AI & Machine Learning

Making GPU Clusters More Efficient with NVIDIA Data Center Monitoring Tools

Ali NematiNov 25, 2025

24 sec read61 views0 listens

NVIDIA introduced new data center monitoring tools aimed at improving GPU cluster efficiency for high-performance computing tasks such as generative AI and large language models. These tools help content creators optimize resource usage and reduce inefficiencies in GPU clusters, which is crucial given the rapid scaling of GPU demands in various computational fields.

Read the full article at NVIDIA Tech Blog

Want to create content about this topic? Use Nemati AI tools to generate articles, social posts, and more.

Getting a Proprietary-Bus GPU onto PCIe Enables Cheaper Local LLMs, For Now

Hardware Haven has found a way to use a 16 GB NVidia V100 GPU for just $100 by adapting it from an SXM2 socket to PCIe, offering developers a cheaper option for running local large language models. This method could democratize access to powerful AI ...

Ali Nemati

AI & Machine LearningMay 249 sec read

[AINews] AI Engineer World's Fair - Autoresearch, Memory, World Models, Tokenmaxxing, Agentic Commerce, and Vertical AI Call for Speakers

generation by identifying specific internal features that may be causing the issue. Key Points from Reddit Discussions: PFlash: Speedup: PFlash claims to achieve up to 10x prefill speedup over vanilla llama.cpp for long-context decoding on quantized...

Ali Nemati

AI & Machine LearningMay 159 sec read

Your AI, Your Rules: Running a Local LLM with GPU Acceleration on Proxmox

The guide you've provided outlines an intricate setup for running Claude Code, an interactive terminal application designed for conversing with large language models (LLMs), on a machine that hosts llama.cpp, a C++ implementation of LLMs like Anthrop...

Ali Nemati

AI & Machine LearningApr 826 sec read

How I Stopped GGUF Models From Crashing My GPU: A Pre-flight VRAM Check

A developer created a CLI tool called gpu-memory-guard to prevent GPU out-of-memory errors when loading large AI models by accurately calculating VRAM requirements, including overhead and KV cache sizes. This matters because it helps developers avoid...

Ali Nemati

Gaming13 hours ago30 sec read

Reply: General Role-Playing:: Re: GM travails

Effective collaborative storytelling in role-playing games depends on players actively engaging with established plot hooks rather than derailing narratives with tangential or uncooperative actions. For game designers and narrative leads, this highli...

Ali Nemati

Making GPU Clusters More Efficient with NVIDIA Data Center Monitoring Tools

Related Articles

Getting a Proprietary-Bus GPU onto PCIe Enables Cheaper Local LLMs, For Now

[AINews] AI Engineer World's Fair - Autoresearch, Memory, World Models, Tokenmaxxing, Agentic Commerce, and Vertical AI Call for Speakers

Your AI, Your Rules: Running a Local LLM with GPU Acceleration on Proxmox

How I Stopped GGUF Models From Crashing My GPU: A Pre-flight VRAM Check

Reply: General Role-Playing:: Re: GM travails