A. Kritikakou, F. Catthoor, Vasilios I. Kelefouras, C. Goutis
{"title":"Array Size Computation under Uniform Overlapping and Irregular Accesses","authors":"A. Kritikakou, F. Catthoor, Vasilios I. Kelefouras, C. Goutis","doi":"10.1145/2818643","DOIUrl":null,"url":null,"abstract":"The size required to store an array is crucial for an embedded system, as it affects the memory size, the energy per memory access, and the overall system cost. Existing techniques for finding the minimum number of resources required to store an array are less efficient for codes with large loops and not regularly occurring memory accesses. They have to approximate the accessed parts of the array leading to overestimation of the required resources. Otherwise, their exploration time is increased with an increase over the number of the different accessed parts of the array. We propose a methodology to compute the minimum resources required for storing an array which keeps the exploration time low and provides a near-optimal result for regularly and non-regularly occurring memory accesses and overlapping writes and reads.","PeriodicalId":7063,"journal":{"name":"ACM Trans. Design Autom. Electr. Syst.","volume":"115 1","pages":"22:1-22:35"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Trans. Design Autom. Electr. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2818643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The size required to store an array is crucial for an embedded system, as it affects the memory size, the energy per memory access, and the overall system cost. Existing techniques for finding the minimum number of resources required to store an array are less efficient for codes with large loops and not regularly occurring memory accesses. They have to approximate the accessed parts of the array leading to overestimation of the required resources. Otherwise, their exploration time is increased with an increase over the number of the different accessed parts of the array. We propose a methodology to compute the minimum resources required for storing an array which keeps the exploration time low and provides a near-optimal result for regularly and non-regularly occurring memory accesses and overlapping writes and reads.