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An Efficient and Robust Partial Differential Equation Solver by Flash-Based Computing in Memory.

Yueran Qi1, Yang Feng1, Jixuan Wu1

  • 1School of Information Science and Engineering, Shandong University, Qingdao 266237, China.

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This study introduces a novel flash memory computing-in-memory (CIM) partial differential equation (PDE) solver. The new solver offers high accuracy, low power, and superior noise immunity for scientific calculations.

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computing in memoryflash memorypartial differential equations

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Applied Mathematics

Background:

  • Flash memory-based computing-in-memory (CIM) architectures are increasingly used for data-intensive tasks like machine learning and scientific calculations.
  • Partial differential equation (PDE) solvers are crucial in scientific calculations, demanding high accuracy, speed, and low power consumption.

Purpose of the Study:

  • To propose a novel flash memory-based PDE solver.
  • To achieve high accuracy, low power consumption, and fast convergence in PDE solving.
  • To evaluate the solver's robustness against current noise in nanoscale devices.

Main Methods:

  • Development of a novel flash memory-based computing-in-memory (CIM) architecture for PDE solving.
  • Implementation and testing of the proposed PDE solver.
  • Analysis of noise tolerance compared to conventional Jacobi CIM solvers.

Main Results:

  • The proposed flash memory-based PDE solver demonstrates high accuracy, low power consumption, and fast iterative convergence.
  • The solver exhibits significantly enhanced noise tolerance, exceeding conventional Jacobi CIM solvers by over five times.
  • The results highlight the robustness of the proposed architecture against current noise.

Conclusions:

  • The novel flash memory-based PDE solver presents a promising solution for scientific calculations.
  • The solver meets critical requirements for accuracy, low power, and noise immunity.
  • This work contributes to the development of flash-based general-purpose computing.