Data Center Environmental Monitoring
```mediawiki This is a comprehensive technical documentation article for the server configuration designated as **Template:DocumentationPage**. This configuration represents a high-density, dual-socket system optimized for enterprise virtualization and high-throughput database operations.
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- Technical Documentation: Server Configuration Template:DocumentationPage
This document details the hardware specifications, performance metrics, recommended operational profiles, comparative analysis, and required maintenance protocols for the standardized server configuration designated as **Template:DocumentationPage**. This baseline configuration is engineered for maximum platform stability and high-density workload consolidation within enterprise data center environments.
- 1. Hardware Specifications
The Template:DocumentationPage utilizes a leading-edge dual-socket motherboard architecture, maximizing the core count while maintaining stringent power efficiency targets. All components are validated for operation within a 40°C ambient temperature range.
- 1.1 Core Processing Unit (CPU)
The configuration mandates the use of Intel Xeon Scalable processors (4th Generation, codenamed Sapphire Rapids). The specific SKU selection prioritizes a balance between high core frequency and maximum available PCIe lane count for I/O expansion.
Parameter | Specification | Notes |
---|---|---|
Processor Model | Intel Xeon Gold 6438M (Example Baseline) | Optimized for memory capacity and moderate core count. |
Socket Count | 2 | Dual-socket configuration. |
Base Clock Speed | 2.0 GHz | Varies based on specific SKU selected. |
Max Turbo Frequency | Up to 4.0 GHz (Single Core) | Dependent on thermal headroom and workload intensity. |
Core Count (Total) | 32 Cores (64 Threads) per CPU (64 Cores Total) | Total logical processors available. |
L3 Cache (Total) | 120 MB per CPU (240 MB Total) | High-speed shared cache for improved data locality. |
TDP (Thermal Design Power) | 205W per CPU | Requires robust cooling solutions; see Section 5. |
Further details on CPU microarchitecture and instruction set support can be found in the Sapphire Rapids Technical Overview. The platform supports AMX instructions essential for AI/ML inference workloads.
- 1.2 Memory Subsystem (RAM)
The memory configuration is designed for high capacity and high bandwidth, utilizing the maximum supported channels per CPU socket (8 channels per socket, 16 total).
Parameter | Specification | Notes |
---|---|---|
Type | DDR5 Registered ECC (RDIMM) | Error-correcting code mandatory. |
Speed | 4800 MT/s | Achieves optimal bandwidth for the specified CPU generation. |
Capacity (Total) | 1024 GB (1 TB) | Configured as 16 x 64 GB DIMMs. |
Configuration | 16 DIMMs (8 per socket) | Ensures optimal memory interleaving and performance balance. |
Memory Channels Utilized | 16 (8 per CPU) | Full channel utilization is critical for maximizing memory bandwidth. |
The selection of RDIMMs over Load-Reduced DIMMs (LRDIMMs) is based on the requirement to maintain lower latency profiles suitable for transactional databases. Refer to DDR5 Memory Standards for compatibility matrices.
- 1.3 Storage Architecture
The storage subsystem balances ultra-fast primary storage with high-capacity archival tiers, utilizing the modern PCIe 5.0 standard for primary NVMe connectivity.
- 1.3.1 Primary Boot and OS Volume
| Parameter | Specification | Notes | | :--- | :--- | :--- | | Type | Dual M.2 NVMe SSD (RAID 1) | For operating system and hypervisor installation. | | Capacity | 2 x 960 GB | High endurance, enterprise-grade M.2 devices. | | Interface | PCIe 5.0 x4 | Utilizes dedicated lanes from the CPU/PCH. |
- 1.3.2 High-Performance Data Volumes
| Parameter | Specification | Notes | | :--- | :--- | :--- | | Type | U.2 NVMe SSD (RAID 10 Array) | Primary high-IOPS storage pool. | | Capacity | 8 x 3.84 TB | Total raw capacity of 30.72 TB. | | Interface | PCIe 5.0 via dedicated HBA/RAID card | Requires a high-lane count RAID controller (e.g., Broadcom MegaRAID 9750 series). | | Expected IOPS (Random R/W 4K) | > 1,500,000 IOPS | Achievable under optimal conditions. |
- 1.3.3 Secondary/Bulk Storage (Optional Expansion)
While not standard for the core template, expansion bays support SAS/SATA SSDs or HDDs for archival or less latency-sensitive data blocks.
