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Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
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Analog Coding in Emerging Memory Systems.

Ryan V Zarcone1, Jesse H Engel2,3,4, S Burc Eryilmaz5

  • 1Redwood Center for Theoretical Neuroscience, UC Berkeley, Berkeley, CA, 94720, US. ryan.zarcone@gmail.com.

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Summary
This summary is machine-generated.

Analog memory systems offer higher storage capacities and lower complexity than digital systems. By treating storage as a communication problem, analog coding enhances performance for emerging memory technologies.

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Area of Science:

  • Materials Science
  • Computer Science
  • Electrical Engineering

Background:

  • The exponential growth in data generation necessitates advanced, high-density, low-power storage solutions.
  • Current storage paradigms quantize analog data and devices for digital systems, leading to inefficiencies.
  • Emerging multi-level memory devices store information in analog states, offering potential for greater density.

Purpose of the Study:

  • To investigate the potential of analog coding for multi-level memory devices.
  • To demonstrate that analog storage systems can outperform digital systems in capacity and efficiency.
  • To explore joint optimization strategies for analog memory systems.

Main Methods:

  • Recasting the data storage problem as a communication problem.
  • Applying principles of analog coding to multi-level memory devices, specifically phase change memory.
  • Jointly optimizing signal statistics, device characteristics, and distortion metrics for analog coding.

Main Results:

  • Analog-valued memory devices paired with analog codes achieve higher storage capacities.
  • Directly storing analog signals via joint coding reduces distortion and coding complexity.
  • Single-symbol analog codings demonstrate performance comparable to digital codings at large code lengths.

Conclusions:

  • End-to-end analog memory systems can surpass discrete systems in storage capacity.
  • Analog coding significantly lowers complexity, enabling faster and more energy-efficient data storage.
  • This approach paves the way for more efficient information storage solutions.