WinBuzzer

AI: Memory Bottleneck Emerges as Main LLM Inference Challenge

Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.
EDN

Why memory swizzling is hidden tax on AI compute

Walk into any modern AI lab, data center, or autonomous vehicle development environment, and you’ll hear engineers talk endlessly about FLOPS, TOPS, sparsity, quantization, and model scaling laws.
The Next Platform

With “Big Chip,” China Lays Out Aspirations For Waferscale

The end of Moore’s Law – the real Moore’s Law where transistors get cheaper and faster with every process shrink – is making chip makers crazy. And there are two different approaches to making more ...
Seeking Alpha

WiMi Develops a Quantum Technology-Based Random Access Memory Architecture

BEIJING, Dec. 26, 2024 /PRNewswire/ -- WiMi Hologram Cloud Inc. (WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the ...
Semiconductor Engineering

LtRAM And StRAM: Specialized Memory Architectures Leveraging Workload-Specific Access Characteristics (Stanford, Microsoft)

A new technical paper titled “Towards Memory Specialization: A Case for Long-Term and Short-Term RAM” was published by researchers at Stanford University and Microsoft, and an independent researcher. ...