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Analytical Characterization and Design Space Exploration for Optimization of CNNs [article]

Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan
2021 arXiv   pre-print
This paper develops an analytical modeling approach for finding the best loop-level optimization configuration for CNNs on multi-core CPUs.  ...  Experimental evaluation shows that this approach achieves comparable or better performance than state-of-the-art libraries and auto-tuning based optimizers for CNNs.  ...  A.5 Evaluation and Expected Results We run each conv2d operator 50 times with cache flush for MOpt, OneDNN, and TVM.  ... 
arXiv:2101.09808v1 fatcat:vdrzd6v4ezgbfme3mj6bz3nh7a

Pareto Optimal Design Space Exploration for Accelerated CNN on FPGA

Enrico Reggiani, Marco Rabozzi, Anna Maria Nestorov, Alberto Scolari, Luca Stornaiuolo, Marco Santambrogio
2019 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)  
Space Exploration (DSE) towards the best solution.  ...  This paper proposes a solution composed of highly configurable kernels designed for resources time-sharing with an analytical model of their resource/performance characteristics.  ...  DESIGN SPACE EXPLORATION In this Section, we describe our pareto optimal design space exploration that allows exploring CNN architectures that are both optimal in terms of throughput and DSPs resource  ... 
doi:10.1109/ipdpsw.2019.00028 dblp:conf/ipps/ReggianiRNSSS19 fatcat:otzpbg2zozdpfgd5dhs3lh5364

Improving Convolutional Neural Network Design via Variable Neighborhood Search [chapter]

Teresa Araújo, Guilherme Aresta, Bernardo Almada-Lobo, Ana Maria Mendonça, Aurélio Campilho
2017 Lecture Notes in Computer Science  
Moreover, the network shows higher predictive power and robustness, validating our method for the optimization of the CNN design.  ...  An unsupervised method for convolutional neural network (CNN) architecture design is proposed.  ...  Project "NanoSTIMA: Macro-to-Nano Human Sensing: Towards Integrated Multimodal Health Monitoring and Analytics/NORTE-01-0145-FEDER-000016" is financed by the North Portugal Regional Operational Programme  ... 
doi:10.1007/978-3-319-59876-5_41 fatcat:zspstd45k5fwldf743j4xr2joq

Using convolutional neural networks to predict composite properties beyond the elastic limit

Charles Yang, Youngsoo Kim, Seunghwa Ryu, Grace X. Gu
2019 MRS Communications  
However, the vast design space of composites and computational cost of numerical methods limit the application of high-throughput computing for optimizing composite design, especially when considering  ...  Results of this study demonstrate potential for DL to accelerate composite design optimization.  ...  Acknowledgments The authors acknowledge support from the Regents of the University of California, Berkeley and the Extreme Science and Engineering Discovery Environment (XSEDE) Bridges system at the Pittsburgh  ... 
doi:10.1557/mrc.2019.49 fatcat:ukrp6wmxnrcljhse7locrghjiu

Radiation Pattern Prediction for Metasurfaces: A Neural Network-Based Approach

Hamidreza Taghvaee, Akshay Jain, Xavier Timoneda, Christos Liaskos, Sergi Abadal, Eduard Alarcón, Albert Cabellos-Aparicio
2021 Sensors  
The aforementioned result and methodology will be of specific importance for the design, fault tolerance, and maintenance of the thousands of reconfigurable intelligent surfaces that will be deployed in  ...  complexity of an analytical model.  ...  Convolutional Neural Network Another NN that we explore for our methodology is the CNN.  ... 
doi:10.3390/s21082765 pmid:33919861 fatcat:w76brarjdvcudfrgvkgr4pco3m

Table of Contents

2021 2021 5th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)  
Novel Metaheuristic Optimization Algorithms for Sidelobe Suppression of Linear Antenna Array.........................  ...  Design and Simulation of H Shape and Duplicate U Shape Slots Microstrip Patch Antenna for WiMAX Applications ............................................................................................  ... 
doi:10.1109/ismsit52890.2021.9604758 fatcat:er7b2yejyfaphihuvwqq4logdy

Development of a Robust CNN Model for Capturing Microstructure-Property Linkages and Building Property Closures Supporting Material Design

Andrew Mann, Surya R. Kalidindi
2022 Frontiers in Materials  
This is because it allows for easy exploration of the space of valid 2-point spatial correlations, which is known to be a convex hull.  ...  Recent works have demonstrated the viability of convolutional neural networks (CNN) for capturing the highly non-linear microstructure-property linkages in high contrast composite material systems.  ...  ACKNOWLEDGMENTS The authors thank Conlain Kelly and Andreas Robertson for their helpful comments in guiding this work.  ... 
doi:10.3389/fmats.2022.851085 fatcat:hv2qbwcp2bdjfexo3vajtor2ye

Electrochemical Biosensor for SARS-CoV-2 cDNA Detection Using AuPs-Modified 3D-Printed Graphene Electrodes

