GraPhSyM: Graph Physical Synthesis Model

Author:

Agiza Ahmed1,Roy Rajarshi2,Ene Teodor Dumitru2,Godil Saad2,Reda Sherief1,Catanzaro Bryan2

Affiliation:

1. Brown University,Providence,RI,USA

2. NVIDIA,Santa Clara,CA,USA

Publisher

IEEE

Reference31 articles.

1. Fast and Accurate Estimation of Quality of Results in High-Level Synthesis with Machine Learning

2. AdderNet: Do We Really Need Multiplications in Deep Learning?

3. Using Machine Learning to Predict Path-Based Slack from Graph-Based Timing Analysis

4. Pyramid: Machine learning framework to estimate the optimal timing and resource usage of a high-level synthesis design;makrani;2019 29th International Conference on Field Programmable Logic and Applications (FPL),0

5. Bio-inspired imprecise computational blocks for efficient VLSI implementation of soft-computing applications;mahdiani;IEEE Transactions on Circuits and Systems I Regular Papers,2009

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