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Achieving high precision in analog in-memory computing systems.

Piergiulio Mannocci1, Giacomo Larelli1, Marco Bonomi1

  • 1Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.

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|January 12, 2026
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Summary
This summary is machine-generated.

Analog in-memory computing (AIMC) offers efficient processing but faces precision limits. This review details AIMC error sources and explores mitigation techniques like error correction codes for improved hardware performance.

Keywords:
EngineeringMathematics and computingPhysics

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Area of Science:

  • Computer Engineering
  • Materials Science
  • Electrical Engineering

Background:

  • Modern computing architectures face bottlenecks from data transfer between memory and processors.
  • In-memory computing (IMC) addresses this by performing computations directly within memory.
  • Analog IMC (AIMC) using resistive memories shows promise for high-throughput, energy-efficient multiply-accumulate operations.

Purpose of the Study:

  • To comprehensively review error sources impacting precision in analog in-memory computing.
  • To survey and analyze various strategies for mitigating these errors.
  • To evaluate the hardware implementations, overheads, and tradeoffs of different mitigation techniques.

Main Methods:

  • Literature review of error mechanisms in AIMC systems.
  • Categorization and analysis of error mitigation strategies.
  • Comparative assessment of techniques including bit slicing, residue number systems, error correction codes, and mixed-precision iterative refinement.

Main Results:

  • Identified key error sources in AIMC, including noise, device variations, and circuit non-idealities.
  • Detailed various mitigation approaches and their effectiveness.
  • Analyzed the practical implications of implementing these strategies on hardware.

Conclusions:

  • Precision limitations are a critical challenge for AIMC.
  • Multiple strategies exist to enhance AIMC accuracy, each with specific hardware costs.
  • Careful selection of mitigation techniques is crucial for realizing the full potential of AIMC.