high performance computing on graphics processing units: hgpu.org

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DeepSpeech: Scaling up end-to-end speech recognition

Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, Andrew Y. Ng

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Tags: Computer science, CUDA, Deep learning, nVidia, Speech recognition

December 18, 2014 by hgpu

Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification

Hongsheng Li, Rui Zhao, Xiaogang Wang

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, Tesla K40

December 16, 2014 by hgpu

Multi-Centroid PSO Classification Learning on the GPU

Cain Cresswell-Miley

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Particle swarm optimization, Thesis

December 16, 2014 by hgpu

An Optimized GPU Memory Hierarchy Design for an OpenCL Kernel

Numair Khan

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Tags: Computer science, GPGPU-sim, Memory, OpenCL

December 16, 2014 by hgpu

MatConvNet – Convolutional Neural Networks for MATLAB

Andrea Vedaldi, Karel Lenc

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Tags: Computer science, CUDA, Machine learning, Mathematical Software, Neural and Evolutionary Computing, Neural networks, nVidia

December 16, 2014 by hgpu

Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning

Minjie Wang, Tianjun Xiao, Jianpeng Li, Jiaxing Zhang, Chuntao Hong, Zheng Zhang

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Tags: Computer science, CUBLAS, CUDA, Machine learning, Neural networks, nVidia

December 15, 2014 by hgpu

Analysis and Optimization Techniques for Massively Parallel Processors

Wenhao Jia

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, PTX, Tesla C2070, Thesis, Virtualization

December 15, 2014 by hgpu

Easy-to-Use On-the-Fly Binary Program Acceleration on Many-Cores

Marvin Damschen, Christian Plessl

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Tags: Computer science, Intel Xeon Phi, Package, Performance

December 15, 2014 by hgpu

Performance Comparison of GPUs with a Genetic Algorithm based on CUDA

Jae-Hyun Seo, Eun-Sol Ko, Yong-Hyuk Kim

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Tags: Algorithms, Computer science, CUDA, Genetic algorithm, nVidia, nVidia GeForce GT 430, nVidia GeForce GTX 260, nVidia GeForce GTX 760, nVidia GeForce GTX 770

December 15, 2014 by hgpu

Bamboo: Automatic Translation of MPI Source into a Latency-Tolerant Form

Nhat Tan Nguyen Thanh

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Tags: Computer science, CUDA, Linear Algebra, MPI, nVidia, Package, Tesla K20, Thesis

December 15, 2014 by hgpu

Heuristics for Conversion Process of GPU’s Kernels for Multiples Kernels with Concurrent Optimization Divergence

Jose Ritomar Carneiro Torquato, Esteban Walter Gonzalez Clua

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Performance, Tesla K10, Tesla K20

December 14, 2014 by hgpu

Locality-Aware Automatic Parallelization for GPGPU with OpenHMPP Directives

Jose M. Andion, Manuel Arenaz, Francois Bodin, Gabriel Rodriguez, Juan Tourino

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Tags: Computer science, CUDA, Heterogeneous systems, Matrix multiplication, nVidia, Tesla S1070, Tesla S2050

December 14, 2014 by hgpu

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

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

DeepSpeech: Scaling up end-to-end speech recognition

Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification

Multi-Centroid PSO Classification Learning on the GPU

An Optimized GPU Memory Hierarchy Design for an OpenCL Kernel

MatConvNet – Convolutional Neural Networks for MATLAB

Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning

Analysis and Optimization Techniques for Massively Parallel Processors

Easy-to-Use On-the-Fly Binary Program Acceleration on Many-Cores

Performance Comparison of GPUs with a Genetic Algorithm based on CUDA

Bamboo: Automatic Translation of MPI Source into a Latency-Tolerant Form

Heuristics for Conversion Process of GPU’s Kernels for Multiples Kernels with Concurrent Optimization Divergence

Locality-Aware Automatic Parallelization for GPGPU with OpenHMPP Directives

Recent source codes

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

SW#SYCL

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

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

HiRep

Gaia AVU-GSR

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

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