Somha, Worawit

Preferred name

Somha, Worawit

Main Affiliation

School of Industrial Education and Technology

worawit.so@kmitl.ac.th

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A filter design for blind deconvolution to decouple unknown RDF/RTN factors from complexly coupled SRAM margin variations
(2016-04-11)
Yamauchi, Hiroyuki
;
Somha, Worawit
This paper demonstrates a blind deconvolution technique for decoupling the two variation factors caused by the Random Telegraph Noise (RTN) and the Random Dopant Fluctuation (RDF). Unlike the non-blind deconvolution, the blind deconvolution has to seek both of the two unknown factors for RTN and RDF simultaneously, given only the information about the overall SRAM margin distribution. This paper proposes a new filter design technique for the Richardson-Lucy (R-L) blind deconvolutions. This allows to enjoy the benefits of the R-L algorithm while avoiding the inherent pitfall or ringing errors even in the blind deconvolution. The relative errors of the blind-deconvolution for RDF and RTN are reduced to less than 1% within only 300-iteration cycles. This is 400-times shorter than the conventional one.
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A noise suppressing filter design for reducing deconvolution error of both-directions downward sloped asymmeric RTN long-tail distributions
(2016-04-19)
Yamauchi, Hiroyuki
;
Somha, Worawit
A noise suppressing filter design technique to reduce deconvolution error of both-directions downward sloped asymmetrical long-tail distribution of the Random Telegraph Noise (RTN) is proposed. The filter is used in Lucy-Richardson-deconvolution (LRDec) iteration process. The deconvolution is required for inversely analyzing RTN long tail distribution effects on VLSI time-dependent operating margin. The proposed noise suppressing filters avoid unwanted phase misalignment between the distribution curves of feedback gain and deconvolution target for right and left tails. This results in reduction of its relative deconvolution errors by about 12-fold compared with the conventional LRDec. The accuracy of the fail-bit-count (FBC) prediction is increased by about 100-fold.
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A filter design to increase accuracy of Lucy-Richardson deconvolution for analyzing RTN mixtures effects on VLSI reliability margin
(2016-02-12)
Yamauchi, Hiroyuki
;
Somha, Worawit
;
Song, Yuan Qiang
A filter design to improve convergence characteristics in the Lucy-Richardson-deconvolution (LRDec) iterations is proposed, which is required for inversely analyzing log-mixtures 7-segmented Random Telegraph Noise (RTN) distribution effects on VLSI reliability margin. The proposed filter alleviates unwanted phase misalignment between the two distribution curves of feedback gain and deconvoluted RTN. This contributes to reduce its relative deconvolution errors by 1.5-orders of magnitude compared with the conventional LRDec. The accuracy of the fail-bit-count (FBC) prediction is increased by 10-folds while accelerating its convergence speed by 7 times of the conventional one. This contributes not to give up on a benefit of smaller iteration cycles from LRDec.
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Feedback gain phase alignment effects on convergence characteristics in Lucy-Richardson deconvolution for inversely predicting complex-shaped RTN distributions
(2015-09-28)
Yamauchi, Hiroyuki
;
Somha, Worawit
A technique to prevent deconvolution object from ringing errors in Lucy-Richardson-deconvolution (LRDec) iteration cycles is proposed, which is required for inversely analyzing complex-shaped Random Telegraph Noise (RTN) effects on SRAM margin variations. The proposed feedback gain phase alignment successfully circumvents the unwanted errors and makes it possible to avoid the need to give up on a benefit (smaller iteration cycles) from LRDec. The ringing elimination in a real LRDec analysis for the complex-shaped RTN distribution comprising three different sloped segments has been demonstrated for the first time, while exploiting a quicker convergence benefit of LRDec algorithm. The proposed technique reduces its relative errors of the complex-shaped RTN deconvolution by about 10 times, compared with the conventional LRDec.
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Ringing error prevention techniques in Lucy-Richardson deconvolution process for SRAM space-time margin variation effect screening designs
(2015-05-05)
Yamauchi, Hiroyuki
;
Somha, Worawit
This paper proposes a ringing error avoidance technique in Lucy-Richardson-deconvolution (L-R-Dcnv) process, which is used for inversely analyzing the Random Telegraph Noise (RTN) effects on overall SRAM margin variations. The proposed ringing prevention technique successfully circumvents the ringing error by reducing the phase difference between the feedback-gain and deconvolution target distributions in L-R-Dcnv iteration cycles. This avoids any unwanted positive feedbacks, resulting in no error amplification. This effectiveness has been demonstrated with applying it to a real L-R-Dcnv analysis for the effects of the RTN on the overall SRAM margin variations, while exploiting a quicker convergence benefit of L-R-Dcnv algorithm. It has been shown that the proposed technique reduces its relative errors of the RTN deconvolution by 10<sup>2</sup>~10<sup>3</sup> times compared with the conventional L-R-Dcnv. This enables to increase an accuracy of the fail-bit-count prediction based on the cumulative density function (cdf) of the convolution of the RTN with the Random Dopant Fluctuation (RDF) by over 2-orders of magnitude while accelerating its convergence speed by 7~30 times of the conventional one.
