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Mastering GPU orchestration for massive AI training

Training today’s largest AI models demands more than just powerful GPUs — it requires smart orchestration, efficient communication, and optimized resource use across massive clusters. From Google ...
Geeky Gadgets

Unsloth : The Secret Weapon for Faster Machine Learning Models

What if you could train massive machine learning models in half the time without compromising performance? For researchers and developers tackling the ever-growing complexity of AI, this isn’t just a ...
Network World

Nvidia turns to software to speed up its data center networking hardware for AI

New algorithms will fine-tune the performance of Nvidia Spectrum-X systems used to connect GPUs across multiple servers and even between data centers. Nvidia wants to make long-haul GPU-to-GPU ...
SDxCentral

Google opens up AI with Cloud GPU communication and agentic interfacing

AI enthusiasts rejoice, for Google has released a new open source agent solution on top of updates to its supercomputing platform in Google Cloud. The Google AI Hypercomputer now includes support for ...
Network World

Perplexity’s open-source tool to run trillion-parameter models without costly upgrades

TransferEngine enables GPU-to-GPU communication across AWS and Nvidia hardware, allowing trillion-parameter models to run on older systems. Perplexity AI has released an open-source software tool that ...
Semiconductor Engineering

Replacing GPU Compute Dies With PNM-Enabled HBM Cubes For Long-Context Decode Attention (UCSD, Columbia, Yonsei U., NVIDIA, Samsung)

A new technical paper, “AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving,” was published by researchers at UC San Diego, Columbia University, Yonsei ...