Energy-efficient and fast memristor-based serial multipliers applicable in image processing
Computation-in-memory (CIM) is a promising technique for overcoming the Von-Neumann bottleneck. Applying memristors in CIM reduces data transfer between processor and memory. Memristive CIM reduces energy consumption and processing time of data-intensive applications. Multipliers are one of the arit...
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Elsevier
2025-03-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S259012302500101X |
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| author | Seyed Erfan Fatemieh Bahareh Bagheralmoosavi Mohammad Reza Reshadinezhad |
| author_facet | Seyed Erfan Fatemieh Bahareh Bagheralmoosavi Mohammad Reza Reshadinezhad |
| author_sort | Seyed Erfan Fatemieh |
| collection | DOAJ |
| description | Computation-in-memory (CIM) is a promising technique for overcoming the Von-Neumann bottleneck. Applying memristors in CIM reduces data transfer between processor and memory. Memristive CIM reduces energy consumption and processing time of data-intensive applications. Multipliers are one of the arithmetic circuits that play a significant role in data-intensive processing applications. Serial Material Implication (IMPLY) logic design implements arithmetic circuits by applying emerging memristive technology that enables CIM Array (CIM-A). The computational complexity of IMPLY-based multipliers for use in the CIM-A architecture is a significant design challenge. Implementing IMPLY-based crossbar array-friendly multipliers and reducing their computational cycles and energy consumption are designers' goals in applying computational applications such as convolution in the basic CIM-A architecture. This work presents unsigned and signed array multipliers using serial IMPLY logic. The proposed multipliers have improved significantly compared to State-Of-the Art (SOA) by applying the proposed Partial Product Units (PPUs) and overlapping computational steps. The number of computational steps, energy consumption, and required memristors of the proposed 8-bit unsigned array multiplier are improved by up to 36 %, 31 %, and 47 % compared to the classic designs. The proposed 8-bit signed multiplier has also improved the computational steps, energy consumption, and required memristors by up to 59 %, 54 %, and 45 %. The performance of the proposed multipliers in the applications of Gaussian blur and edge detection is also investigated, and the simulation results have shown an improvement of 31 % in energy consumption and 33 % in the number of computational steps in these applications. |
| format | Article |
| id | doaj-art-df340268d9874af09d60c431450c3925 |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-df340268d9874af09d60c431450c39252025-01-22T05:43:49ZengElsevierResults in Engineering2590-12302025-03-0125104013Energy-efficient and fast memristor-based serial multipliers applicable in image processingSeyed Erfan Fatemieh0Bahareh Bagheralmoosavi1Mohammad Reza Reshadinezhad2Department of Computer Architecture, Faculty of Computer Engineering, University of Isfahan, Isfahan 8174673441, IranDepartment of Computer Architecture, Faculty of Computer Engineering, University of Isfahan, Isfahan 8174673441, IranCorresponding author.; Department of Computer Architecture, Faculty of Computer Engineering, University of Isfahan, Isfahan 8174673441, IranComputation-in-memory (CIM) is a promising technique for overcoming the Von-Neumann bottleneck. Applying memristors in CIM reduces data transfer between processor and memory. Memristive CIM reduces energy consumption and processing time of data-intensive applications. Multipliers are one of the arithmetic circuits that play a significant role in data-intensive processing applications. Serial Material Implication (IMPLY) logic design implements arithmetic circuits by applying emerging memristive technology that enables CIM Array (CIM-A). The computational complexity of IMPLY-based multipliers for use in the CIM-A architecture is a significant design challenge. Implementing IMPLY-based crossbar array-friendly multipliers and reducing their computational cycles and energy consumption are designers' goals in applying computational applications such as convolution in the basic CIM-A architecture. This work presents unsigned and signed array multipliers using serial IMPLY logic. The proposed multipliers have improved significantly compared to State-Of-the Art (SOA) by applying the proposed Partial Product Units (PPUs) and overlapping computational steps. The number of computational steps, energy consumption, and required memristors of the proposed 8-bit unsigned array multiplier are improved by up to 36 %, 31 %, and 47 % compared to the classic designs. The proposed 8-bit signed multiplier has also improved the computational steps, energy consumption, and required memristors by up to 59 %, 54 %, and 45 %. The performance of the proposed multipliers in the applications of Gaussian blur and edge detection is also investigated, and the simulation results have shown an improvement of 31 % in energy consumption and 33 % in the number of computational steps in these applications.http://www.sciencedirect.com/science/article/pii/S259012302500101XMemristorIMPLY logicMultiplierImage processingComputation-in-memoryProcessing in-memory |
| spellingShingle | Seyed Erfan Fatemieh Bahareh Bagheralmoosavi Mohammad Reza Reshadinezhad Energy-efficient and fast memristor-based serial multipliers applicable in image processing Results in Engineering Memristor IMPLY logic Multiplier Image processing Computation-in-memory Processing in-memory |
| title | Energy-efficient and fast memristor-based serial multipliers applicable in image processing |
| title_full | Energy-efficient and fast memristor-based serial multipliers applicable in image processing |
| title_fullStr | Energy-efficient and fast memristor-based serial multipliers applicable in image processing |
| title_full_unstemmed | Energy-efficient and fast memristor-based serial multipliers applicable in image processing |
| title_short | Energy-efficient and fast memristor-based serial multipliers applicable in image processing |
| title_sort | energy efficient and fast memristor based serial multipliers applicable in image processing |
| topic | Memristor IMPLY logic Multiplier Image processing Computation-in-memory Processing in-memory |
| url | http://www.sciencedirect.com/science/article/pii/S259012302500101X |
| work_keys_str_mv | AT seyederfanfatemieh energyefficientandfastmemristorbasedserialmultipliersapplicableinimageprocessing AT baharehbagheralmoosavi energyefficientandfastmemristorbasedserialmultipliersapplicableinimageprocessing AT mohammadrezareshadinezhad energyefficientandfastmemristorbasedserialmultipliersapplicableinimageprocessing |