Luiz Silva, Jéssica Stefano, Luiz Orzari, Laís Brazaca, Emanuel Carrilho, Luiz Marcolino-Junior, Marcio Bergamini, Rodrigo Munoz, Bruno Janegitz
2022 Biosensors  
A low-cost and disposable graphene polylactic (G-PLA) 3D-printed electrode modified with gold particles (AuPs) was explored to detect the cDNA of SARS-CoV-2 and creatinine, a potential biomarker for COVID  ...  Physicochemical characterizations were performed by SEM, EIS, FTIR, and cyclic voltammetry.  ...  /2019-9, 427731/2018-6 and 307271/2017-0), and INCTBio (CNPq grant no. 465389/2014-7) for the financial support.  ... 
doi:10.3390/bios12080622 pmid:36005018 pmcid:PMC9405530 fatcat:mbvebdbabzgvvani4a2h5mloqy

ROMANet: Fine-Grained Reuse-Driven Off-Chip Memory Access Management and Data Organization for Deep Neural Network Accelerators [article]

Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
2020 arXiv   pre-print
a design space exploration, based on the knowledge of the available on-chip memory and the data reuse factors.  ...  Therefore, searching for a solution towards the minimum DRAM access energy is an important optimization problem.  ...  . 2) We propose an analytical model to compute the number of DRAM accesses in design space exploration for a given layer partitioning and scheduling of a layer.  ... 
arXiv:1902.10222v2 fatcat:is5zntnv4nf6zlsz7lwh3gdjei

Easy over hard: a case study on deep learning

Wei Fu, Tim Menzies
2017 Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering - ESEC/FSE 2017  
We show here that applying a very simple optimizer called DE to fine tune SVM, it can achieve similar (and sometimes better) results.  ...  We offer these results as a cautionary tale to the software analytics community and suggest that not every new innovation should be applied without critical analysis.  ...  The conclusion of this work must be to stress the importance of this kind of tuning, using local data, for any future software analytics study. Better explore the searching space.  ... 
doi:10.1145/3106237.3106256 dblp:conf/sigsoft/FuM17 fatcat:6lkzxfaktnbyvpc34jkzw26zzm

How Meta-heuristic Algorithms Contribute to Deep Learning in the Hype of Big Data Analytics [chapter]

Simon Fong, Suash Deb, Xin-she Yang
2017 Advances in Intelligent Systems and Computing  
She (2018) How meta-heuristic algorithms contribute to deep learning in the hype of big data analytics.  ...  Acknowledgement The authors are thankful for the financial support from the Research Grant called "A Scalable Data Stream Mining Methodology: Stream-based Holistic Analytics and Reasoning in Parallel",  ...  FDCT/126/2014/A3, offered by the University of Macau, FST, RDAO and the FDCT of Macau SAR government.  ... 
doi:10.1007/978-981-10-3373-5_1 fatcat:66p7b6o5hnalvjppokvoaxiuue

Performance characterization of video analytics workloads in heterogeneous edge infrastructures

Daniel Rivas, Francesc Guim, Jordà Polo, David Carrera
2021 Concurrency and Computation  
This article provides a complete characterization of end-to-end video analytics across a set of hardware platforms and different neural network architectures.  ...  Finally, we extract the key conclusions of the characterization to build an experimental model to estimate performance and cost of end-to-end video analytics in different edge scenarios.  ...  and how that inevitably impacts the design of the optimal infrastructure for a given deployment.  ... 
doi:10.1002/cpe.6317 fatcat:fay3qd4jibe55fppiaasixs37q

Instantaneous Property Prediction and Inverse Design of Plasmonic Nanostructures Using Machine Learning: Current Applications and Future Directions

Xinkai Xu, Dipesh Aggarwal, Karthik Shankar
2022 Nanomaterials  
With the advent of computing power and artificial neural networks, the characterization and design process of plasmonic nanostructures can be significantly accelerated using machine learning as opposed  ...  The machine learning (ML) based methods can not only perform with high accuracy and return optical spectra and optimal design parameters, but also maintain a stable high computing efficiency without being  ...  Acknowledgments: We would like to thank the Natural Sciences and Engineering Research Council of Canada (NSERC), the National Research Council Canada (NRC), and the Future Energy Systems (FES) CFREF for  ... 
doi:10.3390/nano12040633 pmid:35214962 pmcid:PMC8874423 fatcat:xmybuqw3djerlcjzjypmsspjxa

HL-Pow: A Learning-Based Power Modeling Framework for High-Level Synthesis

Zhe Lin, Jieru Zhao, Sharad Sinha, Wei Zhang
2020 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC)  
To further facilitate power-oriented optimizations, we describe a novel design space exploration (DSE) algorithm built on top of HL-Pow to trade off between latency and power consumption.  ...  This algorithm can reach a close approximation of the real Pareto frontier while only requiring running HLS flow for 20% of design points in the entire design space.  ...  Design Space Exploration A rich body of research studies DSE for HLS.  ... 
doi:10.1109/asp-dac47756.2020.9045442 dblp:conf/aspdac/0007ZSZ20 fatcat:3bz45ch6gff7zosplubzefdv34

2020-2021 Index IEEE Transactions on Computers Vol. 70

2021 IEEE transactions on computers  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  Alignment -Design Space Exploration for Optimal Performance and Energy Architectures; TC Dec.  ... 
doi:10.1109/tc.2021.3134810 fatcat:p5otlsapynbwvjmqogj47kv5qa
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