NCP-AIN
Free NVIDIA-Certified Professional: AI Networking Practice Test
12 exam-style questions with full explanations — no sign-up. Score yourself, then close your gaps with the full course.
Exam fee ~$4005 exam domainsLevel Advanced2 timed practice tests in the course
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An AI factory has 8 GPUs per DGX node, each connected via NVLink internally and via a separate NIC to the network fabric for inter-node communication. Which topology design connects each GPU's NIC to a dedicated leaf switch such that GPU 0 across every node connects to leaf switch 0, GPU 1 to leaf switch 1, and so on?
Rail-optimized topology explicitly aligns each GPU's NIC to a dedicated rail (leaf) switch so that same-index GPUs across all nodes share a switch, minimizing hops for collective operations like NCCL all-reduce. This is the reference design used in NVIDIA DGX SuperPOD deployments.
A customer's InfiniBand fabric runs redundant Subnet Managers (SM) for high availability: SM-A on one management node and SM-B on another. During a planned maintenance window, the administrator manually fails mastership from SM-A to SM-B before powering down SM-A. After SM-A comes back online, it immediately reclaims master status and triggers a disruptive resweep of the fabric. Which configuration change would prevent SM-A from automatically reclaiming mastership when it rejoins?
OpenSM master election is based on sm_priority (and GUID as tiebreaker). Lowering SM-A's priority relative to SM-B ensures SM-B stays preferred master when both are active, preventing an unwanted takeover, while still keeping SM-A available as a standby for true redundancy.
An AI training cluster running RoCEv2 over a Spectrum-X Ethernet fabric is experiencing high tail latency at GPU-facing leaf switches, but PFC pause-frame counters remain low. The network team wants to reduce sender rates before congestion escalates to PFC pause storms and head-of-line blocking. Which approach BEST meets this requirement?
NVIDIA's programmable congestion control on Spectrum-X uses fine-grained telemetry (RTT and ECN signals) fed back to the NIC/DPU to proactively slow senders, addressing congestion before it escalates into PFC pauses and HOL blocking.
During a large AI training job, GPUDirect RDMA traffic experiences intermittent drops. The network operations team needs to identify the exact root cause (e.g., buffer overrun vs. CRC error vs. congestion) in real time without capturing full packet traces. Which tool should they use?
WJH is purpose-built for real-time, per-packet root-cause classification of drops (buffer overrun, CRC, ECN marking, tail drop, etc.) without requiring full packet capture, making it the fastest path to root cause.
A cloud provider runs a multi-tenant AI training cluster on a single InfiniBand fabric. Customer A's compute nodes must never be able to communicate with Customer B's compute nodes at the fabric level, even if both are on the same physical switches. Which mechanism should be configured to enforce this isolation?
P_Keys are the native InfiniBand mechanism for Layer 2 fabric isolation, restricting which HCAs can exchange traffic; UFM/OpenSM provisions and enforces partition membership across the subnet.
A cloud service provider must build a multi-tenant AI training-as-a-service platform that isolates tenant traffic, integrates with existing Ethernet-based operational tooling, and requires RoCEv2 for GPU-to-GPU communication. Which NVIDIA networking platform BEST meets these requirements?
Spectrum-X is purpose-built for Ethernet-based, multi-tenant AI clouds, combining adaptive routing and advanced congestion control (via Spectrum switches and BlueField DPUs) with RoCEv2 to deliver InfiniBand-like performance while keeping standard Ethernet operational tooling.
A deep learning training job runs NCCL AllReduce collectives across 512 GPUs on an NVIDIA InfiniBand fabric. To offload gradient aggregation from GPU compute directly into the network switches and reduce the data volume traversing the fabric, which technology should the administrator enable?
SHARP is NVIDIA's in-network computing feature that performs collective reduction operations (such as AllReduce) inside the switch ASICs, cutting the amount of data GPUs must send and reducing collective completion time.
In an NVIDIA Spectrum-X fabric, which component makes the per-packet (or per-flow) decision to spread RoCEv2 traffic across all available uplinks to avoid ECMP hash collisions?
Adaptive routing decisions that dynamically select uplinks based on real-time port load are made in the Spectrum switch ASIC's forwarding/routing engine, not on the host or DPU.
A network team wants to deploy declarative, version-controlled configuration changes across a fleet of NVIDIA Spectrum switches running Cumulus Linux, integrated into an existing CI/CD pipeline with idempotent execution. Which approach correctly satisfies this requirement?
The nvidia.nvue Ansible collection allows declarative, idempotent NVUE configuration to be version-controlled and pushed as part of a CI/CD pipeline, matching the exact requirement.
An organization wants to enforce zero-trust security policies -- including stateful firewalling and IPsec encryption -- on east-west AI training traffic, without consuming any CPU cycles on the GPU host servers. Which NVIDIA capability should be deployed to achieve this?
DOCA Flow and DOCA Firewall are BlueField DPU-accelerated services that offload packet filtering, stateful firewalling, and encryption to the DPU's dedicated ARM cores and hardware accelerators, keeping host CPU cycles free -- this is the core of BlueField zero-trust architecture.
A hyperscale AI data center design places GPU compute traffic, storage traffic, and out-of-band management traffic on physically separate fabrics. What is the PRIMARY reason for this separation?
Separating fabrics isolates bursty, latency-sensitive RDMA collective traffic on the compute fabric from best-effort storage and management traffic, preventing congestion and jitter that would degrade training performance.
An administrator must define an InfiniBand partition in OpenSM's partitions.conf that assigns pkey 0x8001 with full membership to two GUIDs: 0x0011223344556677 and 0x0011223344556688, enabling IPoIB on the partition. Which line correctly implements this?
The correct partitions.conf syntax specifies the pkey value with the 0x prefix (0x8001, whose high bit already indicates full membership), the ipoib option to enable IP over InfiniBand, and each GUID explicitly marked as a full or limited member.
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How much does the NCP-AIN exam cost?
The exam fee is approximately $400 and varies by region — confirm current pricing with the certification vendor before you book.
What topics are on the exam?
It covers 5 domains: AI Data Center Network Design and Optimization (~18%), InfiniBand Fabric Configuration and Management (~24%), Spectrum-X Ethernet and RoCE for AI (~24%), Network Automation, Monitoring, and Telemetry (~16%), Security, Troubleshooting, and Performance (~18%). The full course has a dedicated chapter, lab and practice-test coverage for each.
Is this practice test really free?
Yes — all questions on this page are free with explanations and no sign-up. The paid Udemy course adds two full-length timed exams, video lessons and hands-on labs.
Will this prepare me for the real exam?
The questions mirror the real exam's style and are mapped to the official domains. This is exam-focused preparation — combine the free test with the full course's timed simulations to gauge your readiness.