2 papers
cs.NE2024
Analog In-Memory Computing Attention Mechanism for Fast and Energy-Efficient Large Language Models
Nathan Leroux, Paul-Philipp Manea, Chirag Sudarshan +4
Transformer networks, driven by self-attention, are central to Large Language Models. In generative Transformers, self-attention uses cache memory to store token projections, avoid…
cs.ET2024
Gain Cell-Based Analog Content Addressable Memory for Dynamic Associative tasks in AI
Paul-Philipp Manea, Nathan Leroux, Emre Neftci +1
Analog Content Addressable Memories (aCAMs) have proven useful for associative in-memory computing applications like Decision Trees, Finite State Machines, and Hyper-dimensional Co…