Preprint FZJ-2024-00368

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MemSPICE: Automated Simulation and Energy Estimation Framework for MAGIC-Based Logic-in-Memory

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2023
arXiv

arXiv () [10.48550/ARXIV.2309.04868]

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Abstract: Existing logic-in-memory (LiM) research is limited to generating mappings and micro-operations. In this paper, we present~\emph{MemSPICE}, a novel framework that addresses this gap by automatically generating both the netlist and testbench needed to evaluate the LiM on a memristive crossbar. MemSPICE goes beyond conventional approaches by providing energy estimation scripts to calculate the precise energy consumption of the testbench at the SPICE level. We propose an automated framework that utilizes the mapping obtained from the SIMPLER tool to perform accurate energy estimation through SPICE simulations. To the best of our knowledge, no existing framework is capable of generating a SPICE netlist from a hardware description language. By offering a comprehensive solution for SPICE-based netlist generation, testbench creation, and accurate energy estimation, MemSPICE empowers researchers and engineers working on memristor-based LiM to enhance their understanding and optimization of energy usage in these systems. Finally, we tested the circuits from the ISCAS'85 benchmark on MemSPICE and conducted a detailed energy analysis.

Keyword(s): Emerging Technologies (cs.ET) ; Logic in Computer Science (cs.LO) ; FOS: Computer and information sciences


Contributing Institute(s):
  1. Elektronische Materialien (PGI-7)
  2. JARA Institut Green IT (PGI-10)
  3. JARA-FIT (JARA-FIT)
Research Program(s):
  1. 5233 - Memristive Materials and Devices (POF4-523) (POF4-523)
  2. BMBF 16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0398K) (BMBF-16ME0398K)

Appears in the scientific report 2023
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 Record created 2024-01-10, last modified 2024-02-26


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