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| Section | Objectives |
|---|---|
| Network Monitoring and Troubleshooting | - UFM monitoring and alerting capabilities - Performance analysis and congestion management - Monitoring tools and telemetry for AI fabrics - Link-level and fabric-level troubleshooting - Error handling and recovery |
| Network Optimization for AI Workloads | - Collective communication optimization - GPU Direct RDMA and storage network optimization - Quality of Service (QoS) for AI traffic - Congestion control mechanisms - Adaptive routing and load balancing |
| NVIDIA AI Networking Hardware and Platforms | - DGX cluster networking architecture - SuperPOD reference architectures - NVIDIA Spectrum switches - NVIDIA ConnectX NICs and BlueField DPUs - NVIDIA Quantum InfiniBand switches |
| AI Networking Fundamentals | - RDMA and InfiniBand technologies - Traffic patterns and communication collectives (All-Reduce, All-Gather) - Network topology considerations for AI clusters - AI/ML network architectures |
| Network Configuration and Provisioning | - UFM (Unified Fabric Manager) configuration and management - RoCE network configuration - Cumulus Linux and SONiC network OS fundamentals - InfiniBand fabric bring-up and configuration - VXLAN and overlay networking for AI |
| Security and Management | - Access control and management plane security - Network segmentation and isolation strategies - Security features in AI networking infrastructure |
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NEW QUESTION # 87
What are two methods for accessing the operating system on a BlueField DPU? Pick the 2 correct responses below
Answer: C,D
Explanation:
Accessing the BlueField DPU Operating System (OS)is possible throughrshim, either over PCIe or USB, and via SSH through the OOB interface when in DPU mode.
NEW QUESTION # 88
In Cumulus Linux, which technology enables the ability to provide active-active redundancy to servers, without the need for direct inter-switch links?
Answer: B
Explanation:
EVPN Multi-homingenablesactive-active redundancy without inter-switch linksby usingoverlay routing over VXLAN and distributed control plane using BGP EVPN.
From the officialNVIDIA Cumulus Linux EVPN Multihoming Documentation:
"EVPN multihoming allows multiple Top-of-Rack (ToR) switches to connect to the same server while maintaining full layer-2 redundancy without the need for inter-switch links or traditional MLAG configuration." Key benefits:
* Simplified topology (no ISL/peer-link needed)
* BGP-based control plane
* Fast convergence
* Active-active links per host NIC
Incorrect Options:
* MLAGrequires ISL between switches and peer-link configuration.
* VSS(Virtual Switching System) is a Cisco term, not supported in NVIDIA networking.
Reference: Cumulus Linux Docs - EVPN Multihoming
NEW QUESTION # 89
A leading AI research center is upgrading its infrastructure to support large language model projects. The team is debating whether to implement a dedicated storage fabric for their AI workloads. Which of the following best explains why a dedicated storage fabric is crucial for this AI network architecture? Pick the 2 correct responses below
Answer: C,D
Explanation:
Modern AI training (especially with LLMs) requires extremely high-speed, parallel access to large datasets. A dedicated storage fabric separates data I/O traffic from the training compute path and avoids contention.
NEW QUESTION # 90
Which of the following statements are true about AI workloads and adaptive routing?
Pick the 2 correct responses below.
Answer: A,B
Explanation:
AI workloads, particularly in large-scale training scenarios, are characterized by a small number of high- bandwidth, long-lived flows known as "elephant flows." These flows can dominate network traffic and are prone to causing congestion if not managed effectively.
Traditional flow-based load balancing mechanisms, such as Equal-Cost Multipath (ECMP), distribute traffic based on flow hashes. However, in AI workloads with lowentropy (i.e., limited variability in flow characteristics), ECMP can lead to uneven traffic distribution and congestion on certain paths.
Adaptive routing techniques, which dynamically adjust paths based on real-time network conditions, are more effective in managing AI traffic patterns and mitigating congestion risks.
Reference:Powering Next-Generation AI Networking with NVIDIA SuperNICs
NEW QUESTION # 91
You are tasked with configuring multi-tenancy using partition key (PKey) for a high-performance storage fabric running on InfiniBand. Each tenant's GPU server is allowed to access the shared storage system but cannot communicate with another tenant's GPU server.
Which of the following partition key membership configurations would you implement to set up multi- tenancy in this environment?
Answer: A
Explanation:
To enforce strictmulti-tenancy, where:
* Tenant A's GPUcannot talk toTenant B's GPU
* But both can accessshared storage
The correct solution is:
* Storage system # Full PKey membership
* Each tenant's GPU # Limited PKey membership
From theNVIDIA InfiniBand P_Key Partitioning Guide:
"A port with limited membership can only communicate with full members of the same PKey. It cannot communicate with other limited members, even within the same partition." This isolates tenantsfrom each other, while allowingshared access to storage.
Incorrect Options:
* Apermits tenant-to-tenant communication.
* Bisolates everything, including access to storage.
* Cprevents GPU access to storage.
Reference: NVIDIA InfiniBand - Multi-Tenant PKey Partitioning Design
NEW QUESTION # 92
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