Template:DocumentationFooter
- Template:DocumentationFooter: High-Density Compute Node (HDCN-v4.2)
This technical documentation details the specifications, performance characteristics, recommended applications, comparative analysis, and maintenance requirements for the **Template:DocumentationFooter** server configuration, hereafter referred to as the High-Density Compute Node, version 4.2 (HDCN-v4.2). This configuration is optimized for virtualization density, large-scale in-memory processing, and demanding HPC workloads requiring extreme thread density and high-speed interconnectivity.
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- 1. Hardware Specifications
The HDCN-v4.2 is built upon a dual-socket, 4U rackmount chassis designed for maximum component density while adhering to strict thermal dissipation standards. The core philosophy of this design emphasizes high core count, massive RAM capacity, and low-latency storage access.
- 1.1. System Board and Chassis
The foundation of the HDCN-v4.2 is the proprietary Quasar-X1000 motherboard, utilizing the latest generation server chipset architecture.
| Component | Specification |
|---|---|
| Chassis Form Factor | 4U Rackmount (EIA-310 compliant) |
| Motherboard Model | Quasar-X1000 Dual-Socket Platform |
| Chipset Architecture | Dual-Socket Server Platform with UPI 2.0/Infinity Fabric Link |
| Maximum Power Delivery (PSU) | 3000W (3+1 Redundant, Titanium Efficiency) |
| Cooling System | Direct-to-Chip Liquid Cooling Ready (Optional Air Cooling Available) |
| Expansion Slots (Total) | 8x PCIe 5.0 x16 slots (Full Height, Full Length) |
| Integrated Networking | 2x 100GbE (QSFP56-DD) and 1x OCP 3.0 Slot (Configurable) |
| Management Controller | BMC 4.0 with Redfish API Support |
- 1.2. Central Processing Units (CPUs)
The HDCN-v4.2 mandates the use of high-core-count, low-latency processors optimized for multi-threaded workloads. The standard configuration specifies two processors configured for maximum core density and memory bandwidth utilization.
| Parameter | Specification (Per Socket) |
|---|---|
| Processor Model (Standard) | Intel Xeon Scalable (Sapphire Rapids-EP equivalent) / AMD EPYC Genoa equivalent |
| Core Count (Nominal) | 64 Cores / 128 Threads (Minimum) |
| Maximum Core Count Supported | 96 Cores / 192 Threads |
| Base Clock Frequency | 2.4 GHz |
| Max Turbo Frequency (Single Thread) | Up to 3.8 GHz |
| L3 Cache (Total Per CPU) | 128 MB |
| Thermal Design Power (TDP) | 350W (Nominal) |
| Memory Channels Supported | 8 Channels DDR5 (Per Socket) |
The selection of processors must be validated against the Dynamic Power Management Policy (DPMP) governing the specific data center deployment. Careful consideration must be given to NUMA Architecture topology when configuring related operating system kernel tuning.
- 1.3. Memory Subsystem
This configuration is designed for memory-intensive applications, supporting the highest available density and speed for DDR5 ECC Registered DIMMs (RDIMMs).
| Parameter | Specification |
|---|---|
| Total DIMM Slots | 32 (16 per CPU) |
| Maximum Capacity | 8 TB (Using 256GB LRDIMMs, if supported by BIOS revision) |
| Standard Configuration (Density Focus) | 2 TB (Using 64GB DDR5-4800 RDIMMs, 32 DIMMs populated) |
| Memory Type Supported | DDR5 ECC RDIMM / LRDIMM |
| Memory Bandwidth (Theoretical Max) | ~1.2 TB/s Aggregate |
| Memory Speed (Standard) | DDR5-5600 MHz (All channels populated at JEDEC standard) |
| Memory Mirroring/Lockstep Support | Yes, configurable via BIOS settings. |
It is critical to adhere to the DIMM Population Guidelines to maintain optimal memory interleaving and avoid performance degradation associated with uneven channel loading.
