AI workloads

A DGX SuperPOD. (Source: Nvidia)

Nvidia’s DGX AI Systems Are Faster and Smarter Than Ever

At its GTC event in San Jose today, Nvidia unveiled updates to its AI infrastructure portfolio, including its next-generation datacenter GPU, the NVIDIA Blackwell Ultra. Expanding on the Blackwell ...Full Article

Three Architecture Tips for Storage Environments Primed for AI/ML

Artificial intelligence has revolutionized the world around us, and its transformative impact stems from its ability to analyze vast amounts of data, learn from it and offer insights and ...Full Article

Nvidia Acquires Bright Computing for its HPC Cluster Management Software

GPU-maker Nvidia is broadening its enterprise software portfolio by buying HPC cluster management company Bright Computing for an undisclosed sum. Unlike Nvidia’s ongoing effort to purchase semiconductor IP company ...Full Article

New Relic, Mona Labs Partner to Provide Deep Monitoring for Production AI Workloads

New Relic’s cloud-based software stack observability platform is being combined with AI monitoring from Mona Labs to help enterprises better monitor, analyze and troubleshoot their growing production AI workloads. ...Full Article

Google’s Latest TPU v4 to Play Big Role in Google’s Growing ML Training Compute Services

GOOGLE I/O 2021 – Google CEO Sundar Pichai spoke for only one minute and 42 seconds about the company’s latest TPU v4 Tensor Processing Units during his keynote at ...Full Article

AI Demands Are Fueling Hardware Acceleration

As Moore’s law chip scaling reaches the point of diminishing returns, processor architectures are evolving to accelerate everything from AI model training and inference, data centers that support those ...Full Article

Inspur Takes OCP Beyond Hyperscalers

Inspur, China’s server leader, is expanding its AI offerings based on Open Compute Project specifications, including an OCP “cloud optimized” server geared to SAP HANA workloads and running Intel’s ...Full Article