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A parallel filter technique to stabilize error-rectification behavior in RDF deconvolution process for SRAM screening test
(2016-08-29)
Yamauchi, Hiroyuki
;
Somha, Worawit
This paper proposes a parallel filter design technique for stabilizing the error rectification process in the iterative Lucy-Richardson (LR) deconvolution. The proposed filter is designed to adequately decouple the variation factors caused by the Random Dopant Fluctuation (RDF) from the complexly coupled SRAM margin variations. This allows to enjoy the benefits of the LR algorithm while avoiding the inherent pitfall or ringing behaviors even in the RDF deconvolution. The ringing elimination with the proposed filter contributes to suppress the relative errors to 7-orders of magnitude smaller than that for the conventional single filter. When compared with the conventional single filter at the number of iteration cycles of 30, a 100-fold larger error reduction is achieved.
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A segmentation kernel fitting technique to circumvent extreme deviation from exponentially descent tail distribution
(2018-07-01)
Somha, Worawit
;
Yamauchi, Hiroyuki
A segmentation kernel fitting technique has been proposed to circumvent an extreme deviation from the exponentially steeping descent tail distribution in the deconvolution. The proposed technique regenerates each segmented distribution line by finding the minimum of unconstrained multivariable function using derivative-free method. We decomposed the convolution effects of the two types of the minimum operating voltage variations caused by the spatially random threshold variation (VDD<inf>SPAT</inf>) and the temporally random threshold variation (VDD<inf>TIME</inf>), respectively. We discussed the VDD<inf>SPAT</inf> and VDD<inf>TIME</inf> effects on the SRAM fail-bit count (FBC) based on the decomposing results. It is found that the FBC estimation error for the proposed one can be reduced to almost 14-orders of magnitude smaller than that for the off-the-shell functions.
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An Error Reduction Technique in Richardson-Lucy Deconvolution Method
(2018-07-04)
Yamauchi, Hiroyuki
;
Somha, Worawit
An error reduction technique for Richardson-Lucy deconvolution (RL-deconv) is proposed. The deconvolution is indispensable technique for inversely analysing the SRAM fail-bit probability variations caused by the Random Telegraph Noise (RTN). The proposed technique reduces the phase difference between the two distributions of the deconvoluted RTN and the feedback-gain in the maximum likelihood (MLE) gradient iteration cycles. This avoids an unwanted positive feedback, resulting in a significant decrease in probability of undesired ringing occurrence. A quicker convergence benefit of the RL-deconv algorithm while avoiding the ringing is achieved. It has been demonstrated that the proposed technique reduces its relative deconvolution errors by 100 times compared with the conventional RL-deconv. This provides an increase in accuracy of the fail-bit-count prediction by over 2-orders of magnitude while accelerating its convergence speed by 33times of the conventional one.
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A mutual rectification-interference avoidance technique with cascade filters for both downward-direction tailed-RDF deconvolution
(2016-10-27)
Yamauchi, Hiroyuki
;
Somha, Worawit
This paper proposes a cascade filter design technique to avoid mutual interference in the error rectification process of the Lucy-Richardson (LR) deconvolution. The deconvolution is designed to adequately retrieve the variation factors caused by the Random Dopant Fluctuation (RDF) from the complexly coupled SRAM margin variations. The proposed filter avoids the mutual interferences between the two rectification processes for the both downward-direction-tails of the RDF caused margin distribution. The proposed filter contributes to suppress the relative errors to 7-orders of magnitude smaller than that for the conventional single filter. A 400-fold larger error reduction and a 5-times faster speed of the error reduction are achieved compared with the parallel filter.
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A phase shifting multiple filter design methodology for lucy-richardson deconvolution of log-mixtures complex RTN tail distribution
(2015-08-31)
Yamauchi, Hiroyuki
;
Somha, Worawit
A multiple structure filter design methodology to improve convergence characteristics of the Lucy-Richardson-deconvolution (LRDec) is proposed. The deconvolution is required for decoupling the Random Telegraph Noise (RTN) tail effects from overall VLSI time-dependent operating margin characteristics. The proposed parallel filter design alleviates unwanted phase misalignment between the two distributions of feedback gain and deconvolution target. This reduces the relative deconvolution errors by 1.2-orders of magnitude compared with the conventional one. The prediction accuracy of fail-bit probability is increased by 100-folds while accelerating its convergence speed by 33 times of the conventional one.

Somha, Worawit

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