NVIDIA 900-2G179-0020-101 | A2 Tensor Core 16GB GPU, PCIe 4.0 x8, 40-60W TDP

Q: What AI workloads is the NVIDIA A2 optimized for?
A: The A2 is designed for entry-level AI inference workloads including intelligent video analytics, edge AI deployments, machine learning inference, and virtual desktop infrastructure. It excels in scenarios requiring low power consumption and compact form factors while delivering up to 20x better inference performance compared to CPU-only servers.

Q: What server form factors support this GPU?
A: The A2 supports both low-profile and full-height server configurations thanks to its single-slot design and included brackets. The passive cooling and 40-60W configurable TDP make it compatible with standard 1U and 2U rackmount servers, tower servers, and edge computing platforms with PCIe 4.0 x8 slots.

Q: Does this GPU support virtualization?
A: Yes, the A2 supports NVIDIA vGPU software including Virtual PC, Virtual Applications, RTX Virtual Workstation, AI Enterprise, and Virtual Compute Server. This enables multiple users to share GPU resources for virtual desktop infrastructure and cloud-based AI inference applications.

Q: What precision formats does the A2 Tensor Core support?
A: The A2's 3rd generation Tensor Cores support multiple precision formats including FP32, TF32, FP16, BFLOAT16, INT8, and INT4. It also supports NVIDIA's automatic mixed precision capabilities and sparsity acceleration, which can double effective throughput for compatible AI models.

Q: Can multiple A2 GPUs be installed in the same server?
A: Yes, the A2's single-slot, low-profile design and passive cooling enable dense multi-GPU configurations in standard servers. Multiple A2 GPUs can be deployed to scale inference capacity or run parallel workloads, making it ideal for edge data centers and consolidated AI deployments.