Cisco HCI-CPU-I4514Y= Processor: Hyperconverg
HCI-CPU-I4514Y= Overview: Engineered for Cisco Hy...
Product Overview and Target Workloads
The Cisco UCSX-GPU-H100-80= is a NVIDIA H100 Tensor Core GPU optimized for Cisco’s UCS X-Series modular systems, delivering 80GB HBM3 memory for enterprise AI and HPC workloads. This Cisco-specific SKU integrates pre-configured firmware for seamless compatibility with UCS Manager and Intersight, enabling deterministic performance in multi-tenant environments. Unlike generic H100 GPUs, it supports Cisco’s Unified Fabric Controller for adaptive bandwidth allocation across UCS 9108 fabric interconnects.
Technical Architecture and Hardware Innovations
GPU Core Configuration
- NVIDIA Hopper Architecture with 16896 CUDA cores and 528 Tensor cores
- 80GB HBM3 memory at 3.35TB/s bandwidth (1.6x A100 80GB bandwidth)
- PCIe 5.0 x16 interface with Cisco DirectPath DMA for 128GB/s host-GPU throughput
Enterprise-Optimized Features
- Multi-Instance GPU (MIG) partitioning into 7x 10GB instances with isolated clocks
- Hardware-enforced SR-IOV supporting 16 virtual GPUs (vGPU) per physical unit
- Cisco Secure Boot with UEFI firmware validation for regulated industries
Performance Benchmarks in AI/HPC Workloads
Generative AI Training
- Trains 175B-parameter GPT models 3.2x faster than A100 80GB using FP8 precision
- Achieves 98% scaling efficiency in 8-GPU clusters with NVLink Switch System
Inference Acceleration
- Processes 32,000 queries/sec on BERT-Large with <2ms latency (vs. 18,000 on A100)
- MIG-enabled multi-tenancy isolates healthcare AI models with <5% performance penalty
Thermal and Power Management
- 700W maximum TDP with Cisco’s Dynamic Power Capping (±10% adjustments)
- Liquid-cooling readiness via UCS X9508 cold plate compatibility (50°C coolant inlet)
- Per-MIG power telemetry through UCS Manager 4.9(1c) for SLA enforcement
Platform Compatibility and Configuration
Supported UCS Infrastructure
- Requires UCS X210c M7 compute nodes with Cisco UCSX-M7-HD100G mezzanine adapters
- Validated with UCS 6454 Fabric Interconnects for NVLink over EDR InfiniBand
Firmware and Software Requirements
- NVIDIA AI Enterprise 4.0 with Cisco-signed drivers for vGPU support
- UCS Manager 5.0(1a) mandatory for MIG resource partitioning
Deployment Strategies for AI Clusters
Large Language Model (LLM) Training
- 3.2TB/s inter-GPU bandwidth via NVLink Switch System 2.0
- Checkpointing optimizations using HBM3’s 7.8μs access latency
Hyperconverged AI/ML
- VMware vSphere 8.0U2 supports 8 vGPUs per VM with 99% hardware utilization
- Red Hat OpenShift AI achieves 1,500 containers/GPU using MIG isolation
Licensing and Procurement Considerations
The UCSX-GPU-H100-80= requires:
- Cisco Intersight for Compute License for GPU health monitoring
- NVIDIA AI Enterprise 4.0+ for MIG/vGPU capabilities
For organizations requiring validated hardware with full support SLAs, [“UCSX-GPU-H100-80=” link to (https://itmall.sale/product-category/cisco/) provides Cisco-certified procurement options.
Strategic Insights from Technical Evaluations
In comparative testing against AMD’s MI250X, the H100-80 demonstrates 72% higher FP8 throughput for transformer models—critical for real-time language translation services. While the 700W TDP demands advanced cooling infrastructure, the MIG-enabled resource slicing allows telecom providers to monetize GPU capacity across 16 tenants simultaneously. Healthcare organizations leveraging federated learning observe 89% faster model convergence using NVLink’s 900GB/s inter-GPU bandwidth versus traditional RDMA. However, enterprises must carefully evaluate MIG partition sizes against evolving AI model requirements, as repartitioning requires hardware reboot cycles. The accelerator’s ability to sustain 3.1TB/s memory bandwidth during full-system encryption (via NVIDIA DPX instructions) redefines confidential computing economics for financial institutions.