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NVIDIA NCP-AII Practice Test 84

Question 830

During an NVIDIA AI factory acceptance test, engineers discover: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks. Which TWO complementary elements are needed: the correct technical action and the strongest independent diagnostic evidence? Select TWO answers.

  1. Run a controlled representative GPU stress with monitoring of temperatures, memory and power-limit behavior.
  2. Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution.
  3. Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.
  4. Inspect rank-to-device assignments, CPU binding, NUMA traffic, GPU topology and achieved HPL timing.
  5. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.

Explanation

Correct Answers

B:

This is the direct operational evidence to investigate: Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks.

C:

This is an appropriate correction for AI fabric bisection and oversubscription test: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

Incorrect Answers

A:

This alternative is relevant to GPU thermal power and memory single-node burn-in but does not directly resolve the current AI fabric bisection and oversubscription test issue: Run a controlled representative GPU stress with monitoring of temperatures, memory and power-limit behavior. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

D:

This alternative is relevant to Multi-process HPL rank placement and CPU affinity but does not directly resolve the current AI fabric bisection and oversubscription test issue: Inspect rank-to-device assignments, CPU binding, NUMA traffic, GPU topology and achieved HPL timing. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks.

E:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

Question 831

A production GPU cluster review identifies this condition: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks. Which diagnostic evidence should be obtained FIRST to substantiate the likely fault or configuration gap? Select ONE best answer.

  1. Inspect rank-to-device assignments, CPU binding, NUMA traffic, GPU topology and achieved HPL timing.
  2. Inspect dcgmi diag suite results, entity IDs, error logs, driver state and conflicting running workloads.
  3. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  4. Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution.

Explanation

Correct Answer

D:

This is the direct operational evidence to investigate: Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

Incorrect Answers

A:

This alternative is relevant to Multi-process HPL rank placement and CPU affinity but does not directly resolve the current AI fabric bisection and oversubscription test issue: Inspect rank-to-device assignments, CPU binding, NUMA traffic, GPU topology and achieved HPL timing. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

B:

This alternative is relevant to DCGM active single-node diagnostic suites but does not directly resolve the current AI fabric bisection and oversubscription test issue: Inspect dcgmi diag suite results, entity IDs, error logs, driver state and conflicting running workloads. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks.

C:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks.

Question 832

In a professional AI infrastructure deployment, a technician observes: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks. After corrective work, which observable result BEST confirms that the requirement is met? Select ONE best answer.

  1. The fabric meets aggregate traffic expectations with no persistent oversubscription hotspot under representative concurrent jobs.
  2. The approved HPL run completes valid numerical checks with repeatable measured throughput documented.
  3. Repeat runs produce stable accepted performance with no unintended GPU or host-core oversubscription.
  4. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.

Explanation

Correct Answer

A:

This is an observable verified result, not merely a claimed configuration change: The fabric meets aggregate traffic expectations with no persistent oversubscription hotspot under representative concurrent jobs. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks.

Incorrect Answers

B:

This alternative is relevant to HPL configuration matrix dimensions and performance but does not directly resolve the current AI fabric bisection and oversubscription test issue: The approved HPL run completes valid numerical checks with repeatable measured throughput documented. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks.

C:

This alternative is relevant to Multi-process HPL rank placement and CPU affinity but does not directly resolve the current AI fabric bisection and oversubscription test issue: Repeat runs produce stable accepted performance with no unintended GPU or host-core oversubscription. Observed scenario: Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks.

D:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. Every compute NIC reports link at full speed but simultaneous NCCL jobs bottleneck on shared spine uplinks. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

Question 833

The cluster operations team needs to evaluate this situation: A network acceptance test uses a single pair of hosts and misses multi-rack contention. Which operational response is MOST appropriate to address the root issue? Select ONE best answer.

  1. Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.
  2. Capture a reproducible preflight inventory of node hardware, software, connections and expected acceptance tests.
  3. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  4. Schedule supported active DCGM diagnostics for the relevant GPU class and investigate detailed failures.

Explanation

Correct Answer

A:

This is an appropriate correction for AI fabric bisection and oversubscription test: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention.

