Memory stocks are surging as AI fuels HBM/DRAM/NAND shortages and pricing power at Micron, Samsung, SK Hynix. Click for more.

The technology uses predictive algorithms to identify frequently accessed data and move it between flash storage and high-speed memory in real time, reducing the amount of expensive DRAM a data center ...

Our research paper, "The Kubernetes Network Driver Model: A Composable Architecture for High-Performance Networking", provides a deep dive into the DRANET model and its impact. The DRANET driver ...

There’s a lot of hype around the Rust programming language, and I’m seeing it being adopted by various projects, not least the Linux kernel. However, so far it was unclear to me whether it was ...

Achieving optimal performance in GPU-centric workflows frequently requires customizing how host and device memory are allocated. For example, using "pinned" host memory for asynchronous host <-> ...

1 School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. 2 Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA. As cloud ...

Advanced Mac users may wish to manually increase the VRAM allocation on their Apple Silicon Mac for performance reasons when engaging in graphics intensive tasks like running LLMs locally, AI models, ...

Abstract: Visual working memory (VWM) allows storing goal-relevant information to guide future behavior. Prior work suggests that VWM is spatially organized and relies on spatial attention directed ...