Cisco HCI-GPU-A30 | A30 24GB HBM2 GPU, PCIe 4.0, Passive, 165W

Q: What workloads is the Cisco HCI-GPU-A30 designed for?
A: The A30 GPU is optimized for AI inference at scale, AI training, high-performance computing, data analytics, and engineering simulation. It excels in workloads requiring large memory capacity and high bandwidth, including large language models, deep learning frameworks, and GPU-intensive enterprise applications.

Q: What is Multi-Instance GPU technology and how does it work?
A: Multi-Instance GPU allows the A30 to be partitioned into up to four independent GPU instances, each with dedicated high-bandwidth memory, cache, and compute cores. This enables multiple users or workloads to securely share a single GPU while maintaining hardware-level isolation, maximizing utilization in virtualized and containerized environments.

Q: Which Cisco servers support the HCI-GPU-A30?
A: The HCI-GPU-A30 is designed for Cisco HCI and UCS C-Series rack servers. GPU cards must be procured from Cisco with the required unique SBIOS ID for compatibility with CIMC and UCSM management. Consult Cisco compatibility guides for specific slot configurations and server models.

Q: Does this GPU require active cooling or special power requirements?
A: The A30 uses passive cooling and requires adequate server airflow to operate within its thermal envelope. It draws 165W typical power with a maximum of 180W TDP and connects via a single 8-pin PCIe power connector. Ensure your server chassis provides sufficient cooling and power delivery.

Q: How does the A30 compare to other data center GPUs for AI workloads?
A: The A30 offers 24GB HBM2 memory and 933 GB/s bandwidth, delivering 1.5x more memory and 3x more bandwidth than the T4 GPU. While positioned below the A100 in compute performance, the A30 provides excellent price-to-performance for mainstream AI inference and training tasks, with Tensor Core acceleration and support for TF32, FP16, INT8, and sparse model optimization.