E-LIB Suche - Ergebnisse für: Goswami, Pingakshya

1

Application of Machine Learning in FPGA EDA Tool Developmen:

Goswami, Pingakshya ; Bhatia, Dinesh
IEEE Access. 11 (2023) - p. 109564-109580 , 2023

Link: https://doi.org/10.1109/..

2

Machine learning based fast and accurate High Level Synthes..:

Goswami, Pingakshya ; Schaefer, Benjamin Carrion ; Bhatia, Dinesh
Integration. 88 (2023) - p. 116-124 , 2023

Link: https://doi.org/10.1016/..

3

MLSBench: A Benchmark Set for Machine Learning based FPGA H..:

, In: 2022 IEEE 13th Latin America Symposium on Circuits and System (LASCAS),

Goswami, Pingakshya ; Shahshahani, Masoud ; Bhatia, Dinesh - p. 1-4 , 2022

Link: https://doi.org/10.1109/..

4

Predicting Post-Route Quality of Results Estimates for HLS ..:

, In: 2022 23rd International Symposium on Quality Electronic Design (ISQED),

Goswami, Pingakshya ; Bhatia, Dinesh - p. 45-50 , 2022

Link: https://doi.org/10.1109/..

5

Robust Estimation of FPGA Resources and Performance from CN..:

, In: 2022 35th International Conference on VLSI Design and 2022 21st International Conference on Embedded Systems (VLSID),

Goswami, Pingakshya ; Shahshahani, Masoud ; Bhatia, Dinesh - p. 144-149 , 2022

Link: https://doi.org/10.1109/..

6

Congestion Prediction in FPGA Using Regression Based Learni..:

Goswami, Pingakshya ; Bhatia, Dinesh
Electronics. 10 (2021) 16 - p. 1995 , 2021

Link: https://doi.org/10.3390/..

7

MLSBench: A Synthesizable Dataset of HLS Designs to Support..:

, In: Proceedings of the 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays,

Goswami, Pingakshya ; Shahshahani, Masoud ; Bhatia, Dinesh - p. 312 ff. , 2020

Link: https://dl.acm.org/doi/1..

8

Floorplanning of Partially Reconfigurable Design on Heterog..:

, In: Proceedings of the 2016 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays,

Goswami, Pingakshya ; Bhatia, Dinesh - p. 275 ff. , 2016

Link: https://dl.acm.org/doi/1..

9

Predicting Post-Route Quality of Results Estimates for HLS ..:

Goswami, Pingakshya ; Bhatia, Dinesh
http://arxiv.org/abs/2205.12397. , 2022

Link: http://arxiv.org/abs/220..

10

Automated Floorplanning for Partially Reconfigurable Design..:

Goswami, Pingakshya ; Bhatia, Dinesh
http://arxiv.org/abs/2011.11716. , 2020

Link: http://arxiv.org/abs/201..

11

Application of Machine Learning in FPGA EDA Tool Developmen:

Pingakshya Goswami ; Dinesh Bhatia
https://ieeexplore.ieee.org/document/10272331/. , 2023

Link: https://doi.org/10.1109/..

12

Congestion Prediction in FPGA Using Regression Based Learni..:

Pingakshya Goswami ; Dinesh Bhatia
https://www.mdpi.com/2079-9292/10/16/1995. , 2021

Link: https://doi.org/10.3390/..

13

Congestion Prediction in FPGA Using Regression Based Learni..:

Pingakshya Goswami ; Dinesh Bhatia
Artificial Intelligence Circuits and Systems (AICAS). , 2021

Link: https://doi.org/10.3390/..

14

MLSBench: A Synthesizable Dataset of HLS Designs to Support..:

Pingakshya Goswami ; Masoud Shahshahani
doi:10.5281/zenodo.3406667. , 2019

Link: https://zenodo.org/recor..