Abstract: The rapid growth of model parameters presents a significant challenge when deploying large generative models on GPU. Existing LLM runtime memory management solutions tend to maximize batch ...

Ireland were pushed all the way by Wales but held on to keep their slim title hopes alive. You can read Matt Gault's report from Dublin here, and keep an eye on the BBC Sport app and website for ...

When we talk about the cost of AI infrastructure, the focus is usually on Nvidia and GPUs — but memory is an increasingly important part of the picture. As hyperscalers prepare to build out billions ...

⭐ If you like our project, please give us a star on GitHub for the latest updates! LightMem is a lightweight and efficient memory management framework designed for Large Language Models and AI Agents.

Abstract: Processing-In-Memory (PIM) architectures alleviate the memory bottleneck in the decode phase of large language model (LLM) inference by performing operations like GEMV and Softmax in memory.

Structured memory management for OpenClaw agents using SQLite graph store, multi-view indexing, TTL pruning, and HANDOFF generation.

Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...

PCWorld explores whether PC RAM wears out, revealing that memory modules typically last 3-15 years depending on quality and usage conditions. RAM failure manifests ...

The rapid expansion of artificial-intelligence infrastructure is triggering a global memory chip shortage, as factories prioritize chips for hyperscalers over the kinds used in laptops and smartphones ...