Archit Manishbhai Gajjar

College of Engineering

Works (2)

Updated: April 11th, 2023 10:13

2022 article

FAXID: FPGA-Accelerated XGBoost Inference for Data Centers using HLS

2022 IEEE 30TH INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES (FCCM 2022), pp. 113–121.

By: A. Gajjar n, P. Kashyap n , A. Aysu n, P. Franzon n , S. Dey* & C. Cheng *

TL;DR: An FPGA-based XGBoost accelerator designed with High-Level Synthesis (HLS) tools and design flow accelerating binary classification inference is showcased, showing a latency speedup of the proposed design over state-of-art CPU and GPU implementations, including energy efficiency and cost-effectiveness. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: October 11, 2022

2022 article

RxGAN: Modeling High-Speed Receiver through Generative Adversarial Networks

MLCAD '22: PROCEEDINGS OF THE 2022 ACM/IEEE 4TH WORKSHOP ON MACHINE LEARNING FOR CAD (MLCAD), pp. 167–172.

By: P. Kashyap n , A. Gajjar n, Y. Choi *, C. Wong n , D. Baron n , T. Wu n , C. Cheng *, P. Franzon n 

Contributors: P. Kashyap n 

author keywords: SerDes; receiver; behavior modeling; adaptive; generative; measurement; GAN; DFE; IBIS-AMI
TL;DR: This work proposes a data-driven approach using generative adversarial training to model a real-world receiver with varying DFE and CTLE configurations while handling different channel conditions and bitstreams. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: October 31, 2022

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