793c3791b4e27c70fb1ad036694c1508 electronics_a2021v10n19p2427.pdf b0802ac3debee070de9ba87dd8918ffe223ea7c4 electronics_a2021v10n19p2427.pdf 57eb9bc09c623e19ac4c08d68bcea0a5baa8afedbafb5657a8ce8db5059b2ef2 electronics_a2021v10n19p2427.pdf Title: Assessment and Improvement of the Pattern Recognition Performance of Memdiode-Based Cross-Point Arrays with Randomly Distributed Stuck-at-Faults Subject: In this work, the effect of randomly distributed stuck-at faults (SAFs) in memristive cross-point array (CPA)-based single and multi-layer perceptrons (SLPs and MLPs, respectively) intended for pattern recognition tasks is investigated by means of realistic SPICE simulations. The quasi-static memdiode model (QMM) is considered here for the modelling of the synaptic weights implemented with memristors. Following the standard memristive approach, the QMM comprises two coupled equations, one for the electron transport based on the double-diode equation with a single series resistance and a second equation for the internal memory state of the device based on the so-called logistic hysteron. By modifying the state parameter in the current-voltage characteristic, SAFs of different severeness are simulated and the final outcome is analysed. Supervised ex-situ training and two well-known image datasets involving hand-written digits and human faces are employed to assess the inference accuracy of the SLP as a function of the faulty device ratio. The roles played by the memristor’s electrical parameters, line resistance, mapping strategy, image pixelation, and fault type (stuck-at-ON or stuck-at-OFF) on the CPA performance are statistically analysed following a Monte-Carlo approach. Three different re-mapping schemes to help mitigate the effect of the SAFs in the SLP inference phase are thoroughly investigated. Keywords: stuck-at fault; RRAM; pattern recognition; memristor; QMM; neural network;neuromorphics Author: Fernando L. Aguirre, Sebastián M. Pazos, Félix Palumbo, Antoni Morell, Jordi Suñé and Enrique Miranda Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Tue Oct 12 13:12:44 2021 CEST ModDate: Tue Oct 12 13:25:15 2021 CEST Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 24 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 22324401 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- MWHIBA+VnURWPalladioL Type 1 Custom yes yes no 10 0 CGPIEE+URWPalladioL-Ital Type 1 Custom yes yes no 15 0 SYBNCZ+URWPalladioL-Bold Type 1 Custom yes yes no 20 0 CYFHWR+URWPalladioL-Roma Type 1 Custom yes yes no 24 0 GIFXFT+VnURWPalladioL-Bold Type 1 Custom yes yes no 28 0 GKSXYT+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 36 0 MCBCCI+SourceSansRoman-Regular Type 1C Custom yes yes no 58 0 MCBCCM+SourceSansRoman.613wght Type 1C Custom yes yes no 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PJCLLL+CambriaMath CID TrueType Identity-H yes yes yes 235 0 PJCIKG+PalatinoLinotype,Bold TrueType WinAnsi yes yes no 244 0 PJCIKI+PalatinoLinotype TrueType WinAnsi yes yes no 247 0 PJCIKK+PalatinoLinotype,Italic TrueType WinAnsi yes yes no 250 0 PJCLLL+CambriaMath CID TrueType Identity-H yes yes yes 253 0 Jhove (Rel. 1.22.1, 2019-04-17) Date: 2022-03-10 03:05:44 CET RepresentationInformation: electronics_a2021v10n19p2427.pdf ReportingModule: PDF-hul, Rel. 1.12.1 (2019-04-17) LastModified: 2022-02-02 13:02:53 CET Size: 22324401 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 623 FreeObjects: 13 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7b69c6ba Item: Title: Previous Related Works Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@46daef40 Children: Item: Title: CPA Modelling Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@12f41634 Item: Title: Simulation Platform Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@13c27452 Item: Title: RRAM Models Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@262b2c86 Item: Title: Alternative RRAM Integration Structures Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@371a67ec Item: Title: Costs Associated with the Mitigation of SAF Effects Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@5ed828d Item: Title: Materials and Methods Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@50d0686 Children: Item: Title: Quasi-Static Memdiode Model Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7a3d45bd Item: Title: Procedure for SPICE CPA Creation, Training, and Simulation Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1e7c7811 Item: Title: Results and Discussion Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@77ec78b9 Children: Item: Title: Impact of the CPA Parasitics on the Recognition Accuracy Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1a3869f4 Item: Title: Impact of the Fault Ratio on the Inference Accuracy Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@a38d7a3 Children: Item: Title: Impact of the Normalisation Method (NM) Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@77f99a05 Item: Title: Influence of the Line Resistance (RL) and Image Size (n n) Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@63440df3 Item: Title: CPA Remapping Procedures Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@3aeaafa6 Children: Item: Title: Algorithm 1: Fault-Tolerant Adaptative Mapping Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@76a3e297 Item: Title: Algorithm 2: SWV-Minimisation-Based Row Permutation Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@4d3167f4 Item: Title: Algorithm 3: Mean-Bias-Dependent Mapping Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@ed9d034 Item: Title: Performance of the CPA-Remapping Algorithms Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@6121c9d6 Item: Title: Conclusions Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@87f383f Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@4eb7f003 Info: Title: Assessment and Improvement of the Pattern Recognition Performance of Memdiode-Based Cross-Point Arrays with Randomly Distributed Stuck-at-Faults Author: Fernando L. Aguirre, Sebastián M. Pazos, Félix Palumbo, Antoni Morell, Jordi Suñé and Enrique Miranda Subject: In this work, the effect of randomly distributed stuck-at faults (SAFs) in memristive cross-point array (CPA)-based single and multi-layer perceptrons (SLPs and MLPs, respectively) intended for pattern recognition tasks is investigated by means of realistic SPICE simulations. The quasi-static memdiode model (QMM) is considered here for the modelling of the synaptic weights implemented with memristors. Following the standard memristive approach, the QMM comprises two coupled equations, one for the electron transport based on the double-diode equation with a single series resistance and a second equation for the internal memory state of the device based on the so-called logistic hysteron. By modifying the state parameter in the current-voltage characteristic, SAFs of different severeness are simulated and the final outcome is analysed. Supervised ex-situ training and two well-known image datasets involving hand-written digits and human faces are employed to assess the inference accuracy of the SLP as a function of the faulty device ratio. The roles played by the memristor’s electrical parameters, line resistance, mapping strategy, image pixelation, and fault type (stuck-at-ON or stuck-at-OFF) on the CPA performance are statistically analysed following a Monte-Carlo approach. Three different re-mapping schemes to help mitigate the effect of the SAFs in the SLP inference phase are thoroughly investigated. 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