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Turbocharging AI Factories with DPU-Accelerated Service Proxy for Kubernetes

As AI evolves to planning, research, and reasoning with agentic AI, workflows are becoming increasingly complex. To deploy agentic AI applications efficiently,…

As AI evolves to planning, research, and reasoning with agentic AI, workflows are becoming increasingly complex. To deploy agentic AI applications efficiently, AI clouds need a software-defined, hardware-accelerated application delivery controller (ADC). That enables dynamic load balancing, robust security, cloud-native multi-tenancy, and rich observability. F5 BIG-IP ADC for Kubernetes…

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LLM Inference Benchmarking: Performance Tuning with TensorRT-LLM

This is the third post in the large language model latency-throughput benchmarking series, which aims to instruct developers on how to benchmark LLM inference…

This is the third post in the large language model latency-throughput benchmarking series, which aims to instruct developers on how to benchmark LLM inference with TensorRT-LLM. See LLM Inference Benchmarking: Fundamental Concepts for background knowledge on common metrics for benchmarking and parameters. And read LLM Inference Benchmarking Guide: NVIDIA GenAI-Perf and NIM for tips on using GenAI…

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RAPIDS Adds GPU Polars Streaming, a Unified GNN API, and Zero-Code ML Speedups

RAPIDS, a suite of NVIDIA CUDA-X libraries for Python data science, released version 25.06, introducing exciting new features. These include a Polars GPU…

RAPIDS, a suite of NVIDIA CUDA-X libraries for Python data science, released version 25.06, introducing exciting new features. These include a Polars GPU streaming engine, a unified API for graph neural networks (GNNs), and acceleration for support vector machines with zero code changes required. In this blog post, we’ll explore a few of these updates. In September 2024…

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New Video: Build Self-Improving AI Agents with the NVIDIA Data Flywheel Blueprint

AI agents powered by large language models are transforming enterprise workflows, but high inference costs and latency can limit their scalability and user…

AI agents powered by large language models are transforming enterprise workflows, but high inference costs and latency can limit their scalability and user experience. To address this, NVIDIA recently announced the NVIDIA AI Blueprint for Building Data Flywheels. It’s an enterprise-ready workflow that helps optimize AI agents by automated experimentation to find efficient models that reduce…

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GeForce NOW’s 20 July Games Bring the Heat to the Cloud

The forecast this month is showing a 100% chance of epic gaming. Catch the scorching lineup of 20 titles coming to the cloud, which gamers can play whether indoors or on the go. Six new games are landing on GeForce NOW this week, including launch day titles Figment and Little Nightmares II. And to make
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Advanced NVIDIA CUDA Kernel Optimization Techniques: Handwritten PTX

As accelerated computing continues to drive application performance in all areas of AI and scientific computing, there’s a renewed interest in GPU optimization…

As accelerated computing continues to drive application performance in all areas of AI and scientific computing, there’s a renewed interest in GPU optimization techniques to ensure applications obtain the best possible performance. As an application developer, there are many ways to program GPUs, up and down the software stack. In this post, we introduce some of the different levels of the stack…

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NVIDIA Omniverse: What Developers Need to Know About Migration Away From Launcher

As part of continued efforts to ensure NVIDIA Omniverse is a developer-first platform, NVIDIA will be deprecating the Omniverse Launcher on Oct. 1. Doing so…

As part of continued efforts to ensure NVIDIA Omniverse is a developer-first platform, NVIDIA will be deprecating the Omniverse Launcher on Oct. 1. Doing so will enable a more open, integrated, and efficient development experience. Removing the Launcher will streamline how developers access essential tools and resources on the platforms they already use and trust.

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NVIDIA RTX AI Accelerates FLUX.1 Kontext — Now Available for Download

Black Forest Labs, one of the world’s leading AI research labs, just changed the game for image generation. The lab’s FLUX.1 image models have earned global attention for delivering high-quality visuals with exceptional prompt adherence. Now, with its new FLUX.1 Kontext model, the lab is fundamentally changing how users can guide and refine the image
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Optimizing FLUX.1 Kontext for Image Editing with Low-Precision Quantization

FLUX.1 Kontext, the recently released model from Black Forest Labs, is a fascinating addition to the repertoire of community image generation models. The open…

FLUX.1 Kontext, the recently released model from Black Forest Labs, is a fascinating addition to the repertoire of community image generation models. The open weights FLUX.1 Kontext [dev] variant, the focus of this post, is a model meticulously optimized for image-to-image transformation tasks. This pioneering tool stands out for its incremental image editing capabilities…

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Per-Tensor and Per-Block Scaling Strategies for Effective FP8 Training

Decorative image.In this blog post, we’ll break down the main FP8 scaling strategies—per-tensor scaling, delayed and current scaling, and per-block scaling (including the…Decorative image.

In this blog post, we’ll break down the main FP8 scaling strategies—per-tensor scaling, delayed and current scaling, and per-block scaling (including the Blackwell-backed MXFP8 format)—and explain why each is essential for maintaining numerical stability and accuracy during low-precision training. Understanding these approaches will help with choosing the right recipe for your own FP8 workflows.

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