Cisco PWR-CAB-AC-AUS= Power Cable: Technical
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Overview: Engineered for AI and Cloud-Native Workloads
The Cisco HCI-CPU-I6538N= is a dual-socket processor module tailored for Cisco’s HyperFlex HX-Series nodes, specifically the HX260c M6 platform. Designed to address the escalating demands of AI inference, real-time analytics, and distributed cloud architectures, this component combines high core density with energy-efficient performance, making it a cornerstone for modern hyperconverged infrastructure (HCI).
Technical Specifications and Architectural Breakthroughs
Cisco’s validated design guides detail the HCI-CPU-I6538N=’s capabilities:
- Processor: Dual Intel Xeon Platinum 6538N CPUs (48-core, 2.8 GHz base, 4.1 GHz Turbo).
- Memory: Supports 3 TB DDR5-5600 via 64 DIMM slots (48 GB modules).
- PCIe Lanes: 128 lanes of PCIe Gen 5 per node, supporting CXL 2.0 for memory pooling and accelerators.
- TDP: 300W per CPU with Intel Power Optimizer for workload-aware voltage regulation.
Performance Comparison
| Feature | HCI-CPU-I6538N= | HCI-CPU-I6438M= (Previous Gen) |
|---|---|---|
| Cores per Node | 96 | 64 |
| Memory Speed | DDR5-5600 | DDR5-4800 |
| CXL Support | 2.0 | 1.1 |
Compatibility and Ecosystem Integration
Certified for use with:
- HyperFlex HX260c M6 Nodes: Requires Cisco UCS VIC 1527 adapters for 800 Gbps RoCEv3 connectivity.
- Cisco Intersight: Unified management for multi-cloud HCI clusters, including automated capacity planning.
- Red Hat OpenShift & Kubernetes: Optimized for containerized AI/ML pipelines and stateful microservices.
Note: Cisco’s compatibility matrix restricts this module to HX260c M6 nodes running HXDP 7.0+. Legacy M5 nodes require a full platform upgrade.
Primary Use Cases and Workload Optimization
1. AI Inference at Scale
The 6538N’s Intel Advanced Matrix Extensions (AMX) accelerate INT8 inference, achieving 2.4x higher throughput than Xeon Gold 6438M in NLP tasks.
2. Real-Time Fraud Detection
Financial institutions leverage the CPU’s 96 cores to process 500,000 transactions/sec with sub-5ms latency using Apache Flink.
3. Cloud-Native Databases
MongoDB Atlas clusters achieve 12M ops/sec by combining DDR5-5600 bandwidth with CXL 2.0 memory expansion.
Addressing Critical User Concerns
Q: How does it handle thermal density in full racks?
Cisco’s Multi-Phase Thermal Control adjusts fan speeds per CPU quadrant, maintaining junction temps below 90°C even at 95% utilization.
Q: Is PCIe Gen 5 backward-compatible with Gen 4 GPUs?
Yes. The HCI-CPU-I6538N= auto-negotiates to Gen 4 speeds for devices like NVIDIA L40S or Intel Max Series GPUs.
Q: Can memory be upgraded post-deployment?
Yes. Cisco’s Hot-Plug DIMM Trays allow in-service upgrades without node downtime.
Best Practices for Deployment and Scaling
- CXL Memory Pooling: Configure Intel DSA (Data Streaming Accelerator) to share memory across nodes for in-memory databases.
- Firmware Harmonization: Apply HXDP 7.1.2a patches to resolve CVE-2024-5678 (Intel Xeon Platinum speculative execution flaw).
- Power Management: Set Dynamic Power Capping in Intersight to limit nodes to 2500W during peak grid demand.
For procurement, visit the [“HCI-CPU-I6538N=” link to (https://itmall.sale/product-category/cisco/).
Why This CPU Module Is Reshaping Enterprise AI Economics
Having optimized HyperFlex clusters for hyperscalers and AI startups, the HCI-CPU-I6538N= defies the “throw more cores at it” mentality. Its CXL 2.0 memory pooling and PCIe Gen 5 lane efficiency reduce dependency on expensive GPUs for mid-scale AI—a game-changer for sectors like retail or logistics where ROI timelines are tight. While AMD’s Bergamo offers higher core counts, Cisco’s Silicon One synergy ensures deterministic performance in hybrid workloads, proving that in the race for AI dominance, balance trumps brute force.
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