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Training vs Inference: Why Your AI Network Architecture Needs to Be Different

Training vs Inference: Why Your AI Network Architecture Needs to Be Different

AI training and inference have fundamentally different network requirements. Learn how the shift from training to inference workloads is driving the rise of RoCE—and how NADDOD's RoCEv2 solutions deliver the performance, cost efficiency, and scalability your AI infrastructure needs.

NADDOD × DGX Spark × OpenClaw: A Practical Guide to Local AI Agent Cluster Deployment

NADDOD × DGX Spark × OpenClaw: A Practical Guide to Local AI Agent Cluster Deployment

Learn how to deploy OpenClaw on NVIDIA DGX Spark with NADDOD's high-performance network solutions. A practical guide to building a secure, scalable local AI agent cluster for enterprises.

NVIDIA MGX Ecosystem: Building Modular Infrastructure for AI Factories

NVIDIA MGX Ecosystem: Building Modular Infrastructure for AI Factories

Explore the NVIDIA MGX ecosystem unveiled at GTC 2026, from Vera Rubin Pod to third-generation rack architecture. Learn how modular design, liquid cooling, and system-level co-design enable scalable AI infrastructure for training and inference.

NVIDIA Groq 3 LPX: A Low-Latency Inference Accelerator Designed for the NVIDIA Vera Rubin Platform

NVIDIA Groq 3 LPX: A Low-Latency Inference Accelerator Designed for the NVIDIA Vera Rubin Platform

NVIDIA Groq 3 LPX is a low-latency inference accelerator for the Vera Rubin platform. It adopts a GPU+LPU heterogeneous architecture, optimizes the decoding performance of large models, and achieves high throughput and predictable low latency in long context and high-concurrency scenarios, thus helping the development of intelligent agent systems and next-generation AI applications.

NVIDIA BlueField-4 STX Storage Architecture: Designed for an AI-Native Storage and Data Platform

NVIDIA BlueField-4 STX Storage Architecture: Designed for an AI-Native Storage and Data Platform

The NVIDIA BlueField-4 STX architecture enables high-performance, low-latency data access from GPUs through modular rack design and CMX external context storage, facilitating intelligent agent AI, multimodal large model inference and training, and promoting the deployment of scalable infrastructure for native AI data platforms.

Deep Dive into NVIDIA Groq 3 LPU: A New Choice for AI Inference

Deep Dive into NVIDIA Groq 3 LPU: A New Choice for AI Inference

NVIDIA Groq 3 LPU, integrated into the Vera Rubin platform, works with Rubin GPUs to accelerate low-latency, token-based AI inference with predictable performance and scalable multi-chip execution.

A Comprehensive Market Insight into 800G Switches

A Comprehensive Market Insight into 800G Switches

This paper systematically analyzes the market drivers, technological evolution, and development trends of 800G switches, focusing on high-density interconnect requirements in AI training scenarios, CPO architecture, silicon photonics applications, and the prospects for future large-scale deployment.

InfiniBand Networking

NADDOD Successfully Delivers a Full-Stack InfiniBand XDR B300 Solution

NADDOD Successfully Delivers a Full-Stack InfiniBand XDR B300 Solution

Explore NADDOD end-to-end 800G InfiniBand XDR solution for B300 GPU clusters, achieving 787.7 Gbps RDMA bandwidth, ultra-low latency, and scalable AI training performance with industrial-grade deployment.

Spectrum-6 Ethernet Switch Deep Dive: SN6810 102.4T and SN6800 409.6T Switch

Spectrum-6 Ethernet Switch Deep Dive: SN6810 102.4T and SN6800 409.6T Switch

In-depth analysis of the NVIDIA Spectrum-6 Ethernet switch: Supporting 102.4T single-chip bandwidth, CPO co-packaged optics, 224G SerDes, and a high-cardinality port design, suitable for scale-out and scale-across network deployments of large-scale GPU clusters.

NVIDIA Vera Rubin: AI Supercomputer with Seven New Chips

NVIDIA Vera Rubin: AI Supercomputer with Seven New Chips

The NVIDIA Vera Rubin platform is a new computing platform for next-generation AI. Through the co-design of GPUs, CPUs, interconnects, and networks, it achieves high performance, low cost, and system-level security, supporting large-scale AI models and multi-agent applications.

In-Depth Analysis of AI Industry Insights in 2025

In-Depth Analysis of AI Industry Insights in 2025

This paper systematically reviews the current status and trends of the AI industry in 2025, the structure of the computing power industry chain, commercialization paths, and emerging scenarios such as embodied intelligence and quantum computing. It also analyzes the transition of AI from technology to large-scale application.

Google TPU: The AI Chip for the AI Inference Era

Google TPU: The AI Chip for the AI Inference Era

Google TPU vs NVIDIA GPU: Who Wins? This article provides a comprehensive analysis of the architectural evolution and system-level advantages of Google TPUs, delves into Ironwood, memory, and interconnect design, and discusses the differences between TPUs and NVIDIA GPUs, helping enterprises evaluate the best computing power solution for the era of large-scale computing.