EDN

The hidden bottleneck in LLM inference and the impact on MLPerf benchmarking

Here is how the prefill versus generation split exposes GPU structural inefficiencies in AI processor designs.
Business Wire

Red Hat Launches the llm-d Community, Powering Distributed Gen AI Inference at Scale

Forged in collaboration with founding contributors CoreWeave, Google Cloud, IBM Research and NVIDIA and joined by industry leaders AMD, Cisco, Hugging Face, Intel, Lambda and Mistral AI and university ...
Semiconductor Engineering

LLM-Based Chiplet Design Generation Framework (Univ. of Minnesota)

A new technical paper titled “MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging” was published by researchers at the University of Minnesota – Twin Cities. “As program ...
MUO on MSN

Local LLM setup: how to use RAG and an embedding model to stop wasting context

Local LLMs degrade fast when context fills up. An embedding model and RAG pipeline fixes that — and runs entirely on your ...
XDA Developers on MSN

These 5 small tweaks made my self-hosted LLM setup way more productive

Why workflow optimization matters more than massive hardware specs.