

Stochastic Gradient Descent on GPUs

Rashid Kaleem, Sreepathi Pai, Keshav Pingali

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Tags: Algorithms, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla K40

February 22, 2015 by hgpu

Large-Scale Deep Learning on the YFCC100M Dataset

Karl Ni, Roger Pearce, Kofi Boakye, Brian Van Essen, Damian Borth, Barry Chen, Eric Wang

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Tesla M2050

February 13, 2015 by hgpu

Sparse Matrix-Vector Multiplication on GPU

Arash Ashari

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX Titan, Sparse matrix, Tesla K10, Thesis

February 9, 2015 by hgpu

Scaling Recurrent Neural Network Language Models

Will Williams, Niranjani Prasad, David Mrva, Tom Ash, Tony Robinson

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan

February 3, 2015 by hgpu

On Vectorization of Deep Convolutional Neural Networks for Vision Tasks

Jimmy SJ. Ren, Li Xu

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Tags: CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 780 Ti, Package

January 30, 2015 by hgpu

maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs

Andrew Lavin

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Tags: Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Package

January 28, 2015 by hgpu

Revisit Long Short-Term Memory: An Optimization Perspective

Qi Lyu, Jun Zhu

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Tags: Computer science, CUDA, Machine learning, MapReduce, Neural networks, nVidia, nVidia GeForce GTX 770

January 23, 2015 by hgpu

Accelerating mahout on heterogeneous clusters using HadoopCL

Xiangyu Li

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Tags: Cluster computing, Computer science, GPU cluster, Heterogeneous systems, Java, Machine learning, MapReduce, nVidia, OpenCL, Tesla K20, Thesis

January 19, 2015 by hgpu

Image Super-Resolution Using Deep Convolutional Networks

Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang

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Tags: CNN, Computer science, CUDA, Machine learning, Neural networks, nVidia, Package

January 10, 2015 by hgpu

Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks

Albert Haque

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Tags: CUDA, Machine learning, Medicine, Neural networks, nVidia, nVidia GeForce GTX 750 Ti, Package

January 8, 2015 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

See all packages

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high performance computing on graphics processing units: hgpu.org

MILJS: Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

Accelerating Deep Convolutional Neural Networks Using Specialized Hardware

Stochastic Gradient Descent on GPUs

Large-Scale Deep Learning on the YFCC100M Dataset

Sparse Matrix-Vector Multiplication on GPU

Scaling Recurrent Neural Network Language Models

On Vectorization of Deep Convolutional Neural Networks for Vision Tasks

maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs

Revisit Long Short-Term Memory: An Optimization Perspective

Accelerating mahout on heterogeneous clusters using HadoopCL

Image Super-Resolution Using Deep Convolutional Networks

Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

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