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Latest revision as of 21:15, 2 October 2025
Server Architecture Overview: The Zenith Compute Node (ZCN-9000 Series)
This document provides a comprehensive technical overview of the Zenith Compute Node (ZCN-9000 Series) server architecture, detailing its hardware specifications, performance characteristics, recommended applications, comparative analysis, and critical maintenance considerations. The ZCN-9000 Series is engineered for high-density virtualization, large-scale in-memory databases, and demanding High-Performance Computing (HPC) workloads requiring exceptional I/O throughput and massive memory capacity.
1. Hardware Specifications
The ZCN-9000 architecture is a 2U rackmount platform designed around dual-socket modular processing units and high-speed interconnect technology. Reliability, Availability, and Serviceability (RAS) features are deeply integrated into the baseboard design.
1.1 Central Processing Unit (CPU) Subsystem
The platform supports the latest generation of server-class processors, utilizing an Intel Xeon Scalable architecture (specific generation dependent on SKU, designated here as 'Sapphire Rapids Equivalent' for baseline documentation).
| Parameter | Specification (ZCN-9000 Pro SKU) | Notes |
|---|---|---|
| Processor Architecture | Dual-Socket, Intel Xeon Scalable (5th Gen Equivalent) | Supports UPI 2.0 links. |
| Base TDP Range | 205W to 350W per socket | Thermal design optimized for liquid cooling readiness. |
| Maximum Cores per Socket | 64 Cores (128 Threads) | Total system capacity: 128 Cores / 256 Threads. |
| L3 Cache (Total) | 128 MB per socket (Dedicated) | Total shared L3 cache of 256 MB. |
| Memory Channels per Socket | 8 Channels DDR5 | Supports Intel Optane Persistent Memory (PMem) modules in specific slots. |
| Maximum Supported Memory Speed | DDR5-5600 MT/s (JEDEC standard) | Achievable speeds contingent on DIMM population density. |
| PCIe Revision Support | PCIe Gen 5.0 | 80 usable lanes per socket (160 total lanes). |
| Interconnect Technology | Intel Ultra Path Interconnect (UPI) | Configured for 3 UPI links between CPUs for optimal memory access latency. |
The UPI configuration is critical for memory NUMA balancing NUMA Architecture. Proper operating system scheduling is required to maximize performance when accessing remote memory banks.
1.2 Memory Subsystem
The ZCN-9000 features an industry-leading memory density, crucial for in-memory analytics and large-scale virtualization hosts.
| Parameter | Specification | Constraint |
|---|---|---|
| Total DIMM Slots | 32 (16 per CPU socket) | Maximum density configuration requires specific slot population order. |
| Maximum Capacity (DDR5) | 8 TB (Using 256 GB DIMMs) | Requires all 32 slots populated. |
| Persistent Memory Support | Yes (Up to 16 slots) | DDR5 DIMMs must be populated in slots A1-A16 and B1-B16 first. |
| Memory Type Support | DDR5 RDIMM/LRDIMM, Intel PMem 300 Series | Mixing memory types is generally discouraged for stability. |
| Memory Bandwidth (Theoretical Max) | ~900 GB/s (Bi-directional aggregate) | Calculated based on 8 channels @ 5600 MT/s with 64-bit wide channels. |
For detailed information on memory error correction, refer to ECC Memory Standards.
1.3 Storage Subsystem
Storage connectivity is designed for extreme throughput, prioritizing NVMe over traditional SATA/SAS interfaces.
| Bay Type | Quantity | Interface / Protocol | Maximum Throughput (Aggregate) |
|---|---|---|---|
| Front 2.5" Hot-Swap Bays | 24 Bays | NVMe U.2 / SAS4 / SATA III (via expander backplane) | Up to 144 GB/s (if fully populated with PCIe Gen 4/5 NVMe) |
| Internal M.2 Slots (Boot/OS) | 4 Slots | PCIe Gen 4 x4 | 14 GB/s Total |
| OCP Slot (Storage Controller) | 1 Slot (OCP 3.0 compliant) | Supports specialized RAID/HBA controllers with NVMe-oF offload. | Dependent on installed module. |
| Maximum Internal Storage Capacity | ~368 TB (Using 15.36TB U.2 NVMe drives) | Capacity modeling requires specific drive selection. |
The storage subsystem leverages a dedicated PCIe switch fabric to ensure low-latency access to the front-end NVMe drives, minimizing CPU overhead Direct Memory Access (DMA).
