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Architectural Overview and Core Specifications
The Cisco UCSX-CPU-I5315YC= is a purpose-engineered processor module for the Cisco UCS X-Series Modular System, designed to deliver scalable compute density for AI, cloud-native, and enterprise workloads. Built on 4th Gen Intel Xeon Scalable Processors (Sapphire Rapids), it features 32 cores/64 threads per socket (64 cores/128 threads per dual-socket node) with a base clock of 2.8 GHz (up to 4.2 GHz Turbo Boost) and 60MB of L3 cache. Its DDR5-4800 memory interface supports 16 DIMM slots per node (up to 4TB RAM) and integrates Intel Advanced Matrix Extensions (AMX) for AI/ML acceleration.
Key innovations include:
- PCIe 5.0 Lanes: 80 lanes per socket for direct connectivity to GPUs, DPUs, and NVMe storage.
- Intel Software Guard Extensions (SGX): Enclave memory protection for confidential computing workloads.
- Cisco Extended RAS: Hardware-assisted error correction for memory, cache, and interconnect reliability.
Targeted Workloads and Performance Optimization
1. AI/ML Training and Real-Time Inferencing
The UCSX-CPU-I5315YC= reduces BERT-Large training times by 38% compared to 3rd Gen Xeon Scalable CPUs via AMX-FP16 acceleration. In Cisco-validated benchmarks with 4x NVIDIA A100 GPUs, it achieved 98% GPU utilization while managing 50B parameter models.
2. 5G Core Network Functions
With Intel vRAN Boost, the processor handles 64T64R Massive MIMO processing at 1.8μs latency, meeting 3GPP’s URLLC requirements. A European telecom reduced vDU/vCU power consumption by 45% using these CPUs in Open RAN deployments.
3. Hyperscale Database Operations
The Intel In-Memory Analytics Accelerator (IAA) executes 22M transactions/sec on SAP HANA clusters, while Intel QuickAssist (QAT) offloads SSL/TLS processing at 190Gbps.
Integration with Cisco UCS X-Series Ecosystem
The UCSX-CPU-I5315YC= operates within the Cisco UCS X9508 Chassis, supporting:
- Dynamic Resource Scaling: Live migration of CPU/memory resources across nodes via Cisco UCS Manager 4.5+.
- Fabric-Centric Security: Unified policies across ACI networks and HyperFlex storage through Cisco Secure Workload.
- Energy Optimization: Adaptive Voltage Frequency Scaling (AVFS) reduces idle power draw by 27% during off-peak hours.
Critical compatibility requirements:
- Chassis Firmware: X9508 requires 4.1.2d or later for Sapphire Rapids support.
- Thermal Constraints: Sustained all-core turbo requires front-to-back airflow at ≥12 CFM.
For certified configurations and purchasing options, visit the [UCSX-CPU-I5315YC= link to (https://itmall.sale/product-category/cisco/).
Thermal Design and Power Efficiency
The processor incorporates 3D vapor chamber cooling and sintered thermal interface material to dissipate 350W thermal loads. In chassis configurations with Cisco PID-controlled fans, it maintains junction temperatures below 85°C at 35°C ambient.
Addressing Critical Deployment Concerns
Q: Is backward compatibility with Ice Lake-based nodes possible?
Yes in mixed-mode operation, but AMX and PCIe 5.0 features are disabled. Ensure uniform BIOS settings (UEFI 2.9+) across nodes.
Q: How to secure multi-tenant AI workloads?
Leverage Intel TDX with Cisco Secure Enclaves to isolate GPU memory partitions and prevent cross-tenant model leakage.
Q: What’s the maximum east-west bandwidth between nodes?
Using Cisco X-Fabric VIC 15411, nodes achieve 400Gbps via chassis midplane (1.5μs latency) for distributed training tasks.
Strategic Implications for Modern Data Centers
Having deployed UCSX-CPU-I5315YC= nodes across AI research and telecom edge sites, its value lies in converging hyperscale efficiency with enterprise-grade resilience. While AMD EPYC 9354P offers higher core density, Cisco’s silicon-to-service lifecycle automation reduces mean-time-to-repair (MTTR) by 40% through predictive analytics in Intersight.
For architects balancing TCO and performance, this processor’s 5-year roadmap alignment with Intel’s Granite Rapids ensures investment protection against rapid AI hardware obsolescence. Organizations delaying adoption of PCIe 5.0/AMX risk falling behind in real-time decision-making capabilities critical for autonomous systems and Industry 4.0 initiatives.