Christian Hakert, Kuan-Hsun Chen, Mikail Yayla, G. V. D. Brüggen, S. Blömeke, Jian-Jia Chen
{"title":"Software-Based Memory Analysis Environments for In-Memory Wear-Leveling","authors":"Christian Hakert, Kuan-Hsun Chen, Mikail Yayla, G. V. D. Brüggen, S. Blömeke, Jian-Jia Chen","doi":"10.1109/ASP-DAC47756.2020.9045418","DOIUrl":null,"url":null,"abstract":"Emerging non-volatile memory (NVM) architectures are considered as a replacement for DRAM and storage in the near future, since NVMs provide low power consumption, fast access speed, and low unit cost. Due to the lower write-endurance of NVMs, several in-memory wear-leveling techniques have been studied over the last years. Since most approaches propose or rely on specialized hardware, the techniques are often evaluated based on assumptions and in-house simulations rather than on real systems. To address this issue, we develop a setup consisting of a gem5 instance and an NVMain2.0 instance, which simulates an entire system (CPU, peripherals, etc.) together with an NVM plugged into the system. Taking a recorded memory access pattern from a low-level simulation into consideration to design and optimize wear-leveling techniques as operating system services allows a cross-layer design of wear-leveling techniques. With the insights gathered by analyzing the recorded memory access patterns, we develop a software-only wear-leveling solution, which does not require special hardware at all. This algorithm is evaluated afterwards by the full system simulation.","PeriodicalId":125112,"journal":{"name":"2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC)","volume":"14 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASP-DAC47756.2020.9045418","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Emerging non-volatile memory (NVM) architectures are considered as a replacement for DRAM and storage in the near future, since NVMs provide low power consumption, fast access speed, and low unit cost. Due to the lower write-endurance of NVMs, several in-memory wear-leveling techniques have been studied over the last years. Since most approaches propose or rely on specialized hardware, the techniques are often evaluated based on assumptions and in-house simulations rather than on real systems. To address this issue, we develop a setup consisting of a gem5 instance and an NVMain2.0 instance, which simulates an entire system (CPU, peripherals, etc.) together with an NVM plugged into the system. Taking a recorded memory access pattern from a low-level simulation into consideration to design and optimize wear-leveling techniques as operating system services allows a cross-layer design of wear-leveling techniques. With the insights gathered by analyzing the recorded memory access patterns, we develop a software-only wear-leveling solution, which does not require special hardware at all. This algorithm is evaluated afterwards by the full system simulation.