- Mia
Harper Ross
Answered on 5:55 am
100GBASE-LR4 QSFP28, which can support up to 10km over duplex single-mode fiber (SMF) with LC connectors. This transceiver uses four wavelengths of 1310nm LAN WDM to achieve a 100G data rate. It is compliant with IEEE 802.3ba 100GBASE-LR4 and QSFP28 MSA standards.
100GBASE-ER4L QSFP28, which can support up to 25km or 40km over duplex SMF with LC connectors, depending on the product specifications. This transceiver also uses four wavelengths of 1310nm LAN WDM to achieve 100G data rate. It is compliant with IEEE 802.3ba 100GBASE-ER4 and QSFP28 MSA standards.
100GBASE-ZR4 QSFP28, which can support up to 80km over duplex SMF with LC connectors. This transceiver also uses four wavelengths of 1310nm LAN WDM to achieve 100G data rate. It is compliant with IEEE 802.3ba 100GBASE-ZR4 and QSFP28 MSA standards.
People Also Ask
NVIDIA GB200 NVL72: Defining the New Benchmark for Rack-Scale AI Computing
The explosive growth of Large Language Models (LLM) and Mixture-of-Experts (MoE) architectures is fundamentally reshaping the underlying logic of computing infrastructure. As model parameters cross the trillion mark, traditional cluster architectures—centered on standalone servers connected by standard networking—are hitting physical and economic ceilings. In this context, NVIDIA’s GB200 NVL72 is
In-Depth Analysis Report on 800G Switches: Architectural Evolution, Market Landscape, and Future Outlook
Introduction: Reconstructing Network Infrastructure in the AI Era Paradigm Shift from Cloud Computing to AI Factories Global data center networks are undergoing the most profound transformation in the past decade. Previously, network architectures were primarily designed around cloud computing and internet application traffic patterns, dominated by “north-south” client-server models. However,
Global 400G Ethernet Switch Market and Technical Architecture In-depth Research Report: AI-Driven Network Restructuring and Ecosystem Evolution
Executive Summary Driven by the explosive growth of the digital economy and Artificial Intelligence (AI) technologies, global data center network infrastructure is at a critical historical node of migration from 100G to 400G/800G. As Large Language Model (LLM) parameters break through the trillion level and demands for High-Performance Computing (HPC)
Key Design Constraints for Stack-OSFP Optical Transceiver Cold Plate Liquid Cooling
Foreword The data center industry has already adopted 800G/1.6T optical modules on a large scale, and the demand for cold plate liquid cooling of optical modules has increased significantly. To meet this industry demand, OSFP-MSA V5.22 version has added solutions applicable to cold plate liquid cooling. At present, there are
NVIDIA DGX Spark Quick Start Guide: Your Personal AI Supercomputer on the Desk
NVIDIA DGX Spark — the world’s smallest AI supercomputer powered by the NVIDIA GB10 Grace Blackwell Superchip — brings data-center-class AI performance to your desktop. With up to 1 PFLOP of FP4 AI compute and 128 GB of unified memory, it enables local inference on models up to 200 billion parameters and fine-tuning of models
Related Articles
800G SR8 and 400G SR4 Optical Transceiver Modules Compatibility and Interconnection Test Report
Version Change Log Writer V0 Sample Test Cassie Test Purpose Test Objects：800G OSFP SR8/400G OSFP SR4/400G Q112 SR4. By conducting corresponding tests, the test parameters meet the relevant industry standards, and the test modules can be normally used for Nvidia (Mellanox) MQM9790 switch, Nvidia (Mellanox) ConnectX-7 network card and Nvidia (Mellanox) BlueField-3, laying a foundation for
NVIDIA GB200 NVL72: Defining the New Benchmark for Rack-Scale AI Computing
The explosive growth of Large Language Models (LLM) and Mixture-of-Experts (MoE) architectures is fundamentally reshaping the underlying logic of computing infrastructure. As model parameters cross the trillion mark, traditional cluster architectures—centered on standalone servers connected by standard networking—are hitting physical and economic ceilings. In this context, NVIDIA’s GB200 NVL72 is
In-Depth Analysis Report on 800G Switches: Architectural Evolution, Market Landscape, and Future Outlook
Introduction: Reconstructing Network Infrastructure in the AI Era Paradigm Shift from Cloud Computing to AI Factories Global data center networks are undergoing the most profound transformation in the past decade. Previously, network architectures were primarily designed around cloud computing and internet application traffic patterns, dominated by “north-south” client-server models. However,
Why Is It Necessary to Remove the DSP Chip in LPO Optical Module Links?
If you follow the optical module industry, you will often hear the phrase “LPO needs to remove the DSP chip.” Why is this? To answer this question, we first need to clarify two core concepts: what LPO is and the role of DSP in optical modules. This will explain why
Global 400G Ethernet Switch Market and Technical Architecture In-depth Research Report: AI-Driven Network Restructuring and Ecosystem Evolution
Executive Summary Driven by the explosive growth of the digital economy and Artificial Intelligence (AI) technologies, global data center network infrastructure is at a critical historical node of migration from 100G to 400G/800G. As Large Language Model (LLM) parameters break through the trillion level and demands for High-Performance Computing (HPC)
Key Design Constraints for Stack-OSFP Optical Transceiver Cold Plate Liquid Cooling
Foreword The data center industry has already adopted 800G/1.6T optical modules on a large scale, and the demand for cold plate liquid cooling of optical modules has increased significantly. To meet this industry demand, OSFP-MSA V5.22 version has added solutions applicable to cold plate liquid cooling. At present, there are
NVIDIA DGX Spark Quick Start Guide: Your Personal AI Supercomputer on the Desk
NVIDIA DGX Spark — the world’s smallest AI supercomputer powered by the NVIDIA GB10 Grace Blackwell Superchip — brings data-center-class AI performance to your desktop. With up to 1 PFLOP of FP4 AI compute and 128 GB of unified memory, it enables local inference on models up to 200 billion parameters and fine-tuning of models