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NCRF++: An Open-source Neural Sequence Labeling Toolkit

Jie Yang, Yue Zhang

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Tags: CNN, Computer science, CUDA, Deep learning, LSTM, NLP, nVidia, nVidia GeForce GTX 1080, Package, Python, Torch

June 17, 2018 by hgpu

Implementing general matrix-matrix multiplication algorithm on the Intel Xeon Phi Knights Landing Processor

Raehyun Kim

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Tags: Algorithms, Computer science, Intel Xeon Phi, Linear Algebra, Matrix multiplication, Optimization

June 13, 2018 by hgpu

Assessment of various GPU acceleration strategies in text categorization processing flow

Lukasz Kordula, Maciej Wielgosz, Michal Karwatowski, Marcin Pietron, Dominik Zurek, Kazimierz Wiatr

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Tags: AMD Radeon R9 280, ATI, Computer science, NLP, nVidia, nVidia Quadro NVS 4200 M, OpenCL

June 13, 2018 by hgpu

Aspect-Driven Mixed-Precision Tuning Targeting GPUs

Ricardo Nobre, Luis Reis, Joao Bispo, Tiago Carvalho, Joao M.P. Cardoso, Stefano Cherubin, Giovanni Agosta

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Tags: AMD Vega 10 XT, ATI, Code generation, Computer science, Mixed precision, nVidia, OpenCL, Package

June 13, 2018 by hgpu

Efficient Large-scale Approximate Nearest Neighbor Search on OpenCL FPGA

Jialiang Zhang, Soroosh Khoram, Jing Li

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Tags: Computer science, FPGA, Nearest neighbour, nVidia, nVidia GeForce GTX Titan XP, OpenCL

June 13, 2018 by hgpu

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

Shizhao Chen, Jianbin Fang, Donglin Chen, Chuanfu Xu, Zheng Wang

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Tags: Computer science, Intel Xeon Phi, Machine learning, OpenMP, Performance, Sparse matrix

June 9, 2018 by hgpu

GPU Virtualization and Scheduling Methods: A Comprehensive Survey

Cheol-Ho Hong, Ivor Spence, Dimitrios S. Nikolopoulos

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Tags: Cloud, Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, OpenCL, Review, Virtualization

June 9, 2018 by hgpu

A High-efficiency FPGA-based Accelerator for Convolutional Neural Networks using Winograd Algorithm

Y. Huang, J. Shen, Z. Wang, M. Wen, C. Zhang

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Tags: Computational Complexity, Computer science, Computer vision, Deep learning, FPGA, HLS, Neural networks

June 9, 2018 by hgpu

Fast Locality Sensitive Hashing for Beam Search on GPU

Xing Shi, Shizhen Xu, Kevin Knight

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Data Structures and Algorithms, Hashing, NLP, nVidia, Tesla K20

June 9, 2018 by hgpu

clMF: A fine-grained and portable alternating least squares algorithm for parallel matrix factorization

Jing Chen, Jianbin Fanga, Weifeng Liub, Tao Tang, Canqun Yang

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Tags: AMD Radeon R9 Fury X, ATI, Computer science, Factorization, Linear Algebra, nVidia, OpenCL, Package, Tesla K20

June 2, 2018 by hgpu

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang

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Tags: Algorithms, CNN, Computer science, Deep learning, FPGA, Heterogeneous systems, Neural networks, OpenCL

June 2, 2018 by hgpu

NengoDL: Combining deep learning and neuromorphic modelling methods

Daniel Rasmussen

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Tags: Artificial intelligence, Benchmarking, Computer science, Deep learning, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Python

June 2, 2018 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

NCRF++: An Open-source Neural Sequence Labeling Toolkit

Implementing general matrix-matrix multiplication algorithm on the Intel Xeon Phi Knights Landing Processor

Assessment of various GPU acceleration strategies in text categorization processing flow

Aspect-Driven Mixed-Precision Tuning Targeting GPUs

Efficient Large-scale Approximate Nearest Neighbor Search on OpenCL FPGA

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

A High-efficiency FPGA-based Accelerator for Convolutional Neural Networks using Winograd Algorithm

Fast Locality Sensitive Hashing for Beam Search on GPU

clMF: A fine-grained and portable alternating least squares algorithm for parallel matrix factorization

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

NengoDL: Combining deep learning and neuromorphic modelling methods

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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