Skip to content
AI NEWS JOURNAL
SemiEngineeringAI NEWS / JOURNAL

Analog Superposition Increases Effective PCM Storage Density (IBM Research Europe)

Researchers at IBM Research Europe published “Superposed analog memory for vector storage in neural networks.” Summary: Researchers demonstrated an analog phase-change memory architecture that stores multiple AI vectors in superposition, increasing effective storage density with a tunable accuracy tradeoff. Tests on prototype PCM hardware showed inference accuracy close to full-precision software. Find the technical paper here.... » read more The post Analog Superposition Increases Effective PCM Storage Density (IBM Research Europe) appeared first on Semiconductor Engineering.

Researchers at IBM Research Europe published “Superposed analog memory for vector storage in neural networks.”

Summary:

Researchers demonstrated an analog phase-change memory architecture that stores multiple AI vectors in superposition, increasing effective storage density with a tunable accuracy tradeoff. Tests on prototype PCM hardware showed inference accuracy close to full-precision software.

Find the technical paper here. October 2026

Vasilopoulos, Athanasios, Patrick Diener, Michael Hersche, Abbas Rahimi, and Abu Sebastian. “Superposed analog memory for vector storage in neural networks.” arXiv preprint arXiv:2610.26118 (2026). CC BY-NC-SA 4.0 License

The post Analog Superposition Increases Effective PCM Storage Density (IBM Research Europe) appeared first on Semiconductor Engineering.

Sources

SemiEngineering
← Continue to all updates