Incorrect Answers

B:

This alternative is relevant to Cluster-wide preflight hardware inventory but does not directly resolve the current AI fabric bisection and oversubscription test issue: Capture a reproducible preflight inventory of node hardware, software, connections and expected acceptance tests. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention.

C:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. A network acceptance test uses a single pair of hosts and misses multi-rack contention.

D:

This alternative is relevant to DCGM active single-node diagnostic suites but does not directly resolve the current AI fabric bisection and oversubscription test issue: Schedule supported active DCGM diagnostics for the relevant GPU class and investigate detailed failures. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention.

Question 834

At a multi-node AI infrastructure handoff, the team records: A network acceptance test uses a single pair of hosts and misses multi-rack contention. Which underlying infrastructure principle BEST explains the issue? Select ONE best answer.

  1. HPL measures achieved dense linear-algebra throughput under a specific matrix and process mapping, not marketing peak clocks.
  2. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.
  3. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  4. Sustained accelerator load can reveal thermal and electrical limits not visible during idle or brief smoke checks.

Explanation

Correct Answer

B:

This is the governing infrastructure principle: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention.

Incorrect Answers

A:

That option concerns HPL configuration matrix dimensions and performance. The proportionate action is: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.

C:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. A network acceptance test uses a single pair of hosts and misses multi-rack contention. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

D:

That option concerns GPU thermal power and memory single-node burn-in. The proportionate action is: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.

Question 835

During an NVIDIA AI factory acceptance test, engineers discover: A network acceptance test uses a single pair of hosts and misses multi-rack contention. Which diagnostic evidence should be obtained FIRST to substantiate the likely fault or configuration gap? Select ONE best answer.

  1. Inspect HPL configuration, problem size, process grid, elapsed time, residual report and resource mapping.
  2. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  3. Inspect deviceQuery or equivalent CUDA sample output, driver-runtime versions and kernel launch error codes.
  4. Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution.

Explanation

Correct Answer

D:

This is the direct operational evidence to investigate: Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention.

Incorrect Answers

A:

This alternative is relevant to HPL configuration matrix dimensions and performance but does not directly resolve the current AI fabric bisection and oversubscription test issue: Inspect HPL configuration, problem size, process grid, elapsed time, residual report and resource mapping. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention.

B:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability. The proportionate action is: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.

C:

That option concerns CUDA device query and kernel smoke tests. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

Question 836

A production GPU cluster review identifies this condition: A network acceptance test uses a single pair of hosts and misses multi-rack contention. After corrective work, which observable result BEST confirms that the requirement is met? Select ONE best answer.

  1. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  2. All intended links remain stable at supported speed with correct firmware and low error rate.
  3. Every intended node is accounted for and deviations are dispositioned before workload benchmarking begins.
  4. The fabric meets aggregate traffic expectations with no persistent oversubscription hotspot under representative concurrent jobs.

Explanation

Correct Answer

D:

This is an observable verified result, not merely a claimed configuration change: The fabric meets aggregate traffic expectations with no persistent oversubscription hotspot under representative concurrent jobs. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention.

Incorrect Answers

A:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability. The proportionate action is: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription. A direct check is: Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution. The acceptance condition is: The fabric meets aggregate traffic expectations with no persistent oversubscription hotspot under representative concurrent jobs.

B:

That option concerns Transceiver firmware and negotiated link test. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

C:

This alternative is relevant to Cluster-wide preflight hardware inventory but does not directly resolve the current AI fabric bisection and oversubscription test issue: Every intended node is accounted for and deviations are dispositioned before workload benchmarking begins. Observed scenario: A network acceptance test uses a single pair of hosts and misses multi-rack contention.

Question 837

In a professional AI infrastructure deployment, a technician observes: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. Which operational response is MOST appropriate to address the root issue? Select ONE best answer.

  1. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  2. Capture a reproducible preflight inventory of node hardware, software, connections and expected acceptance tests.
  3. Run supported single-node NCCL collectives spanning the intended local GPUs and compare with baseline topology.
  4. Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.

