Business Wire

Enfabrica Unveils Industry’s First Ethernet-Based AI Memory Fabric System for Efficient Superscaling of LLM Inference

MOUNTAIN VIEW, Calif.--(BUSINESS WIRE)--Enfabrica Corporation, an industry leader in high-performance networking silicon for artificial intelligence (AI) and accelerated computing, today announced the ...
Electronic Design

Memory-Centric Compute Speeds Searches for Machine-Learning Apps

Jim Yastic highlights Macronix's memory-centric hardware approach that accelerates in-memory search. Compute architectures are changing radically from bringing in memory using CXL on the PCI Express ...
EDN

Analog in-memory compute tackles the AI inference conundrum

An analog in-memory compute chip claims to solve the power/performance conundrum facing artificial intelligence (AI) inference applications by facilitating energy efficiency and cost reductions ...
Hosted on MSN

The associative processing unit wants to displace Nvidia's GPU as the go-to AI powerhouse by putting compute in the memory itself

GSI Gemini-I APU reduces constant data shuffling between the processor and memory systems Completes retrieval tasks up to 80% faster than comparable CPUs GSI Gemini-II APU will deliver ten times ...
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 ...
Semiconductor Engineering

Increasing AI Energy Efficiency With Compute In Memory

Skyrocketing AI compute workloads and fixed power budgets are forcing chip and system architects to take a much harder look at compute in memory (CIM), which until recently was considered little more ...