Compute in‐memory with non‐volatile elements for neural networks: A review from a co‐design perspective

W Haensch, A Raghunathan, K Roy… - Advanced …, 2023 - Wiley Online Library
Deep learning has become ubiquitous, touching daily lives across the globe. Today,
traditional computer architectures are stressed to their limits in efficiently executing the …
Save Cite Cited by 33 Related articles

Compute in-Memory with Non-Volatile Elements for Neural Networks: A Review from a Co-Design Perspective.

W Haensch, A Raghunathan, K Roy… - … (Deerfield Beach, Fla …, 2022 - europepmc.org
Deep learning has become ubiquitous, touching daily lives across the globe. Today,
traditional computer architectures are stressed to their limits in efficiently executing the …
Cite

Compute in-Memory with Non-Volatile Elements for Neural Networks: A Review from a Co-Design Perspective

W Haensch, A Raghunathan, K Roy… - Advanced …, 2023 - pubmed.ncbi.nlm.nih.gov
Deep learning has become ubiquitous, touching daily lives across the globe. Today,
traditional computer architectures are stressed to their limits in efficiently executing the …
Cite

Compute in‐Memory with Non‐Volatile Elements for Neural Networks: A Review from a Co‐Design Perspective

W Haensch, A Raghunathan, K Roy, B Chakrabarti… - Advanced Materials, 2023 - osti.gov
Deep learning has become ubiquitous, touching daily lives across the globe. Today,
traditional computer architectures are stressed to their limits in efficiently executing the …
Cite

Compute in‑Memory with Non‑Volatile Elements for Neural Networks: A Review from a Co‑Design Perspective

W Haensch, A Raghunathan, K Roy… - Advanced …, 2023 - ui.adsabs.harvard.edu
Deep learning has become ubiquitous, touching daily lives across the globe. Today,
traditional computer architectures are stressed to their limits in efficiently executing the …
Cite