Explanation

Correct Answer

D:

This is an appropriate correction for AI fabric bisection and oversubscription test: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

Incorrect Answers

A:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

B:

This alternative is relevant to Cluster-wide preflight hardware inventory but does not directly resolve the current AI fabric bisection and oversubscription test issue: Capture a reproducible preflight inventory of node hardware, software, connections and expected acceptance tests. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

C:

This alternative is relevant to Intra-node NCCL all-reduce test scope but does not directly resolve the current AI fabric bisection and oversubscription test issue: Run supported single-node NCCL collectives spanning the intended local GPUs and compare with baseline topology. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

Question 838

The cluster operations team needs to evaluate this situation: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. Which underlying infrastructure principle BEST explains the issue? Select ONE best answer.

  1. Distributed HPL scaling depends on mapping processes and communications to actual CPU and GPU locality.
  2. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  3. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.
  4. Port link negotiation depends on mutually supported optical or electrical signaling and component revisions.

Explanation

Correct Answer

C:

This is the governing infrastructure principle: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

Incorrect Answers

A:

That option concerns Multi-process HPL rank placement and CPU affinity. The proportionate action is: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.

B:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

D:

That option concerns Transceiver firmware and negotiated link test. The proportionate action is: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.

Question 839

At a multi-node AI infrastructure handoff, the team records: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. Which diagnostic evidence should be obtained FIRST to substantiate the likely fault or configuration gap? Select ONE best answer.

  1. Inspect HPL output for residual tests, return codes, numerical anomalies and rerun consistency.
  2. Inspect node inventory, GPU and NIC UUIDs, firmware and driver versions, cabling records and test eligibility.
  3. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  4. Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution.

Explanation

Correct Answer

D:

This is the direct operational evidence to investigate: Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

Incorrect Answers

A:

That option concerns HPL numerical result and residual validation. Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

B:

This alternative is relevant to Cluster-wide preflight hardware inventory but does not directly resolve the current AI fabric bisection and oversubscription test issue: Inspect node inventory, GPU and NIC UUIDs, firmware and driver versions, cabling records and test eligibility. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

C:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability. The proportionate action is: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.

Question 840

During an NVIDIA AI factory acceptance test, engineers discover: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. Which TWO complementary elements are needed: the correct technical action and the strongest independent diagnostic evidence? Select TWO answers.

  1. Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription.
  2. Inspect local device topology, nccl-tests rank count, all-reduce bandwidth and link error metrics.
  3. Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s.
  4. Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution.
  5. Align MPI ranks, CPU NUMA affinity and GPU allocation with the tested host and fabric topology.

Explanation

Correct Answers

A:

This is an appropriate correction for AI fabric bisection and oversubscription test: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

D:

This is the direct operational evidence to investigate: Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability.

Incorrect Answers

B:

This alternative is relevant to Intra-node NCCL all-reduce test scope but does not directly resolve the current AI fabric bisection and oversubscription test issue: Inspect local device topology, nccl-tests rank count, all-reduce bandwidth and link error metrics. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

C:

This tempting but unsafe shortcut is not a sufficient remediation for AI fabric bisection and oversubscription test: Assert a nonblocking AI network because every endpoint NIC independently negotiates 400 Gb/s. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports. The governing mechanism is: Simultaneous east-west traffic stresses shared fabric resources beyond individual host line-rate capability. The proportionate action is: Use multi-flow cluster-scale throughput tests to measure effective bisection and hotspot oversubscription. A direct check is: Inspect per-tier utilization, congestion counters, full-rack NCCL measurements and ECMP distribution. The acceptance condition is: The fabric meets aggregate traffic expectations with no persistent oversubscription hotspot under representative concurrent jobs.

E:

This alternative is relevant to Multi-process HPL rank placement and CPU affinity but does not directly resolve the current AI fabric bisection and oversubscription test issue: Align MPI ranks, CPU NUMA affinity and GPU allocation with the tested host and fabric topology. Observed scenario: A fabric upgrade adds GPUs faster than switch uplinks and performance drops despite normal ports.

NCP-AI Infrastructure (NCP-AII) Practice Tests