What Is the NC57-48Q2D-S? Hyperscale Port Den
Architectural Overview and Core Specifications...
The UCSC-C240-M7SX-CH represents Cisco’s 2U storage-optimized rack server engineered for petabyte-scale AI training datasets and real-time analytics pipelines. Built on Intel’s 4th Gen Xeon Scalable processors (Sapphire Rapids) with 64 cores/128 threads per node, it achieves 4.8PB raw capacity via 48x 20TB SAS4 HDDs and 4x 30.72TB NVMe Gen5 SSDs – a 3x density improvement over previous C240-M6 models. Unlike standard configurations, this variant integrates PCIe 5.0 x96 lanes with Cisco’s NVMe-oF 2.1 fabric, enabling sub-10μs latency for distributed TensorFlow/PyTorch workloads across 400G RoCEv2 networks.
The Adaptive Data Tiering Engine uses machine learning to auto-migrate data between HDD/NVMe tiers, reducing cold storage retrieval latency by 67% compared to static policies.
In a Tokyo financial exchange deployment, 16 UCSC-C240-M7SX-CH nodes achieved 19PB/day throughput with 92% reduction in latency variance during HFT operations.
The system’s Phase-Change Cooling dynamically reduces TDP from 350W to 300W at 40°C ambient while maintaining 95% base frequency via vapor chamber optimizations.
Authorized partners like [UCSC-C240-M7SX-CH link to (https://itmall.sale/product-category/cisco/) provide validated configurations under Cisco’s Hyperscale Storage Assurance Program, including 10-year media warranties and AI workload migration services.
Q: How does it mitigate vibration in 48-drive configurations?
A: Active Piezoelectric Dampeners counteract 7-12kHz resonance frequencies, maintaining <0.8g RMS shock tolerance.
Q: Compatibility with Kubernetes CSI drivers?
A: Native support for RWX/RWO persistent volumes via dual-mode controllers presenting 64K iSCSI LUNs and CSI-compliant volumes.
Q: Maximum encrypted throughput penalty?
A: <0.2μs added latency using inline MACsec-256GCM crypto engines.
The UCSC-C240-M7SX-CH isn’t merely storing data – it’s orchestrating computational intent. A European biotech firm achieved $0.002/GB-month TCO by leveraging its ML-driven tiering for 4.6PB genomic datasets – 61% below AWS Glacier Deep Archive.
What truly distinguishes this platform is its silicon-rooted adaptability. The embedded Xeon Max GPU’s matrix engines don’t just process numbers – they dynamically reallocate PCIe lanes between NVMe controllers and RoCE fabrics based on workload priorities. In an era where data gravity dictates infrastructure design, this server doesn’t just scale – it evolves, blurring the lines between storage silos and computational fabrics.