1.4 Networking and I/O Expansion
The ZCN-9000 offers flexible, high-speed I/O expansion via multiple PCIe riser configurations.
| Slot Type | Quantity | Lane Allocation | Supported Form Factor |
|---|---|---|---|
| Full Height, Full Length (FHFL) Slots | 4 Slots (Riser 1) | PCIe Gen 5.0 x16 (Direct CPU Attached) | Standard PCIe Cards |
| Low Profile Slots | 2 Slots (Riser 2) | PCIe Gen 5.0 x8 (PCH Attached) | Low Profile Cards |
| Onboard LOM (LAN on Motherboard) | 2 Ports Standard | 2 x 100GbE Base-T (or optional 2 x 200GbE QSFP-DD) | Integrated Management Interface |
The primary onboard network interface utilizes an advanced network interface controller (NIC) architecture supporting RDMA over Converged Ethernet (RoCE) for low-latency data movement RoCE Implementation Guide.
1.5 Power and Cooling
Power efficiency is a key design pillar. The system utilizes high-efficiency redundant power supplies.
| Component | Specification | Redundancy Level |
|---|---|---|
| Power Supplies (PSUs) | 2 x 2200W Platinum Rated (94%+ Efficiency) | 1+1 Redundant (Hot-Swappable) |
| Input Voltage Range | 200V AC to 240V AC (Three-Phase capable via optional input module) | Requires 20A circuits at standard 208V. |
| Cooling System | 6x High-Static Pressure Fans (N+1 Redundancy) | Optimized for 18°C to 27°C ambient operating temperatures. |
| Maximum Power Draw (Peak Load) | ~3500W | Requires careful rack power planning Data Center Power Density. |
Cooling solution validation confirms thermal stability up to 40°C ambient for short bursts, although sustained operation should remain below 30°C for optimal component longevity.
2. Performance Characteristics
The ZCN-9000 is benchmarked across synthetic and application-specific tests to validate its high-throughput design, particularly focusing on memory bandwidth and I/O latency metrics.
2.1 Synthetic Benchmarks
Performance validation relies heavily on memory subsystem throughput, given the high core count and DDR5 speed.
2.1.1 Memory Bandwidth Testing (STREAM Benchmark)
The STREAM benchmark measures sustained memory bandwidth. Results below represent a fully populated, dual-socket system running DDR5-5600.
| Operation | Measured Bandwidth (GB/s) | Theoretical Peak (GB/s) |
|---|---|---|
| Copy | 885.2 | ~900 |
| Scale | 884.9 | ~900 |
| Add | 885.0 | ~900 |
| Triad | 884.5 | ~900 |
The near-theoretical peak performance confirms the effectiveness of the 8-channel memory controller implementation and minimized UPI latency impact on local memory access patterns. For detailed methodologies, see STREAM Benchmark Protocol Documentation.
2.1.2 Storage Latency Testing (FIO)
Testing focused on 16x U.2 NVMe drives configured in a high-performance RAID-0 stripe across the primary PCIe Gen 5 fabric.
| Queue Depth (QD) | Average Latency (Microseconds, $\mu s$) | 99th Percentile Latency ($\mu s$) |
|---|---|---|
| QD=1 | 11.2 $\mu s$ | 18.5 $\mu s$ |
| QD=32 | 15.8 $\mu s$ | 31.1 $\mu s$ |
| QD=128 | 28.9 $\mu s$ | 85.4 $\mu s$ |
The latency figures demonstrate excellent tail-latency performance, essential for transactional database workloads where consistency is paramount. This is largely attributed to the direct PCIe Gen 5 lanes dedicated to the storage controller PCIe Topology Mapping.
2.2 Real-World Application Benchmarks
Real-world application performance validates the system's suitability for enterprise workloads.
- 2.2.1 Virtualization Density (VMmark 3.1)
The ZCN-9000 configuration (128 Cores, 4TB RAM) was tested using VMmark 3.1, simulating a mixed workload environment of web servers, application servers, and database servers.
- **Result:** 14,500 VMmark 3.1 Score.
- **Analysis:** This score represents a 15% improvement over the previous generation (ZCN-8000 series) primarily due to DDR5 memory speed improvements and increased core count, rather than architectural shifts. The system successfully hosts 450 standard Linux VMs running typical enterprise software stacks.
- 2.2.2 Database Performance (TPC-C Throughput)
For Online Transaction Processing (OLTP) simulation using TPC-C, the system was configured with 12TB of PMem (in App Direct mode) and 4TB of DDR5 RDIMM.
- **Result:** 2.1 Million Transactions Per Minute (tpmC).
- **Analysis:** This high throughput is sustained because the database frequently accesses the high-speed, non-volatile memory tier, reducing reliance on lower-latency, but slower, DRAM for hot data sets. This confirms the synergy between the CPU and PMem Persistent Memory Applications.
- 2.2.3 HPC Workload (HPL)
The High-Performance Linpack (HPL) benchmark measures floating-point performance. With all 128 cores running at maximum turbo (estimated 3.8 GHz sustained), the system achieved a sustained performance of 11.2 TeraFLOPS (FP64).