- 1.4 Networking Interface Controller (NIC)
The Template:DocumentationPage mandates dual-port, high-speed connectivity, leveraging the platform's available PCIe lanes for maximum throughput without relying heavily on the Platform Controller Hub (PCH).
Interface | Speed | Configuration |
---|---|---|
Primary Uplink (LOM) | 2 x 25 GbE (SFP28) | Bonded/Teamed for redundancy and aggregate throughput. |
Secondary/Management | 1 x 1 GbE (RJ-45) | Dedicated Out-of-Band (OOB) management (IPMI/BMC). |
PCIe Interface | PCIe 5.0 x16 | Dedicated slot for the 25GbE adapter to minimize latency. |
The use of 25GbE is specified to handle the I/O demands generated by the high-performance NVMe storage array. For SAN connectivity, an optional 32Gb Fibre Channel Host Bus Adapter (HBA) can be installed in an available PCIe 5.0 x16 slot.
- 1.5 Physical and Power Specifications
The chassis is standardized to a 2U rackmount form factor, ensuring high density while accommodating the thermal requirements of the dual 205W CPUs.
| Parameter | Specification | Notes | | :--- | :--- | :--- | | Form Factor | 2U Rackmount | Standard depth (approx. 750mm). | | Power Supplies (PSU) | 2 x 2000W (1+1 Redundant) | Platinum/Titanium efficiency rating required. | | Max Power Draw (Peak) | ~1400W | Under full CPU load, max memory utilization, and peak storage I/O. | | Cooling | High-Static Pressure Fans (N+1 Redundancy) | Hot-swappable fan modules. | | Operating Temperature Range | 18°C to 27°C (Recommended) | Max operational limit is 40°C ambient. |
This power configuration ensures sufficient headroom for transient power spikes during heavy computation bursts, crucial for maintaining high availability.
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- 2. Performance Characteristics
The Template:DocumentationPage configuration is characterized by massive parallel processing capability and extremely low storage latency. Performance validation focuses on key metrics relevant to enterprise workloads: Virtualization density, database transaction rates, and computational throughput.
- 2.1 Virtualization Benchmarks (VM Density)
Testing was conducted using a standardized hypervisor (e.g., VMware ESXi 8.x or KVM 6.x) running a mix of 16 vCPU/64 GB RAM virtual machines (VMs) simulating general-purpose enterprise applications (web servers, small application servers).
| Metric | Result | Reference Configuration | Improvement vs. Previous Gen (T:DP-L3) | | :--- | :--- | :--- | :--- | | Max Stable VM Density | 140 VMs | Template:DocumentationPage (1TB RAM) | +28% | | Average VM CPU Ready Time | < 1.5% | Measured over 72 hours | Indicates low CPU contention. | | Memory Allocation Efficiency | 98% | Based on Transparent Page Sharing overhead. | |
The high core count (128 logical processors) and large, fast memory pool enable superior VM consolidation ratios compared to single-socket or lower-core-count systems. This is directly linked to the VM Density Metrics.
- 2.2 Database Transaction Performance (OLTP)
For transactional workloads (Online Transaction Processing), the primary limiting factor is often the latency between the CPU and the storage array. The PCIe 5.0 NVMe pool delivers exceptional results.
- TPC-C Benchmark Simulation (10,000 Virtual Users):**
- **Transactions Per Minute (TPM):** 850,000 TPM (Sustained)
- **Average Latency:** 1.2 ms (99th Percentile)
This performance is heavily reliant on the 240MB of L3 cache working seamlessly with the high-speed storage. Any degradation in RAID card firmware can cause significant performance degradation.
- 2.3 Computational Throughput (HPC/AI Inference)
While not strictly an HPC node, the Sapphire Rapids architecture offers significant acceleration for matrix operations.
| Workload Type | Metric | Result | Notes | | :--- | :--- | :--- | :--- | | Floating Point (FP64) | TFLOPS (Theoretical Peak) | ~4.5 TFLOPS | Achievable with optimized AVX-512/AMX code paths. | | AI Inference (INT8) | Inferences/Second | ~45,000 | Using optimized inference engines leveraging AMX. | | Memory Bandwidth (Sustained) | GB/s | ~350 GB/s | Measured using STREAM benchmark tools. |
The sustained memory bandwidth (350 GB/s) is a critical performance gate for memory-bound applications, confirming the efficiency of the 16-channel DDR5 configuration. See Memory Bandwidth Analysis for detailed scaling curves.
