Performance Estimation of FPGA Modules for Modular Design Methodology Using Artificial Neural Network-Reference-Cited by-同舟云学术

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Performance Estimation of FPGA Modules for Modular Design Methodology Using Artificial Neural Network

Published:2018 Issue: Volume: Page:105-118
ISSN:0302-9743
Container-title:Applied Reconfigurable Computing. Architectures, Tools, and Applications
language:
Short-container-title:

Author:

Herath Kalindu,Prakash Alok^ORCID,Srikanthan Thambipillai

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-78890-6_9

Reference26 articles.

1. Altera. https://www.altera.com/

2. CycloneII FPGAs. https://www.altera.com/products/fpga/cyclone-series/cyclone-ii/support.html

3. Increasing Productivity with Quartus II Incremental Compilation. https://goo.gl/uy225f

4. Neural Network Toolbox. https://www.mathworks.com/products/neural-network.html

5. PlanAhead Design and Analysis Tool. https://www.xilinx.com/products/design-tools/planahead.html

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Power-Efficient Mapping of Large Applications on Modern Heterogeneous FPGAs;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2021-12

2. Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design;2019 29th International Conference on Field Programmable Logic and Applications (FPL);2019-09

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