Cisco UCSX-CPU-I8568Y+= Processor: Architectu
Core Architecture and Technical Specifications...
Technical Architecture & Design Philosophy
The HCI-RIS3A-24XM7= is a triple-slot PCIe Gen4 x16 riser designed for Cisco’s Compute Hyperconverged X-Series M7 nodes, specifically engineered to handle AI/ML training clusters and NVMe-oF storage expansions. Based on Cisco’s 2024 HCI-X architecture documentation, this module enables 4x NVIDIA H100 GPUs or 24x E1.S NVMe drives in 2U chassis configurations. Key innovations include:
- PCIe 4.0 Lane Partitioning: Supports x8x8x8x8 bifurcation for multi-GPU parallelism or x4x4 splitting for storage arrays
- Dynamic Thermal Throttling: 80mm counter-rotating fans maintain component temps below 85°C at 45dB(A) noise levels
- Intersight Integration: Auto-configures SR-IOV policies for VMware vSphere/Red Hat OpenShift clusters
Performance Benchmarks & Use Case Optimization
AI Acceleration Capabilities
When configured with NVIDIA H100 GPUs:
- FP8 Tensor Performance: 3.9 petaFLOPS per 2U chassis using 4x GPUs
- NVLink 4.0 Support: Reduces inter-GPU latency by 60% compared to PCIe-switched designs
- vGPU Density: 32 virtual instances per physical GPU via Cisco-UCS-V100-32G profiles
Storage-Centric Configurations
With 24x Kioxia CM7 E1.S NVMe drives:
- Sequential Throughput: 58 GB/s read & 49 GB/s write (4K block size)
- RAID 5 Hardware Offload: 1.2M IOPS sustained via Cisco VIC 1527 adapters
- TCO Reduction: 40% lower power consumption than U.2-based solutions
Addressing Critical Deployment Concerns
“Is it compatible with existing HyperFlex HX220c M6 nodes?”
No. The module requires:
- Cisco UCS Manager 5.4+ for Gen4 link training
- M7-specific backplane with PCIe retimers
- Intersight Managed Mode (IMM) for automated firmware updates
“How does it compare to HCI-RIS2B-24XM7=?”
| Metric | HCI-RIS3A-24XM7= | HCI-RIS2B-24XM7= |
|---|---|---|
| Slot Configuration | Triple-width | Dual-width |
| Max GPU TDP Support | 450W per device | 300W per device |
| NVMe Drive Capacity | 24x E1.S | 16x U.2 |
| Power Efficiency | 94% @ 50% load | 89% @ 50% load |
| Ideal Workload | LLM Training | Real-time Analytics |
“What cooling infrastructure is required?”
- Front-to-Back Airflow: Minimum 300 LFM at 35°C intake
- Liquid Cooling Ready: Supports CDU-LX3000 rear-door heat exchangers
- Altitude Derating: 1% performance loss per 300m above 1,500m ASL
Procurement & Validation Recommendations
For guaranteed interoperability with Cisco HyperFlex M7 systems, HCI-RIS3A-24XM7= is available through certified channels like itmall.sale. Validate configurations using:
- Cisco HCI Sizing Tool 5.3+ for thermal/power modeling
- NVIDIA AI Enterprise 4.0 compatibility matrices
- Intersight Workload Optimizer for SLA-based resource allocation
Operational Perspective
The HCI-RIS3A-24XM7= represents Cisco’s strategic shift toward disaggregated resource scaling in hyperconverged environments. While its 24x E1.S NVMe configuration delivers unmatched storage density for Splunk/Hadoop clusters, the real value emerges in hybrid deployments – pairing 2x H100 GPUs with 12x NVMe caching tiers reduces PyTorch model training times by 45% compared to traditional SAN architectures. However, enterprises must balance its $/Watt premium against actual workload profiles: overprovisioning Gen4 lanes for legacy VDI workloads often yields negative ROI. Always cross-reference thermal simulations using Cisco’s HCI-X CFD Modeling Suite before deployment, as improper airflow distribution in multi-rack installations can degrade GPU boost clocks by 22%.