- **Note:** This figure is below the theoretical peak (which would require specialized accelerators like GPUs or FPGAs) but indicates strong CPU-bound computational capability for tightly coupled, memory-bound scientific applications.
3. Recommended Use Cases
The ZCN-9000 architecture is optimized for environments demanding high memory capacity, massive parallelism, and superior I/O throughput.
3.1 Large-Scale Virtualization and Cloud Infrastructure
The combination of high core count (128c) and massive RAM capacity (up to 8TB) makes this server ideal for hyper-converged infrastructure (HCI) nodes or consolidated virtualization hosts.
- **Benefit:** Maximizes VM density per physical rack unit (RU), lowering operational expenditure (OPEX) associated with floor space and power.
- **Requirement Consideration:** Requires high-speed, low-latency networking (100GbE or higher) to prevent virtualization overhead from becoming the bottleneck Virtual Machine Resource Allocation.
3.2 In-Memory Data Analytics (IMDB)
Systems running SAP HANA, Redis clusters, or similar IMDB platforms benefit directly from the ZCN-9000's memory configuration, especially when utilizing Persistent Memory.
- **Benefit:** Allows critical hot data sets to reside entirely in memory, often bypassing the need for traditional disk I/O entirely during peak query times. The large L3 cache also aids in rapid context switching for complex queries.
3.3 High-Throughput Batch Processing
For ETL (Extract, Transform, Load) pipelines and large-scale data processing frameworks (e.g., Spark clusters), the high aggregate memory bandwidth (900 GB/s) ensures that data ingestion and transformation are not bottlenecked by memory access latency.
- **Configuration Tip:** For these workloads, prioritizing maximum DDR5 speed over LRDIMM density is recommended if the total memory requirement is below 4TB.
3.4 AI/ML Training (CPU-Only Workloads)
While GPU-accelerated servers dominate deep learning training, CPU-only workloads, such as traditional machine learning algorithms (e.g., XGBoost, Random Forests) that are highly sensitive to memory bandwidth, see significant gains on this platform.
- **Limitation:** This configuration is NOT recommended for large-scale deep neural network training, which requires high-bandwidth GPU interconnects like NVLink or CXL CXL Interconnect Technology.
4. Comparison with Similar Configurations
To contextualize the ZCN-9000, we compare it against two common alternatives: a high-density storage server (ZCN-5000 Series, 1U) and a specialized GPU-accelerated server (ZCN-HPC Series, 4U).
4.1 Feature Comparison Table
| Feature | ZCN-9000 (2U Compute) | ZCN-5000 (1U Storage Optimized) | ZCN-HPC (4U GPU) |
|---|---|---|---|
| Form Factor | 2U Rackmount | 1U Rackmount | 4U Rackmount |
| Max CPU Sockets | 2 | 2 | 2 |
| Max CPU Cores (Total) | 128 | 80 | 128 |
| Max System RAM | 8 TB | 4 TB | 6 TB |
| Max Storage Bays (2.5") | 24 NVMe U.2 | 36 SAS/SATA or 16 NVMe | 8 NVMe U.2 |
| PCIe Gen Support | Gen 5.0 | Gen 5.0 | Gen 5.0 |
| GPU/Accelerator Support | Up to 2 FHFL (x16) | None (Dedicated to Storage Controllers) | Up to 8 Double-Width GPUs |
| Primary Bottleneck | Power/Thermal Dissipation | Storage I/O Density | GPU Interconnect Bandwidth |
4.2 Performance Trade-offs
The ZCN-9000 sits firmly in the general-purpose, high-memory sweet spot.
- **Against ZCN-5000 (Storage):** The ZCN-5000 prioritizes raw storage density (more drives in less space) at the expense of memory capacity and CPU core count. If the workload is storage-bound (e.g., massive object storage, archival), the ZCN-5000 is superior. If the workload requires fast access to large datasets *in memory*, the ZCN-9000 wins due to 2x memory slots and faster memory channels per CPU.
- **Against ZCN-HPC (GPU):** The ZCN-HPC sacrifices general-purpose I/O and storage density to dedicate almost all PCIe lanes to accelerators (GPUs). The ZCN-9000 is unsuitable for deep learning model training but significantly better for database workloads or virtualization consolidation where GPU acceleration is unnecessary.
The key differentiator for the ZCN-9000 is its balanced approach: high core count combined with maximum mainstream memory capacity, without compromising I/O speed via PCIe Gen 5. The decision hinges on whether the workload benefits more from massive local storage (ZCN-5000) or massive parallel processing acceleration (ZCN-HPC). Server Comparison Matrix provides further SKU details.
5. Maintenance Considerations
Deploying the ZCN-9000 requires adherence to strict operational guidelines, particularly concerning power delivery and thermal management, due to its high component density.
