The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
링 발진기(RO)의 노화로 인한 지연 저하를 분석하는 것은 재활용된 현장 프로그래밍 가능 게이트 어레이(FPGA)를 감지하는 효과적인 방법입니다. 그러나 배송 전에 모든 FPGA에 대해 많은 수의 RO 측정이 필요하므로 측정 비용이 증가합니다. 압축 센싱 기반의 VP(Virtual Probe)라는 통계적 성능 특성화 기술을 사용하여 비용 효율적인 재활용 FPGA 감지 방법을 제안합니다. VP 기술을 사용하면 매우 적은 수의 샘플 RO 측정을 사용하여 다이에서 RO 주파수의 공간 프로세스 변화를 정확하게 예측할 수 있습니다. 기계 학습 모델은 예측된 주파수 변화를 감독자로 사용하여 대상 FPGA를 재활용 또는 새 것으로 분류합니다. 50개의 상용 FPGA를 사용하여 실험을 통해 제안된 방법이 검출 정확도를 유지하면서 RO 측정 비용을 90% 절감한다는 것을 입증했습니다. 또한 단일 클래스 지원 벡터 머신 알고리즘을 사용하여 약 94%의 감지 정확도로 대상 FPGA를 분류했습니다.
Foisal AHMED
Nara Institute of Science and Technology (NAIST)
Michihiro SHINTANI
Nara Institute of Science and Technology (NAIST)
Michiko INOUE
Nara Institute of Science and Technology (NAIST)
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Foisal AHMED, Michihiro SHINTANI, Michiko INOUE, "Cost-Efficient Recycled FPGA Detection through Statistical Performance Characterization Framework" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 9, pp. 1045-1053, September 2020, doi: 10.1587/transfun.2019KEP0014.
Abstract: Analyzing aging-induced delay degradations of ring oscillators (ROs) is an effective way to detect recycled field-programmable gate arrays (FPGAs). However, it requires a large number of RO measurements for all FPGAs before shipping, which increases the measurement costs. We propose a cost-efficient recycled FPGA detection method using a statistical performance characterization technique called virtual probe (VP) based on compressed sensing. The VP technique enables the accurate prediction of the spatial process variation of RO frequencies on a die by using a very small number of sample RO measurements. Using the predicted frequency variation as a supervisor, the machine-learning model classifies target FPGAs as either recycled or fresh. Through experiments conducted using 50 commercial FPGAs, we demonstrate that the proposed method achieves 90% cost reduction for RO measurements while preserving the detection accuracy. Furthermore, a one-class support vector machine algorithm was used to classify target FPGAs with around 94% detection accuracy.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019KEP0014/_p
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@ARTICLE{e103-a_9_1045,
author={Foisal AHMED, Michihiro SHINTANI, Michiko INOUE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Cost-Efficient Recycled FPGA Detection through Statistical Performance Characterization Framework},
year={2020},
volume={E103-A},
number={9},
pages={1045-1053},
abstract={Analyzing aging-induced delay degradations of ring oscillators (ROs) is an effective way to detect recycled field-programmable gate arrays (FPGAs). However, it requires a large number of RO measurements for all FPGAs before shipping, which increases the measurement costs. We propose a cost-efficient recycled FPGA detection method using a statistical performance characterization technique called virtual probe (VP) based on compressed sensing. The VP technique enables the accurate prediction of the spatial process variation of RO frequencies on a die by using a very small number of sample RO measurements. Using the predicted frequency variation as a supervisor, the machine-learning model classifies target FPGAs as either recycled or fresh. Through experiments conducted using 50 commercial FPGAs, we demonstrate that the proposed method achieves 90% cost reduction for RO measurements while preserving the detection accuracy. Furthermore, a one-class support vector machine algorithm was used to classify target FPGAs with around 94% detection accuracy.},
keywords={},
doi={10.1587/transfun.2019KEP0014},
ISSN={1745-1337},
month={September},}
부
TY - JOUR
TI - Cost-Efficient Recycled FPGA Detection through Statistical Performance Characterization Framework
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1045
EP - 1053
AU - Foisal AHMED
AU - Michihiro SHINTANI
AU - Michiko INOUE
PY - 2020
DO - 10.1587/transfun.2019KEP0014
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2020
AB - Analyzing aging-induced delay degradations of ring oscillators (ROs) is an effective way to detect recycled field-programmable gate arrays (FPGAs). However, it requires a large number of RO measurements for all FPGAs before shipping, which increases the measurement costs. We propose a cost-efficient recycled FPGA detection method using a statistical performance characterization technique called virtual probe (VP) based on compressed sensing. The VP technique enables the accurate prediction of the spatial process variation of RO frequencies on a die by using a very small number of sample RO measurements. Using the predicted frequency variation as a supervisor, the machine-learning model classifies target FPGAs as either recycled or fresh. Through experiments conducted using 50 commercial FPGAs, we demonstrate that the proposed method achieves 90% cost reduction for RO measurements while preserving the detection accuracy. Furthermore, a one-class support vector machine algorithm was used to classify target FPGAs with around 94% detection accuracy.
ER -