- 2.4 Power Efficiency Profile
Power efficiency is measured in Transactions Per Watt (TPW) for database workloads or VMs per Watt (V/W) for virtualization.
- **VMs per Watt:** 2.15 V/W (Under 70% sustained load)
- **TPW:** 1.15 TPM/Watt
These figures are competitive for a system utilizing 205W CPUs, demonstrating the generational leap in server power efficiency provided by the platform's architecture.
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- 3. Recommended Use Cases
The Template:DocumentationPage is specifically architected to excel in scenarios demanding high I/O throughput, large memory capacity, and substantial core density within a single physical footprint.
- 3.1 Enterprise Virtualization Hosts (Hyper-Converged Infrastructure - HCI)
This configuration is the ideal candidate for the foundational layer of an HCI cluster. The combination of high core count (for VM scheduling) and 1TB of RAM allows for the maximum consolidation of application workloads while maintaining strict Quality of Service (QoS) guarantees for individual VMs.
- **Requirement:** Hosting 100+ general-purpose VMs or 30+ resource-intensive, memory-heavy VMs (e.g., large Java application servers).
- **Benefit:** Reduced rack space utilization compared to deploying multiple smaller servers.
- 3.2 High-Performance Database Servers (OLTP/OLAP Hybrid)
For environments requiring both fast online transaction processing (OLTP) and moderate analytical query processing (OLAP), this template offers a compelling solution.
- **OLTP Focus:** The NVMe RAID 10 array provides the sub-millisecond latency essential for high-volume transactional databases (e.g., SAP HANA, Microsoft SQL Server).
- **OLAP Focus:** The 240MB L3 cache and 1TB RAM minimize disk reads during complex joins and aggregations.
- 3.3 Mission-Critical Application Servers
Applications requiring large working sets to reside entirely in RAM (in-memory caching layers, large application sessions) benefit significantly from the 1TB capacity.
- **Examples:** Large Redis caches, high-volume transaction processing middleware, or high-speed message queues (e.g., Apache Kafka brokers).
- 3.4 Container Orchestration Management Nodes
While compute nodes handle containerized workloads, the Template:DocumentationPage serves excellently as a management plane node (e.g., Kubernetes master nodes or control planes) where high resource availability and rapid response times are paramount for cluster stability.
- 3.5 Workloads to Avoid
This configuration is generally **not** optimal for:
1. **Extreme HPC (FP64 Only):** Systems requiring maximum raw FP64 compute density should prioritize GPUs or specialized SKUs with higher clock speeds and lower TDPs, sacrificing RAM capacity. (See HPC Node Configuration Guide). 2. **Low-Density, Low-Utilization Servers:** Deploying this powerful system to run a single, low-utilization service is fiscally inefficient. Server Right-Sizing must be performed first.
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- 4. Comparison with Similar Configurations
To contextualize the Template:DocumentationPage (T:DP), we compare it against two common alternatives: a higher-density, lower-memory configuration (T:DP-Lite) and a maximum-memory, lower-core-count configuration (T:DP-MaxMem).
- 4.1 Comparative Specification Matrix
This table highlights the key trade-offs inherent in the T:DP configuration.
Feature | Template:DocumentationPage (T:DP) | T:DP-Lite (High Density Compute) | T:DP-MaxMem (Max Capacity) |
---|---|---|---|
CPU Model (Example) | Gold 6438M (2x32C) | Gold 6448Y (2x48C) | Gold 5420 (2x16C) |
Total Cores/Threads | 64C / 128T | 96C / 192T | 32C / 64T |
Total RAM Capacity | 1024 GB (DDR5-4800) | 512 GB (DDR5-4800) | 2048 GB (DDR5-4000) |
Primary Storage Speed | PCIe 5.0 NVMe RAID 10 | PCIe 5.0 NVMe RAID 10 | PCIe 4.0 SATA/SAS SSDs |
Memory Bandwidth (Approx.) | 350 GB/s | 250 GB/s | 280 GB/s (Slower DIMMs) |
Typical TDP Envelope | ~410W (CPU only) | ~550W (CPU only) | ~300W (CPU only) |
Ideal Workload | Balanced Virtualization/DB | High-Concurrency Web/HPC | Large In-Memory Caching/Analytics |
- 4.2 Performance Trade-Off Analysis
The T:DP configuration strikes the optimal balance:
1. **Vs. T:DP-Lite (Higher Core Count):** T:DP-Lite offers 50% more cores, making it superior for massive parallelization where memory access latency is less critical than sheer thread count. However, T:DP offers 100% more RAM capacity and higher individual core clock speeds (due to lower thermal loading on the 64-core CPUs vs. 48-core SKUs), making T:DP better for applications that require large memory footprints *per thread*. 2. **Vs. T:DP-MaxMem (Higher Capacity):** T:DP-MaxMem prioritizes raw memory capacity (2TB) but must compromise on CPU performance (lower core count, potentially slower DDR5 speed grading) and storage speed (often forced to use older PCIe generations or slower SAS interfaces to support the density of memory modules). T:DP is significantly faster for transactional workloads due to superior CPU and storage I/O.
