Cisco UCSC-GPU-MI210 | Instinct MI210 GPU Accelerator, 64GB HBM2e, PCIe 4.0

Q: What workloads is the UCSC-GPU-MI210 optimized for?
A: The MI210 is optimized for double-precision HPC applications such as computational fluid dynamics, molecular dynamics, climate modeling, seismic analysis, and genomics. It also supports mixed-precision deep learning training with 181 TFLOPS of FP16/BF16 performance, making it suitable for AI and HPC convergence workloads.

Q: How does the Infinity Fabric interconnect work?
A: The MI210 features three Infinity Fabric links that enable high-speed peer-to-peer communication between multiple GPUs without relying solely on PCIe bandwidth. This allows for 2-way and 4-way GPU clusters within a single server, delivering up to 300 GB/s of direct GPU-to-GPU bandwidth for tightly coupled parallel workloads.

Q: What server platforms are compatible with this GPU?
A: The UCSC-GPU-MI210 is designed for Cisco UCS servers including the UCS X440p PCIe Node and other compatible UCS C-Series rack servers. It requires a PCIe 4.0 x16 slot, dual-slot clearance, FHFL form factor support, and sufficient power delivery via an 8-pin EPS12V connector. Passive cooling design requires proper chassis airflow.

Q: What software frameworks does the MI210 support?
A: The MI210 supports the open-source AMD ROCm software stack with native integration for PyTorch and TensorFlow. It includes the HIP conversion tool for porting CUDA applications, access to AMD Infinity Hub for optimized HPC containers, and broad compatibility with scientific computing libraries and frameworks on Linux 64-bit platforms.

Q: Can multiple MI210 GPUs be installed in the same server?
A: Yes, multiple MI210 GPUs can be deployed in supported servers with adequate PCIe slots, power capacity, and cooling. The three Infinity Fabric links on each card enable direct GPU-to-GPU communication in dual or quad-GPU configurations, creating high-bandwidth GPU hives for distributed HPC and AI workloads.