XDA Developers on MSN

TurboQuant tackles the hidden memory problem that's been limiting your local LLMs

A paper from Google could make local LLMs even easier to run.
VentureBeat

Breaking through AI’s memory wall with token warehousing

Shimon Ben-David, CTO, WEKA and Matt Marshall, Founder & CEO, VentureBeat As agentic AI moves from experiments to real production workloads, a quiet but serious infrastructure problem is coming into ...
Semiconductor Engineering

Memory Wall Problem Grows With LLMs

The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and ...

Nvidia says it can shrink LLM memory 20x without changing model weights

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory ...
TweakTown

Meta's huge 16,384 NVIDIA H100 AI GPU cluster: HBM3 memory crashed half of Llama 3 training

Meta released a new study detailing its Llama 3 405B model training, which took 54 days with the 16,384 NVIDIA H100 AI GPU cluster. During that time, 419 unexpected component failures occurred, with ...
CRN

Nvidia’s H200 GPU To One-Up H100 With 141GB Of HBM3e As Memory Race Heats Up

The H200 features 141GB of HBM3e and a 4.8 TB/s memory bandwidth, a substantial step up from Nvidia’s flagship H100 data center GPU. ‘The integration of faster and more extensive memory will ...
The Next Platform

AWS Taps Nvidia NVSwitch For Liquid Cooled, Rackscale GPU Nodes

Since the advent of distributed computing, there has been a tension between the tight coherency of memory and its compute within a node – the base level of a unit of compute – and the looser coherency ...