An Energy Consumption Model for SRAM-Based In-Memory-Computing Architectures

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AKGÜL B., Karalar T. C.

Electronics (Switzerland), vol.13, no.6, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 13 Issue: 6
  • Publication Date: 2024
  • Doi Number: 10.3390/electronics13061121
  • Journal Name: Electronics (Switzerland)
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
  • Keywords: benchmarking, energy consumption, in-memory computing, mathematical model
  • Yıldız Technical University Affiliated: Yes

Abstract

In this paper, a mathematical model for obtaining energy consumption of IMC architectures is constructed. This model provides energy estimation based on the distribution of a specific dataset. In addition, the estimation reduces the required simulation time to create an energy consumption model of SRAM-based IMC architectures. To validate our model with realistic data, the energy consumption of IMC is compared by using NeuroSim V3.0 for the CIFAR-10 and MNIST-like datasets. Furthermore, an application is created with our model to select highest performing quantization mapping based upon the parameters of energy consumption and accuracy.