ERMES: Efficient Racetrack Memory Emulation System based on FPGA.

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

With the scaling of CMOS technology almost over, non-volatile memories based on emerging technologies are gaining considerable popularity. Particularly, spintronic-based Racetrack memories (RTMs) exhibit unprecedented storage capacity, as well as reduced energy per operation and high write endurance, which make them promising candidates to revolutionize the architecture of memory sub-systems. However, since RTM exploits shifting of magnetic domains to align the required data with the access port, its read/write latency is not constant. Due to this behaviour, several performance optimizations related to the target application may be introduced either on memory architecture or data placement or both. To this purpose, specific tools able to emulate the timing characteristics of RTMs are highly desired. Unfortunately, existing software-based simulators show poor flexibility and run-time. To address such limitations, this paper presents a new emulation system for RTMs based on heterogeneous FPGA-CPU Systems-on-Chips (SoCs). Thanks to its high flexibility, the proposed emulator can be easily configured to evaluate different memory architectures. In addition, the CPU can be used to stimulate the RTM architecture under test with appropriate benchmarks, thus providing a fast self-contained evaluation environment. As case study, ERMES has been implemented within the Xilinx Zynq Ultrascale XCUZ9EG SoC to evaluate performances of several memory configurations when running benchmark applications from the MiBench suite, experiencing a speed-up higher than × 146 over software-based simulators.

Details

OriginalspracheEnglisch
TitelFPL
Seiten342-349
Seitenumfang8
ISBN (elektronisch)9781665473903
PublikationsstatusVeröffentlicht - 2022
Peer-Review-StatusJa

Externe IDs

Scopus 85149320528

Schlagworte

Forschungsprofillinien der TU Dresden