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GPT-Driven Source-to-Source Transformation for Generating Compilable Parallel CUDA Code for Nussinov’s Algorithm
GPT-Driven Source-to-Source Transformation for Generating Compilable Parallel CUDA Code for Nussinov’s Algorithm
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GPT-Driven Source-to-Source Transformation for Generating Compilable Parallel CUDA Code for Nussinov’s Algorithm

Palkowski, Marek ; Gruzewski, Mateusz

Electronics (Basel), 2024-01, Vol.13 (3), p.488 [Periódico revisado por pares]

Basel: MDPI AG

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Pymoo: Multi-Objective Optimization in Python
Pymoo: Multi-Objective Optimization in Python
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Pymoo: Multi-Objective Optimization in Python

Blank, Julian ; Deb, Kalyanmoy

IEEE access, 2020, Vol.8, p.89497-89509 [Periódico revisado por pares]

Piscataway: IEEE

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FPGA-Based Accelerators of Deep Learning Networks for Learning and Classification: A Review
FPGA-Based Accelerators of Deep Learning Networks for Learning and Classification: A Review
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FPGA-Based Accelerators of Deep Learning Networks for Learning and Classification: A Review

Shawahna, Ahmad ; Sait, Sadiq M. ; El-Maleh, Aiman

IEEE access, 2019, Vol.7, p.7823-7859 [Periódico revisado por pares]

Piscataway: IEEE

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4
Accelerating Fully Homomorphic Encryption Through Architecture-Centric Analysis and Optimization
Accelerating Fully Homomorphic Encryption Through Architecture-Centric Analysis and Optimization
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Accelerating Fully Homomorphic Encryption Through Architecture-Centric Analysis and Optimization

Jung, Wonkyung ; Lee, Eojin ; Kim, Sangpyo ; Kim, Jongmin ; Kim, Namhoon ; Lee, Keewoo ; Min, Chohong ; Cheon, Jung Hee ; Ahn, Jung Ho

IEEE access, 2021, Vol.9, p.98772-98789 [Periódico revisado por pares]

Piscataway: IEEE

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5
Basic Enhancement Strategies When Using Bayesian Optimization for Hyperparameter Tuning of Deep Neural Networks
Basic Enhancement Strategies When Using Bayesian Optimization for Hyperparameter Tuning of Deep Neural Networks
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Basic Enhancement Strategies When Using Bayesian Optimization for Hyperparameter Tuning of Deep Neural Networks

Cho, Hyunghun ; Kim, Yongjin ; Lee, Eunjung ; Choi, Daeyoung ; Lee, Yongjae ; Rhee, Wonjong

IEEE access, 2020, Vol.8, p.52588-52608 [Periódico revisado por pares]

Piscataway: IEEE

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6
MIMD Programs Execution Support on SIMD Machines: A Holistic Survey
MIMD Programs Execution Support on SIMD Machines: A Holistic Survey
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MIMD Programs Execution Support on SIMD Machines: A Holistic Survey

Mustafa, Dheya ; Alkhasawneh, Ruba ; Obeidat, Fadi ; Shatnawi, Ahmed S.

IEEE access, 2024-01, Vol.12, p.1-1 [Periódico revisado por pares]

Piscataway: IEEE

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7
Parallel Optimization for Large Scale Interferometric Synthetic Aperture Radar Data Processing
Parallel Optimization for Large Scale Interferometric Synthetic Aperture Radar Data Processing
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Parallel Optimization for Large Scale Interferometric Synthetic Aperture Radar Data Processing

Zhang, Weikang ; You, Haihang ; Wang, Chao ; Zhang, Hong ; Tang, Yixian

Remote sensing (Basel, Switzerland), 2023-04, Vol.15 (7), p.1850 [Periódico revisado por pares]

Basel: MDPI AG

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8
Linearized ADMM for Nonconvex Nonsmooth Optimization With Convergence Analysis
Linearized ADMM for Nonconvex Nonsmooth Optimization With Convergence Analysis
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Linearized ADMM for Nonconvex Nonsmooth Optimization With Convergence Analysis

Liu, Qinghua ; Shen, Xinyue ; Gu, Yuantao

IEEE access, 2019, Vol.7, p.76131-76144 [Periódico revisado por pares]

Piscataway: IEEE

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9
ParSCL: A Parallel and Distributed Framework to Process All Nearest Neighbor Queries on a Road Network
ParSCL: A Parallel and Distributed Framework to Process All Nearest Neighbor Queries on a Road Network
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ParSCL: A Parallel and Distributed Framework to Process All Nearest Neighbor Queries on a Road Network

Bhandari, Aavash ; Hamandawana, Prince ; Attique, Muhammad ; Cho, Hyung-Ju ; Chung, Tae-Sun

IEEE access, 2023-01, Vol.11, p.1-1 [Periódico revisado por pares]

Piscataway: IEEE

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10
Gaussian Mixture Cardinalized Probability Hypothesis Density(GM-CPHD): A Distributed Filter Based on the Intersection of Parallel Inverse Covariances
Gaussian Mixture Cardinalized Probability Hypothesis Density(GM-CPHD): A Distributed Filter Based on the Intersection of Parallel Inverse Covariances
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Gaussian Mixture Cardinalized Probability Hypothesis Density(GM-CPHD): A Distributed Filter Based on the Intersection of Parallel Inverse Covariances

Wang, Liu ; Chen, Guifen ; Chen, Guangjiao

Sensors (Basel, Switzerland), 2023-03, Vol.23 (6), p.2921 [Periódico revisado por pares]

Switzerland: MDPI AG

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