Khaled Humood, Yihan Pan, Shiwei Wang, Alexander Serb, Themis Prodromakis
{"title":"为内存计算应用设计低功耗数字脉冲转换器 (DPC)","authors":"Khaled Humood, Yihan Pan, Shiwei Wang, Alexander Serb, Themis Prodromakis","doi":"10.1016/j.mejo.2024.106420","DOIUrl":null,"url":null,"abstract":"<div><div>Data converters such as analog-to-digital converters (ADCs), digital-to-analog converters (DACs), digital-to-time converters (DTCs), time-to-digital converters (TDCs), among others, are considered some of the most essential blocks in the field of integrated circuit design. In this work, we introduce a novel type of data converter known as the Digital-to-Pulse converter (DPC) and present its novel analog flow circuit implementation. The DPC system is a critical component in emerging artificial neural network accelerators and in-memory computing systems. The DPC system presented in this study offers two distinct operating modes. The first mode is the generation of a single pulse with a width that is modulated by the digital input. The second mode is an n-bit digital to discrete pulse converter, where the number of generated pulses is directly related to the value of the digital input. The proposed DPC system offers designers a high level of flexibility in shaping the characteristics of the output pulses, including the number of pulses, pulse width, and pulse amplitude. This empowers designers to accommodate different application requirements and scenarios effectively. The proposed circuit has been verified and tested using Virtuoso Cadence circuit tools in 180 nm CMOS technology with post-layout simulation and analysis. The results indicate a significant enhancement in average power consumption (<span><math><mrow><mo>∼</mo><mn>12</mn><mo>×</mo></mrow></math></span>), layout area (<span><math><mrow><mo>∼</mo><mn>5</mn><mo>×</mo></mrow></math></span>), and latency (<span><math><mrow><mo>∼</mo><mn>1</mn><mo>.</mo><mn>4</mn><mo>×</mo></mrow></math></span>) with the proposed system compared to the digital Register Transfer Level (RTL) implementation under a power supply of 1.8V and a clock frequency of 1 GHz in the Application Specific Integrated Circuits (ASIC) flow. This demonstrates the suitability of the proposed system for low-power and high-speed applications.</div></div>","PeriodicalId":49818,"journal":{"name":"Microelectronics Journal","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1879239124001243/pdfft?md5=7404a0b8217e2561fc2f63b7af8c8fb4&pid=1-s2.0-S1879239124001243-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Design of a low-power Digital-to-Pulse Converter (DPC) for in-memory-computing applications\",\"authors\":\"Khaled Humood, Yihan Pan, Shiwei Wang, Alexander Serb, Themis Prodromakis\",\"doi\":\"10.1016/j.mejo.2024.106420\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Data converters such as analog-to-digital converters (ADCs), digital-to-analog converters (DACs), digital-to-time converters (DTCs), time-to-digital converters (TDCs), among others, are considered some of the most essential blocks in the field of integrated circuit design. In this work, we introduce a novel type of data converter known as the Digital-to-Pulse converter (DPC) and present its novel analog flow circuit implementation. The DPC system is a critical component in emerging artificial neural network accelerators and in-memory computing systems. The DPC system presented in this study offers two distinct operating modes. The first mode is the generation of a single pulse with a width that is modulated by the digital input. The second mode is an n-bit digital to discrete pulse converter, where the number of generated pulses is directly related to the value of the digital input. The proposed DPC system offers designers a high level of flexibility in shaping the characteristics of the output pulses, including the number of pulses, pulse width, and pulse amplitude. This empowers designers to accommodate different application requirements and scenarios effectively. The proposed circuit has been verified and tested using Virtuoso Cadence circuit tools in 180 nm CMOS technology with post-layout simulation and analysis. The results indicate a significant enhancement in average power consumption (<span><math><mrow><mo>∼</mo><mn>12</mn><mo>×</mo></mrow></math></span>), layout area (<span><math><mrow><mo>∼</mo><mn>5</mn><mo>×</mo></mrow></math></span>), and latency (<span><math><mrow><mo>∼</mo><mn>1</mn><mo>.</mo><mn>4</mn><mo>×</mo></mrow></math></span>) with the proposed system compared to the digital Register Transfer Level (RTL) implementation under a power supply of 1.8V and a clock frequency of 1 GHz in the Application Specific Integrated Circuits (ASIC) flow. 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Design of a low-power Digital-to-Pulse Converter (DPC) for in-memory-computing applications
Data converters such as analog-to-digital converters (ADCs), digital-to-analog converters (DACs), digital-to-time converters (DTCs), time-to-digital converters (TDCs), among others, are considered some of the most essential blocks in the field of integrated circuit design. In this work, we introduce a novel type of data converter known as the Digital-to-Pulse converter (DPC) and present its novel analog flow circuit implementation. The DPC system is a critical component in emerging artificial neural network accelerators and in-memory computing systems. The DPC system presented in this study offers two distinct operating modes. The first mode is the generation of a single pulse with a width that is modulated by the digital input. The second mode is an n-bit digital to discrete pulse converter, where the number of generated pulses is directly related to the value of the digital input. The proposed DPC system offers designers a high level of flexibility in shaping the characteristics of the output pulses, including the number of pulses, pulse width, and pulse amplitude. This empowers designers to accommodate different application requirements and scenarios effectively. The proposed circuit has been verified and tested using Virtuoso Cadence circuit tools in 180 nm CMOS technology with post-layout simulation and analysis. The results indicate a significant enhancement in average power consumption (), layout area (), and latency () with the proposed system compared to the digital Register Transfer Level (RTL) implementation under a power supply of 1.8V and a clock frequency of 1 GHz in the Application Specific Integrated Circuits (ASIC) flow. This demonstrates the suitability of the proposed system for low-power and high-speed applications.
期刊介绍:
Published since 1969, the Microelectronics Journal is an international forum for the dissemination of research and applications of microelectronic systems, circuits, and emerging technologies. Papers published in the Microelectronics Journal have undergone peer review to ensure originality, relevance, and timeliness. The journal thus provides a worldwide, regular, and comprehensive update on microelectronic circuits and systems.
The Microelectronics Journal invites papers describing significant research and applications in all of the areas listed below. Comprehensive review/survey papers covering recent developments will also be considered. The Microelectronics Journal covers circuits and systems. This topic includes but is not limited to: Analog, digital, mixed, and RF circuits and related design methodologies; Logic, architectural, and system level synthesis; Testing, design for testability, built-in self-test; Area, power, and thermal analysis and design; Mixed-domain simulation and design; Embedded systems; Non-von Neumann computing and related technologies and circuits; Design and test of high complexity systems integration; SoC, NoC, SIP, and NIP design and test; 3-D integration design and analysis; Emerging device technologies and circuits, such as FinFETs, SETs, spintronics, SFQ, MTJ, etc.
Application aspects such as signal and image processing including circuits for cryptography, sensors, and actuators including sensor networks, reliability and quality issues, and economic models are also welcome.