Priyank Kashyap

College of Engineering

Works (12)

Updated: December 18th, 2024 05:01

2024 article proceedings

High-Speed Receiver Transient Modeling with Generative Adversarial Networks

By: P. Kashyap* , A. Deroo*, D. Baron n , C. Wong n , T. Wu n  & P. Franzon n 

author keywords: Data-Driven; Generative; Macro-model; SerDes; Transient
Sources: Web Of Science, NC State University Libraries, Crossref
Added: August 26, 2024

2024 journal article

RD-FAXID: Ransomware Detection with FPGA-Accelerated XGBoost

ACM Transactions on Reconfigurable Technology and Systems.

By: A. Gajjar n, P. Kashyap n , A. Aysu n, P. Franzon n , Y. Choi *, C. Cheng *, G. Pedretti *, J. Ignowski *

author keywords: FPGAs; XGBoost; Binary Classification; High-Level Synthesis; Ransomware; Hardware Performance Counters; Accelerators; Machine Learning
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 15, 2024

2023 article proceedings

Generative Adversarial Network Based Adaptive Transmitter Modeling

By: P. Kashyap n , P. Ravichandiran n, D. Baron  n, C. Wong  n, T. Wu  n & P. Franzon n 

TL;DR: A data-driven approach for transmitter modeling is presented, which, coupled with prior receiver modeling work, enables end-to-end modeling of a SerDes link and reduces design time considerably, from running simulations to the final model deployment in under a week. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
Sources: ORCID, Crossref, NC State University Libraries
Added: August 19, 2023

2023 article proceedings

Thermal Estimation for 3D-ICs Through Generative Networks

By: P. Kashyap n , P. Ravichandiran n, L. Wang*, D. Baron n , C. Wong n , T. Wu n , P. Franzon n 

author keywords: 3DIC; thermal; generative; GAN; hybrid-bonding
TL;DR: This paper presents a generative approach for modeling the power to heat dissipation for a 3DIC and shows that, given the power map, the model can generate the resultant heat for the bulk, opening the door for thermally aware floorplanning. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries, Crossref
Added: August 14, 2023

2022 article proceedings

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 Goals Color Wheel
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID, Crossref
Added: October 11, 2022

2022 article proceedings

Modeling of Adaptive Receiver Performance Using Generative Adversarial Networks

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

author keywords: SerDes; receiver; behavior modeling; adaptive; generative; GAN; DFE; IBIS-AMI
TL;DR: A data-driven approach to modeling a high-speed serializer/deserializer (SerDes) receiver through generative adversarial networks (GANs) through the use of a discriminator structure that improves the training to generate a contour plot that makes it difficult to distinguish the ground truth. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID, Crossref
Added: September 19, 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 Goals Color Wheel
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: October 31, 2022

2021 journal article

2Deep: Enhancing Side-Channel Attacks on Lattice-Based Key-Exchange via 2-D Deep Learning

IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 40(6), 1217–1229.

By: P. Kashyap n , F. Aydin n, S. Potluri n, P. Franzon n  & A. Aysu n

author keywords: Resistance; Performance evaluation; Deep learning; Protocols; Power measurement; Side-channel attacks; NIST; Cross-device; data-augmentation; deep learning (DL); lattice-based key-exchange protocols; power side channels
TL;DR: 2Deep—a deep-learning (DL)-based SCA—targeting parallelized implementations of PQKE protocols, namely, Frodo and NewHope with data augmentation techniques are proposed, exploring approaches that convert 1-D time-series power measurement data into 2-D images to formulate SCA an image recognition task. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: June 10, 2021

2021 article

High Speed Receiver Modeling Using Generative Adversarial Networks

IEEE 30TH CONFERENCE ON ELECTRICAL PERFORMANCE OF ELECTRONIC PACKAGING AND SYSTEMS (EPEPS 2021).

By: P. Kashyap n , W. Pitts n, D. Baron n , C. Wong n , T. Wu n  & P. Franzon n 

author keywords: eye diagram; IBIS-AMI; generative model; generative adversarial network; GAN; receiver
TL;DR: The model is not built with domain knowledge but learned from a wide range of channel conditions and input bitstreams to generate an eye diagram, and a neural network model is developed to evaluate the generated eye diagram's relevant characteristics, such as eye height and width. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
Sources: Web Of Science, NC State University Libraries
Added: March 21, 2022

2020 chapter book

DeePar-SCA: Breaking Parallel Architectures of Lattice Cryptography via Learning Based Side-Channel Attacks

By: F. Aydin  n, P. Kashyap n , S. Potluri  n, P. Franzon  n & A. Aysu n

author keywords: Deep-learning; Power side-channels; Lattice-based key-exchange protocols
TL;DR: This paper proposes the first deep-learning based side-channel attacks on post-quantum key-exchange protocols and demonstrates single-trace deep-learning based attacks that outperform traditional attacks such as horizontal differential power analysis and template attacks by up to 900% and 25%, respectively. (via Semantic Scholar)
Sources: ORCID, Crossref
Added: October 4, 2021

2020 article

Machine Learning and Hardware security: Challenges and Opportunities -Invited Talk

2020 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER AIDED-DESIGN (ICCAD).

By: F. Regazzoni *, S. Bhasin *, A. Pour*, I. Alshaer *, F. Aydin n, A. Aysu n, V. Beroulle *, G. Di Natale * ...

author keywords: machine learning; hardware security
TL;DR: Novel applications of machine learning for hardware security, such as evaluation of post quantum cryptography hardware and extraction of physically unclonable functions from neural networks and practical model extraction attack based on electromagnetic side-channel measurements are demonstrated. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 30, 2021

2018 conference paper

An Autonomous Simultaneous Localization and Mapping Walker for Indoor Navigation

2018 IEEE 39th Sarnoff Symposium.

By: P. Kashyap* , M. Saleh*, D. Shakhbulatov * & Z. Dong

TL;DR: A smart walker, a system which guides the users to navigate in an indoor environment and achieves the lowest mean absolute error while navigating to its goal with an error of 2.15% over the path distance, is presented. (via Semantic Scholar)
Source: ORCID
Added: October 4, 2021

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