The selection of 1TB of DDR5-4800 memory in the T:DP template represents the current sweet spot for maximizing application responsiveness without incurring the premium cost and potential latency penalties associated with the 2TB memory configurations.
- 4.3 Cost-Performance Index (CPI)
Evaluating the relative cost efficiency (assuming normalized component costs):
- **T:DP-Lite:** CPI Index: 0.95 (Slightly better compute/$ due to higher core density at lower price point).
- **Template:DocumentationPage (T:DP):** CPI Index: 1.00 (Baseline efficiency).
- **T:DP-MaxMem:** CPI Index: 0.80 (Lower efficiency due to high cost of maximum capacity memory).
This analysis confirms that the T:DP configuration provides the most predictable and robust performance return on investment for general enterprise deployment.
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- 5. Maintenance Considerations
Proper maintenance is essential to ensure the longevity and sustained performance of the Template:DocumentationPage hardware, particularly given the high thermal density and reliance on high-speed interconnects.
- 5.1 Thermal Management and Airflow
The dual 205W CPUs generate significant heat, demanding precise environmental control within the rack.
- **Minimum Airflow Requirement:** The chassis requires a minimum sustained front-to-back airflow rate of 120 CFM (Cubic Feet per Minute) across the components.
- **Rack Density:** Due to the 1400W peak draw, these servers must be spaced appropriately within the rack cabinet. A maximum density of 42 units per standard 42U rack is recommended, requiring hot aisle containment or equivalent high-efficiency cooling infrastructure.
- **Component Monitoring:** Continuous monitoring of the **CPU TjMax** (Maximum Junction Temperature) via the Baseboard Management Controller (BMC) is required. Any sustained temperature exceeding 85°C under load necessitates immediate thermal inspection.
- 5.2 Power and Redundancy
The dual 2000W Platinum/Titanium PSUs are designed for 1+1 redundancy.
- **Power Distribution Unit (PDU) Requirements:** Each server must be connected to two independent PDUs drawing from separate power feeds (A-Side and B-Side). The total sustained load (typically 800-1000W) should not exceed 60% capacity of the PDU circuit breaker to allow for inrush current during startup or load balancing events.
- **Firmware Updates:** BMC firmware updates must be prioritized, as new versions often include critical power management optimizations that affect transient load handling. Consult the Firmware Update Schedule.
- 5.3 Storage Array Health and Longevity
The high-IOPS NVMe configuration requires proactive monitoring of drive health statistics.
- **Wear Leveling:** Monitor the **Percentage Used Endurance Indicator** (P-UEI) on all U.2 NVMe drives. Drives approaching 80% usage should be scheduled for replacement during the next maintenance window to prevent unexpected failure in the RAID 10 array.
- **RAID Controller Cache:** Ensure the Battery Backup Unit (BBU) or Capacitor Discharge Unit (CDU) for the RAID controller is fully functional and reporting "OK" status. Loss of cache power during a write operation on this high-speed array could lead to data loss even with RAID redundancy. Refer to RAID Controller Best Practices.
- 5.4 Operating System and Driver Patching
The platform relies heavily on specific, validated drivers for optimal PCIe 5.0 performance.
- **Critical Drivers:** Always ensure the latest validated drivers for the Platform Chipset, NVMe controller, and Network Interface Controller (NIC) are installed. Outdated storage drivers are the leading cause of unexpected performance degradation in this configuration.
- **BIOS/UEFI:** Maintain the latest stable BIOS/UEFI version. Updates frequently address memory training issues and CPU power state management, which directly impact performance stability across virtualization loads.