- 1.4. Storage Subsystem
The HDCN-v4.2 prioritizes ultra-low latency storage access, typically utilizing NVMe SSDs connected directly via PCIe lanes to bypass traditional HBA bottlenecks.
| Location/Type | Quantity (Standard) | Interface/Throughput |
|---|---|---|
| Front Bay U.2 NVMe (Hot-Swap) | 8 Drives | PCIe 5.0 x4 per drive (Up to 14 GB/s aggregate) |
| Internal M.2 Boot Drives (OS/Hypervisor) | 2 Drives (Mirrored) | PCIe 4.0 x4 |
| Storage Controller | Software RAID (OS Managed) or Optional Hardware RAID Card (Requires 1x PCIe Slot) | |
| Maximum Raw Capacity | 640 TB (Using 80TB U.2 NVMe drives) |
For high-throughput applications, the use of NVMe over Fabrics (NVMe-oF) is recommended over local storage arrays, leveraging the high-speed 100GbE adapters.
- 1.5. Accelerators and I/O Expansion
The dense PCIe layout allows for significant expansion, crucial for AI/ML, advanced data analytics, or specialized network processing.
| Slot Type | Count | Max Power Draw per Slot |
|---|---|---|
| PCIe 5.0 x16 (FHFL) | 8 | 400W (Requires direct PSU connection) |
| OCP 3.0 Slot | 1 | NIC/Storage Adapter |
| Total Available PCIe Lanes (CPU Dependent) | 160 Lanes (Typical Configuration) |
The system supports dual-width, passively cooled accelerators, requiring the advanced liquid cooling option for sustained peak performance, as detailed in Thermal Management Protocols.
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- 2. Performance Characteristics
The HDCN-v4.2 exhibits performance characteristics defined by its high thread count and superior memory bandwidth. Benchmarks are standardized against previous generation dual-socket systems (HDCN-v3.1).
- 2.1. Synthetic Benchmarks
Performance metrics are aggregated across standardized tests simulating heavy computational load across all available CPU cores and memory channels.
| Benchmark Category | HDCN-v3.1 (Baseline) | HDCN-v4.2 (Standard Configuration) | Performance Uplift (%) |
|---|---|---|---|
| SPECrate 2017 Integer (Multi-Threaded) | 100 | 195 | +95% |
| STREAM Triad (Memory Bandwidth) | 100 | 170 | +70% |
| IOPS (4K Random Read - Local NVMe) | 100 | 155 | +55% |
| Floating Point Operations (HPL Simulation) | 100 | 210 (Due to AVX-512/AMX enhancement) | +110% |
The substantial uplift in Floating Point Operations is directly attributable to the architectural improvements in **Vector Processing Units (VPUs)** and specialized AI accelerator instructions supported by the newer CPU generation.
- 2.2. Virtualization Density Metrics
When deployed as a hypervisor host (e.g., running VMware ESXi or KVM Hypervisor), the HDCN-v4.2 excels in maximizing Virtual Machine (VM) consolidation ratios while maintaining acceptable Quality of Service (QoS).
- **vCPU to Physical Core Ratio:** Recommended maximum ratio is **6:1** for general-purpose workloads and **4:1** for latency-sensitive applications. This allows for hosting up to 768 virtual threads reliably.
- **Memory Oversubscription:** Due to the 2TB standard configuration, memory oversubscription rates of up to 1.5x are permissible for burstable workloads, though careful monitoring of Page Table Management overhead is required.
- **Network Latency:** End-to-end latency across the integrated 100GbE ports averages **2.1 microseconds (µs)** under 60% load, which is critical for distributed database synchronization.
- 2.3. Power Efficiency (Performance per Watt)
Despite the high TDP of individual components, the architectural efficiency gains result in superior performance per watt compared to previous generations.
- **Peak Power Draw (Fully Loaded):** Approximately 2,800W (with 8x mid-range GPUs or 4x high-end accelerators).
- **Idle Power Draw:** Under minimal load (OS running, no active tasks), the system maintains a draw of **~280W**, significantly lower than the 450W baseline of the HDCN-v3.1.
- **Performance/Watt Ratio:** Achieves a **68% improvement** in computational throughput per kilowatt-hour utilized compared to the HDCN-v3.0 platform, directly impacting Data Center Operational Expenses.
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- 3. Recommended Use Cases
The HDCN-v4.2 configuration is not intended for low-density, general-purpose web serving. Its high cost and specialized requirements dictate deployment in environments where maximizing resource density and raw computational throughput is paramount.
- 3.1. High-Performance Computing (HPC) and Scientific Simulation
The combination of high core count, massive memory bandwidth, and support for high-speed interconnects (via PCIe 5.0 lanes dedicated to InfiniBand/Omni-Path adapters) makes it ideal for tightly coupled simulations.
