{"title":"Energy-adaptive代码","authors":"Haewon Jeong, P. Grover","doi":"10.1109/ALLERTON.2015.7446995","DOIUrl":null,"url":null,"abstract":"We provide the first constructions of a new family of error-correcting codes called “energy-adaptive codes.” These codes are designed to enable adaptive circuit implementations that minimize the total system-level energy based on varying distances and target error probabilities. Recent work has explored fundamental limits and practical strategies for minimizing total (transmit + circuit) power, considering both power consumed in computational nodes as well as wires in the circuit. It is now established that to minimize total power, code choice and circuit-design should change with communication distances and/or target error probability. Motivated by circuit area constraints, the energy-adaptive codes adapt energy consumption as distances and/or target error probability change. These codes shrink and expand the wiring area they occupy as demands on the system change, adjusting the hardware by turning on and off non-local wires in the circuit. The code constructions are hierarchical, and use QC-LDPC codes as the basis. We estimate the decoding power savings attained by use of these codes through simulation results. Such codes can be of increasing utility as we enter the era of 1000 devices per person where designing the skilled labor for obtaining optimized designs for each system will simply be unavailable. While our first constructions are admittedly simplistic, the goal of the paper is to bring this new problem to the attention of the coding-theory community.","PeriodicalId":112948,"journal":{"name":"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Energy-adaptive codes\",\"authors\":\"Haewon Jeong, P. Grover\",\"doi\":\"10.1109/ALLERTON.2015.7446995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We provide the first constructions of a new family of error-correcting codes called “energy-adaptive codes.” These codes are designed to enable adaptive circuit implementations that minimize the total system-level energy based on varying distances and target error probabilities. Recent work has explored fundamental limits and practical strategies for minimizing total (transmit + circuit) power, considering both power consumed in computational nodes as well as wires in the circuit. It is now established that to minimize total power, code choice and circuit-design should change with communication distances and/or target error probability. Motivated by circuit area constraints, the energy-adaptive codes adapt energy consumption as distances and/or target error probability change. These codes shrink and expand the wiring area they occupy as demands on the system change, adjusting the hardware by turning on and off non-local wires in the circuit. The code constructions are hierarchical, and use QC-LDPC codes as the basis. We estimate the decoding power savings attained by use of these codes through simulation results. Such codes can be of increasing utility as we enter the era of 1000 devices per person where designing the skilled labor for obtaining optimized designs for each system will simply be unavailable. While our first constructions are admittedly simplistic, the goal of the paper is to bring this new problem to the attention of the coding-theory community.\",\"PeriodicalId\":112948,\"journal\":{\"name\":\"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ALLERTON.2015.7446995\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ALLERTON.2015.7446995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We provide the first constructions of a new family of error-correcting codes called “energy-adaptive codes.” These codes are designed to enable adaptive circuit implementations that minimize the total system-level energy based on varying distances and target error probabilities. Recent work has explored fundamental limits and practical strategies for minimizing total (transmit + circuit) power, considering both power consumed in computational nodes as well as wires in the circuit. It is now established that to minimize total power, code choice and circuit-design should change with communication distances and/or target error probability. Motivated by circuit area constraints, the energy-adaptive codes adapt energy consumption as distances and/or target error probability change. These codes shrink and expand the wiring area they occupy as demands on the system change, adjusting the hardware by turning on and off non-local wires in the circuit. The code constructions are hierarchical, and use QC-LDPC codes as the basis. We estimate the decoding power savings attained by use of these codes through simulation results. Such codes can be of increasing utility as we enter the era of 1000 devices per person where designing the skilled labor for obtaining optimized designs for each system will simply be unavailable. While our first constructions are admittedly simplistic, the goal of the paper is to bring this new problem to the attention of the coding-theory community.