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A Machine Learning Approach for Accelerating SimPL-Based Global Placement for FPGA's.

, , , и . SLIP, стр. 5:1-5:7. ACM, (2022)

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Ismail Mohamed Ismail

Ismail Moustafa Ismail

Ismail Ibrahim Ismail

Ismail Abdul Rahman Ismail

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Performance Tuning of Matrix Triple Products Based on Matrix Structure., , , , и . PARA, том 3732 из Lecture Notes in Computer Science, стр. 740-746. Springer, (2004)Session details: Keynote.. ISPD, ACM, (2019)POLAR: A High Performance Mixed-Size Wirelengh-Driven Placer With Density Constraints., , , , и . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 34 (3): 447-459 (2015)Eh?Predictor: A Deep Learning Framework to Identify Detailed Routing Short Violations From a Placed Netlist., , , , , и . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 39 (6): 1177-1190 (2020)A machine learning framework to identify detailed routing short violations from a placed netlist., , , , , , и . DAC, стр. 48:1-48:6. ACM, (2018)NTUplace4dr: A Detailed-Routing-Driven Placer for Mixed-Size Circuit Designs With Technology and Region Constraints., , , , , , , , и . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 37 (3): 669-681 (2018)An Open-Source Constraints-Driven General Partitioning Multi-Tool for VLSI Physical Design., , , , , и . ICCAD, стр. 1-9. IEEE, (2023)POLAR: placement based on novel rough legalization and refinement., , , , и . ICCAD, стр. 357-362. IEEE, (2013)The nature of optimization problem challenges in physical synthesis., , и . ACC, стр. 6057-6059. IEEE, (2013)Machine-Learning Based Delay Prediction for FPGA Technology Mapping., , , , и . SLIP, стр. 7:1-7:6. ACM, (2022)