- **Molecular Dynamics (MD):** Excellent throughput for force calculations across large datasets residing in memory.
- **Computational Fluid Dynamics (CFD):** Effective use of high core counts for grid calculations, especially when coupled with GPU accelerators for matrix operations.
- **Weather Modeling:** Supports large global grids requiring substantial L3 cache residency.
- 3.2. Large-Scale Data Analytics and In-Memory Databases
Systems requiring rapid access to multi-terabyte datasets benefit immensely from the 2TB+ memory capacity and the low-latency NVMe storage tier.
- **In-Memory OLTP Databases (e.g., SAP HANA):** The configuration meets or exceeds the requirements for Tier-1 SAP HANA deployments requiring rapid transactional processing across large tables.
- **Big Data Processing (Spark/Presto):** High core counts accelerate job execution times by allowing more executors to run concurrently within the host environment.
- **Real-Time Fraud Detection:** Low I/O latency is crucial for scoring transactions against massive feature stores held in RAM.
- 3.3. Deep Learning Training (Hybrid CPU/GPU)
While specialized GPU servers exist, the HDCN-v4.2 excels in scenarios where the CPU must manage significant data preprocessing, feature engineering, or complex model orchestration alongside the accelerators.
- **Data Preprocessing Pipelines:** The high core count accelerates ETL tasks required before GPU ingestion.
- **Model Serving (High Throughput):** When serving large language models (LLMs) where the model weights must be swapped rapidly between system memory and accelerator VRAM, the high aggregate memory bandwidth is a decisive factor.
- 3.4. Dense Virtual Desktop Infrastructure (VDI)
For VDI deployments targeting knowledge workers (requiring 4-8 vCPUs and 16-32 GB RAM per user), the HDCN-v4.2 allows for consolidation ratios exceeding typical enterprise averages, reducing the overall physical footprint required for large user populations. This requires careful adherence to the VDI Resource Allocation Guidelines.
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- 4. Comparison with Similar Configurations
To contextualize the HDCN-v4.2, it is compared against two common alternative server configurations: the High-Frequency Workstation (HFW-v2.1) and the Standard 2U Dual-Socket Server (SDS-v5.0).
- 4.1. Configuration Profiles
| Feature | HDCN-v4.2 (Focus: Density/Bandwidth) | SDS-v5.0 (Focus: Balance/Standardization) | HFW-v2.1 (Focus: Single-Thread Speed) | | :--- | :--- | :--- | :--- | | **Chassis Size** | 4U | 2U | 2U (Tower/Rack Convertible) | | **Max Cores (Total)** | 192 (2x 96-core) | 128 (2x 64-core) | 64 (2x 32-core) | | **Max RAM Capacity** | 8 TB | 4 TB | 2 TB | | **Primary PCIe Gen** | PCIe 5.0 | PCIe 4.0 | PCIe 5.0 | | **Storage Bays** | 8x U.2 NVMe | 12x 2.5" SAS/SATA | 4x M.2/U.2 | | **Power Delivery** | 3000W Redundant | 2000W Redundant | 1600W Standard | | **Interconnect Support** | Native 100GbE + OCP 3.0 | 25/50GbE Standard | 10GbE Standard |
- 4.2. Performance Trade-offs Analysis
The comparison highlights the specific trade-offs inherent in choosing the HDCN-v4.2.
| Metric | HDCN-v4.2 Advantage | HDCN-v4.2 Disadvantage |
|---|---|---|
| Aggregate Throughput (Total Cores) | Highest in class (192 Threads) | Higher idle power consumption than SDS-v5.0 |
| Single-Thread Performance | Lower peak frequency than HFW-v2.1 | Requires workload parallelization for efficiency |
| Memory Bandwidth | Superior (DDR5 8-channel per CPU) | Higher cost per GB of installed RAM |
| Storage I/O Latency | Excellent (Direct PCIe 5.0 NVMe access) | Fewer total drive bays than SDS-v5.0 (if SAS/SATA is required) |
| Rack Density (Compute $/U) | Excellent | Poorer Cooling efficiency under air-cooling scenarios |
The decision to deploy HDCN-v4.2 over the SDS-v5.0 is justified when the application scaling factor exceeds the 1.5x core count increase and requires PCIe 5.0 or memory capacities exceeding 4TB. Conversely, the HFW-v2.1 configuration is preferred for legacy applications sensitive to clock speed rather than thread count, as detailed in CPU Microarchitecture Selection.