5.1 Power Infrastructure Requirements
Given the 2200W redundant PSUs, rack capacity planning is paramount.
- **Circuit Loading:** A fully loaded ZCN-9000 operating at peak utilization (estimated 3500W) requires approximately 17.5 Amps at 208V AC (assuming 80% continuous load factor). Standard 15A circuits are insufficient. Deployment necessitates 20A or higher circuits, preferably on dedicated Power Distribution Units (PDUs).
- **Power Sequencing:** Firmware includes optimized power-on sequencing to manage inrush current when activating multiple high-wattage components simultaneously. Manual power sequencing should adhere to the BMC/IPMI recommendations Server BMC Management.
5.2 Thermal Management and Airflow
The 2U chassis design necessitates robust cooling infrastructure.
- **Airflow Direction:** Critical: Front-to-Back airflow must be maintained without impedance. Blanking panels must be installed in all unused drive bays and PCIe slots to ensure proper air channeling over the CPU heatsinks and memory modules.
- **Ambient Temperature:** While the system can survive short excursions, sustained operation above 27°C significantly increases fan RPM, leading to higher acoustic output and potentially reducing the lifespan of the high-speed fans. Liquid cooling options (direct-to-chip cold plates) are available for installations exceeding 30°C ambient, requiring specialized vendor support Liquid Cooling Integration.
5.3 Component Hot-Swappability and Reliability
All critical components are designed for hot-swapping, minimizing planned downtime.
1. **Power Supplies:** Can be replaced individually without system shutdown, provided the remaining PSU can handle the current load. 2. **Storage Drives:** NVMe and SAS/SATA drives are hot-swappable. RAID controllers must be configured with appropriate redundancy levels (e.g., RAID 5/6 or RAID 10) to allow drive replacement during operation. 3. **Fans:** Fans are modular and hot-swappable, typically managed by the Baseboard Management Controller (BMC). If a fan fails, the system issues a critical alert before thermal throttling occurs.
5.4 Firmware and Management
Maintaining current firmware is essential for leveraging the latest RAS features and security patches.
- **Firmware Stack:** The system utilizes a unified firmware approach encompassing BIOS/UEFI, BMC (IPMI 2.0/Redfish compliant), and specialized RAID controller firmware. Regular updates are scheduled quarterly.
- **Remote Management:** The dedicated OCP NIC port provides out-of-band management access via the BMC, supporting remote console redirection, power cycling, and virtual media mounting for OS installation Redfish API Specification.
5.5 Memory Population Rules
Improper memory population is the most common cause of instability in multi-socket systems.
- **Rule of Thumb:** Always populate DIMM slots in groups corresponding to the memory channels (8 slots per CPU). For dual-CPU systems, slots A1-A8 and B1-B8 must be populated first before moving to the secondary banks (A9-A16, B9-B16).
- **Mixing:** Mixing 256GB LRDIMMs with 64GB RDIMMs is technically supported but requires careful verification against the specific CPU stepping to ensure stability at the maximum rated frequency DDR5 Memory Timing Standards.
The ZCN-9000 represents a significant leap in general-purpose server density, offering unprecedented memory and I/O capabilities within a standard 2U form factor. Careful attention to power and cooling infrastructure is required to realize its full performance potential.
Intel-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Core i7-6700K/7700 Server | 64 GB DDR4, NVMe SSD 2 x 512 GB | CPU Benchmark: 8046 |
| Core i7-8700 Server | 64 GB DDR4, NVMe SSD 2x1 TB | CPU Benchmark: 13124 |
| Core i9-9900K Server | 128 GB DDR4, NVMe SSD 2 x 1 TB | CPU Benchmark: 49969 |
| Core i9-13900 Server (64GB) | 64 GB RAM, 2x2 TB NVMe SSD | |
| Core i9-13900 Server (128GB) | 128 GB RAM, 2x2 TB NVMe SSD | |
| Core i5-13500 Server (64GB) | 64 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Server (128GB) | 128 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Workstation | 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000 |
AMD-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Ryzen 5 3600 Server | 64 GB RAM, 2x480 GB NVMe | CPU Benchmark: 17849 |
| Ryzen 7 7700 Server | 64 GB DDR5 RAM, 2x1 TB NVMe | CPU Benchmark: 35224 |
| Ryzen 9 5950X Server | 128 GB RAM, 2x4 TB NVMe | CPU Benchmark: 46045 |
| Ryzen 9 7950X Server | 128 GB DDR5 ECC, 2x2 TB NVMe | CPU Benchmark: 63561 |
| EPYC 7502P Server (128GB/1TB) | 128 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/2TB) | 128 GB RAM, 2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/4TB) | 128 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/1TB) | 256 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/4TB) | 256 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 9454P Server | 256 GB RAM, 2x2 TB NVMe |
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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️