Pass the NVIDIA NVIDIA-Certified Professional NCP-AII Questions and answers with CertsForce

The correct option is export HPL_OOC_SAFE_SIZE=4.0. NVIDIA HPL out-of-core mode allows matrix data that exceeds GPU memory capacity to be placed in host memory, but the GPU still needs reserved memory for drivers and runtime overhead. NVIDIA documents HPL_OOC_SAFE_SIZE as the amount of GPU memory, in GiB, reserved for the driver and not used by HPL out-of-core mode; increasing it is recommended when GPU out-of-memory errors occur. HPL_OOC_MODE=0 disables out-of-core mode, which would not help run a larger 40B matrix. HPL_OOC_NUM_STREAMS=8 changes the number of CUDA streams used for out-of-core operations, but it does not reserve driver memory. HPL_OOC_MAX_GPU_MEM=90 limits total GPU memory use, but the specific variable intended to leave safe driver space is HPL_OOC_SAFE_SIZE. During cluster burn-in, this setting helps preserve test validity while avoiding false failures caused by memory reservation issues rather than actual hardware instability.

When evaluating NVIDIA Collective Communications Library (NCCL) performance, it is vital to distinguish between Algorithm Bandwidth and Bus Bandwidth. For an all_reduce operation, the Bus Bandwidth represents the effective data transfer rate across the hardware links, which includes the overhead of the ring or tree collective algorithm. In an NDR (400G) InfiniBand fabric, the theoretical peak per link is 50 GB/s (unidirectional). In a 64-GPU cluster (8 nodes of 8 GPUs), achieving a bus bandwidth of 656 GB/s indicates that the fabric is efficiently utilizing the multiple 400G rails available on the DGX H100. This result is considered optimal as it reflects near-line-rate performance when accounting for network headers and synchronization overhead. Algorithm bandwidth is naturally lower because it represents the " useful " data moved from the application ' s perspective. If the bus bandwidth were significantly lower, it would suggest congestion, cable faults, or sub-optimal routing.

The correct sequence is to perform the required reset or power-cycle actions for the components being updated. NVIDIA DGX H100/H200 firmware guidance states that activation depends on component type: BMC firmware requires a BMC reset using sudo ipmitool mc reset cold; PCIe switch, PCIe retimer, BIOS, and HGX GPU tray components require a cold system reset using sudo ipmitool chassis power cycle; and EROT or CPLD components require an AC power cycle by removing and restoring system power. NVIDIA also notes that an AC power cycle activates firmware for all updated components. A normal operating system reboot is not sufficient for every firmware class, and relying only on software restart can leave some components running old firmware. In large NVIDIA AI Factory deployments, firmware activation must be treated as part of server bring-up, not just package upload. After the required reset sequence, administrators should verify installed and running firmware versions, confirm NVSM health, and only then return the DGX system to workload scheduling.

The nvidia-smi (NVIDIA System Management Interface) utility is the primary tool for monitoring and managing the state of NVIDIA GPUs. When a node exhibits " jitter " or lower performance compared to its peers in a cluster, nvidia-smi provides the necessary granular data to identify the bottleneck. It reports critical metrics such as GPU utilization percentages, memory usage, and, most importantly, " Clocks Throttle Reasons. " If a GPU is running slower due to power capping, thermal issues, or a hardware error (like an uncorrectable ECC error), nvidia-smi will display this state immediately. While lspci (Option A) can confirm if the GPU is physically visible on the PCIe bus, it cannot provide any telemetry regarding its operational performance or health. iblinkinfo (Option D) is a network-level tool that only monitors InfiniBand link states. In an AI infrastructure context, nvidia-smi is the first-line diagnostic to determine if a GPU is " healthy " and operating at its intended clock speeds.

Building a software image in NVIDIA Base Command Manager and using it to reimage the DGX system is the most efficient and secure method in a large cluster. In managed DGX infrastructure, remote image provisioning allows administrators to maintain consistent operating system versions, drivers, CUDA components, network settings, security baselines, and cluster management agents across compute nodes. This avoids manual access to each server and reduces configuration drift. Using apt-get to upgrade the operating system is not equivalent to a controlled reimage and may leave inconsistent packages or unsupported driver combinations. Creating a USB drive requires physical access and does not scale for large deployments. Skipping ISO verification and directly flashing the operating system over SSH is unsafe because it bypasses image validation and can leave nodes in an unrecoverable or untrusted state. BCM-based imaging supports repeatable deployment, centralized control, rollback planning, and integration with node categories or software images. This is the preferred operational model for reliable DGX cluster bring-up and lifecycle management.

The Baseboard Management Controller (BMC) is a powerful tool that allows for total control over the DGX system, including the ability to flash firmware, cycle power, and access the serial console. Because of this, it is a high-value target for security threats. The " 100% verified " secure approach (Option D) involves two critical layers:

Network Isolation: The BMC port should never be exposed to the public internet (Option A) or even the general production network (Option B). It must reside on a dedicated Out-of-Band (OOB) network that is firewalled and accessible only to authorized administrators.

Credential Management: Standard NVIDIA factory defaults (like admin/admin) must be changed immediately upon first access. As part of the DGX first-boot wizard, the system prompts the administrator to create a strong, unique password for the primary user, which is then synchronized to the BMC.

Leaving the port disconnected (Option C) is unfeasible for modern data center operations, as the BMC is required for remote monitoring and " headless " deployment. Following the isolated/firewalled approach ensures the AI Factory remains resilient against both external attacks and internal lateral movement.