- 4.3. Cost of Ownership (TCO) Implications
While the initial Capital Expenditure (CapEx) for the HDCN-v4.2 is significantly higher (estimated 30-40% premium over SDS-v5.0), the reduced Operational Expenditure (OpEx) derived from superior rack density and improved performance-per-watt can yield a lower Total Cost of Ownership (TCO) over a five-year lifecycle for high-utilization environments. Detailed TCO modeling must account for Data Center Power Utilization Effectiveness (PUE) metrics.
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- 5. Maintenance Considerations
The high component density and reliance on advanced interconnects necessitate stringent maintenance protocols, particularly concerning thermal management and firmware updates.
- 5.1. Thermal Management and Cooling Requirements
The 350W TDP CPUs and potential high-power PCIe accelerators generate substantial heat flux, requiring specialized cooling infrastructure.
- **Air Cooling (Minimum Requirement):** Requires a minimum sustained airflow of **120 CFM** across the chassis with inlet temperatures not exceeding **22°C (71.6°F)**. Standard 1000W PSU configurations are insufficient when utilizing more than two high-TDP accelerators.
- **Liquid Cooling (Recommended):** For sustained peak performance (above 80% utilization for more than 4 hours), the optional Direct-to-Chip (D2C) liquid cooling loop is mandatory. This requires integration with the facility's Chilled Water Loop Infrastructure.
* *Coolant Flow Rate:* Minimum 1.5 L/min per CPU block. * *Coolant Temperature:* Must be maintained between 18°C and 25°C.
Failure to adhere to thermal guidelines will trigger automatic frequency throttling via the BMC, resulting in CPU clock speeds dropping below 1.8 GHz, effectively negating the performance benefits of the configuration. Refer to Thermal Throttling Thresholds for specific sensor readings.
- 5.2. Power Delivery and Redundancy
The 3000W Titanium-rated PSUs are designed for N+1 redundancy.
- **Power Draw Profile:** The system exhibits a high inrush current during cold boot due to the large capacitance required by the DDR5 memory channels and numerous NVMe devices. Power Sequencing Protocols must be strictly followed when bringing up racks containing more than 10 HDCN-v4.2 units simultaneously.
- **Firmware Dependency:** The BMC firmware version must be compatible with the PSU management subsystem. An incompatibility can lead to inaccurate power reporting or failure to properly handle load shedding during power events.
- 5.3. Firmware and BIOS Management
Maintaining the **Quasar-X1000** platform requires disciplined firmware hygiene.
1. **BIOS Updates:** Critical updates often contain microcode patches necessary to mitigate security vulnerabilities (e.g., Spectre/Meltdown variants) and, crucially, adjust voltage/frequency curves for memory stability at higher speeds (DDR5-5600+). 2. **BMC/Redfish:** The Baseboard Management Controller (BMC) must run the latest version to ensure accurate monitoring of the 16+ temperature sensors across the dual CPUs and the PCIe backplane. Automated configuration deployment should use the Redfish API for idempotent state management. 3. **Storage Controller Firmware:** NVMe firmware updates are often released independently of the OS/BIOS and are vital for mitigating drive wear-out issues or addressing specific performance regressions noted in NVMe Drive Life Cycle Management.
- 5.4. Diagnostics and Troubleshooting
Due to the complex I/O topology (multiple UPI links, 8 memory channels per socket), standard diagnostic tools may not expose the root cause of intermittent performance degradation.
- **Memory Debugging:** Errors often manifest as subtle instability under high load rather than hard crashes. Utilizing the BMC's integrated memory scrubbing logs and ECC Error Counters is essential for isolating faulty DIMMs or marginal CPU memory controllers.
- **PCIe Lane Verification:** Tools capable of reading the PCIe configuration space (e.g., `lspci -vvv` on Linux, or equivalent BMC diagnostics) must be used to confirm that all installed accelerators are correctly enumerated on the expected x16 lanes, especially after hardware swaps. Misconfiguration can lead to performance degradation (e.g., running at x8 speed).
The high density of the HDCN-v4.2 means that troubleshooting often requires removing components from the chassis, emphasizing the importance of hot-swap capabilities for all primary storage and networking components.
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- This documentation serves as the primary technical reference for the deployment and maintenance of the HDCN-v4.2 server configuration. All operational staff must be trained on the specific power and thermal profiles detailed herein.*
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.* ⚠️