Telcos around the world are building sovereign AI factories based on the NVIDIA Cloud Partner (NCP) reference architecture, giving governments, enterprises, and...

Telcos around the world are building sovereign AI factories based on the NVIDIA Cloud Partner (NCP) reference architecture, giving governments, enterprises, and startups access to in‑country AI infrastructure with the right controls, trust, and performance. But infrastructure alone doesn’t get you to high-margin, production-ready enterprise AI services. Model sizes and reasoning workloads…

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The path from a trained AI model to production should be smooth, but rarely is. Many teams invest weeks fine-tuning models, only to discover that exporting to a...

The path from a trained AI model to production should be smooth, but rarely is. Many teams invest weeks fine-tuning models, only to discover that exporting to a deployment format breaks layers, input shapes cause runtime failures, or version mismatches silently degrade performance. These issues are collectively known as pipeline friction, and they cost organizations time, money…

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The compute capability of large GPU fleets presents unprecedented opportunities to innovate and provide value to customers in record time. Yet these...

The compute capability of large GPU fleets presents unprecedented opportunities to innovate and provide value to customers in record time. Yet these advancements come with a variety of challenges. At scale, teams are juggling heterogeneous hardware, fast‑moving software stacks, tight power envelopes, and spiky, multitenant workloads. A single hotspot, misconfigured driver, or subtle hardware fault…

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NVIDIA GB200 NVL72 introduces a fundamentally new way to build GPU clusters by extending NVIDIA NVLink coherence across an entire rack. This design enables...

NVIDIA GB200 NVL72 introduces a fundamentally new way to build GPU clusters by extending NVIDIA NVLink coherence across an entire rack. This design enables exascale performance, but it also changes the assumptions that many scheduling systems were built on. As a result, “rack-scale locality” becomes a hard constraint. When workloads cross domain boundaries, performance drops sharply…

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Distributed deep learning depends on fast, reliable GPU-to-GPU communication using the NVIDIA Collective Communication Library (NCCL). When training slows down,...

Distributed deep learning depends on fast, reliable GPU-to-GPU communication using the NVIDIA Collective Communication Library (NCCL). When training slows down, it becomes challenging to determine why and what to do next. A problem can span computation, communication, a specific rank, or underlying hardware. NVIDIA NCCL Inspector accelerates triaging by providing a lightweight and continuous…

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The next wave of enterprise productivity is being built on AI factories. As organizations deploy agentic AI systems capable of reasoning, automation, and...

The next wave of enterprise productivity is being built on AI factories. As organizations deploy agentic AI systems capable of reasoning, automation, and real-time decision-making at scale, competitive advantage increasingly depends on the infrastructure that supports them. Success requires more than raw compute. It demands a scalable, predictable foundation that can orchestrate intelligent…

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Federated learning (FL) is no longer a research curiosity—it’s a practical response to a hard constraint: the most valuable data is often the least movable....

Federated learning (FL) is no longer a research curiosity—it’s a practical response to a hard constraint: the most valuable data is often the least movable. Regulatory boundaries, data sovereignty rules, and organizational risk tolerance routinely prevent centralized aggregation. Meanwhile, sheer data gravity makes even permitted transfers slow, expensive, and fragile at scale.

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When you’re writing CUDA applications, one of the most important things you need to focus on to write great code is data transfer performance. This applies to...

When you’re writing CUDA applications, one of the most important things you need to focus on to write great code is data transfer performance. This applies to both single-GPU and multi-GPU systems alike. One of the tools you can use to understand the memory characteristics of your GPU system is NVIDIA NVbandwidth. In this blog post, we’ll explore what NVbandwidth is, how it works…

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Slurm is an open source cluster management and job scheduling system for Linux. It manages job scheduling for over 65% of TOP500 systems. Most organizations...

Slurm is an open source cluster management and job scheduling system for Linux. It manages job scheduling for over 65% of TOP500 systems. Most organizations running large-scale AI training have years of investment in Slurm job scripts, fair-share policies, and accounting workflows. The challenge is getting Slurm scheduling capabilities onto Kubernetes—the standard platform for managing GPU…

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