Semiconductor Engineering

Analog IMC Attention Mechanism For Fast And Energy-Efficient LLMs (FZJ, RWTH Aachen)

A new technical paper titled “Analog in-memory computing attention mechanism for fast and energy-efficient large language models” was published by researchers at Forschungszentrum Jülich and RWTH ...
EDN

DRAM for energy- and area-efficient analog in-memory computing

Machine learning (ML), a subset of artificial intelligence (AI), has become integral to our lives. It allows us to learn and reason from data using techniques such as deep neural network algorithms.
SDxCentral

DeepSeek looks to offload simple LLM tasks to save billions of parameters

A little over a year after it upended the tech industry, DeepSeek is back with another apparent breakthrough: a means to stop current large language models (LLMs) from wasting computational depth on ...
eWeek

DeepSeek Debuts Sparse Attention for Faster, More Efficient AI

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
NextBigFuture

Analog in-memory Computing Attention Mechanism for Fast and Energy-efficient Large Language Models

A Nature paper describes an innovative analog in-memory computing (IMC) architecture tailored for the attention mechanism in large language models (LLMs). They want to drastically reduce latency and ...