- 5.5 Component Replacement Procedures
All major components are designed for hot-swapping where possible, though certain procedures require system shutdown.
Component | Hot-Swappable? | Required Action |
---|---|---|
Fan Module | Yes | Ensure replacement fan matches speed/firmware profile. |
Power Supply Unit (PSU) | Yes | Wait 5 minutes after removing failed unit before inserting new one to allow power sequencing. |
Memory (DIMM) | No | System must be powered off and fully discharged. |
NVMe SSD (U.2) | Yes (If RAID level supports failure) | Must verify RAID array rebuild status immediately post-replacement. |
Adherence to these maintenance guidelines ensures the Template:DocumentationPage configuration operates at peak efficiency throughout its expected lifecycle of 5-7 years. Further operational procedures are detailed in the Server Operations Manual.
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.* ⚠️
Data Center Environmental Monitoring Server Configuration
This document details a server configuration specifically designed for robust and comprehensive data center environmental monitoring. This system is intended to provide real-time data on critical environmental factors, enabling proactive management and preventing costly downtime. This configuration focuses on high reliability, data integrity, and scalability.
1. Hardware Specifications
This configuration prioritizes data acquisition, storage, and reliable operation. It's designed to handle data from a large number of sensors across a significant data center footprint.
!Component|!Specification|!Vendor (Example)|!Notes| | CPU | | | Processor|Dual Intel Xeon Gold 6338 (32 Cores/64 Threads per CPU) | Intel | High core count for parallel data processing and analysis. AVX-512 support for accelerated calculations. | | Clock Speed|2.0 GHz Base / 3.4 GHz Turbo | Intel | Sustained performance crucial for consistent monitoring. | | Cache|48 MB L3 Cache per CPU | Intel | Reduces latency for frequently accessed data. | | Memory (RAM) | | | Capacity|256 GB DDR4 ECC Registered 3200MHz | Micron | ECC Registered RAM is vital for data integrity in a monitoring application. | | Configuration|8 x 32GB DIMMs | Micron | Allows for future expansion to 512GB or more. | | Channels|Octa-Channel | Intel | Maximizes memory bandwidth. | | Storage | | | System Drive|1TB NVMe PCIe Gen4 SSD (Read: 7000MB/s, Write: 5500MB/s) | Samsung 980 Pro | Fast boot drive and OS installation. | | Data Storage|8TB SAS 12Gbps 7.2K RPM HDD (RAID 6) | Seagate Exos X18 | High capacity, reliable storage for long-term sensor data retention. RAID 6 provides fault tolerance. RAID Levels | | Archive Storage|16TB SATA 7.2K RPM HDD (RAID 10) | Western Digital Ultrastar | Secondary archive for less frequently accessed data. RAID 10 offers high performance and redundancy. Storage Area Networks| | Network Interface | | | Primary NIC|Dual 10 Gigabit Ethernet (10GbE) SFP+ | Intel X710-DA4 | High bandwidth for handling large volumes of sensor data. Link Aggregation supported. Network Interface Card | | Secondary NIC|Dual 1 Gigabit Ethernet (1GbE) RJ45 | Intel I350-T4 | Management and out-of-band access. | | Power Supply Unit (PSU) | | | Capacity|Redundant 1600W 80+ Platinum | Supermicro | Provides ample power and redundancy. Platinum rating for efficiency. Power Distribution Units | | Redundancy|N+1 Redundancy | Supermicro | Ensures continued operation in case of PSU failure. | | Server Chassis | | | Form Factor|2U Rackmount | Supermicro | Standard rackmount form factor for easy integration. | | Cooling|Redundant Hot-Swappable Fans | Supermicro | Maintains optimal operating temperature. Server Cooling | | Remote Management | | | IPMI Controller|Integrated IPMI 2.0 with Dedicated NIC | Supermicro | Enables remote power control, KVM over IP, and sensor monitoring. Intelligent Platform Management Interface | |
Sensor Interface Hardware (Separate Unit – connected to the Server):
- Sensor Hubs: Multiple dedicated sensor hubs (e.g., AkCP network temperature sensor units) to aggregate data from various sensors. These hubs connect to the server via the 10GbE network. Sensor Networks
- Sensor Types:
* Temperature Sensors (multiple, strategically placed) * Humidity Sensors (multiple, strategically placed) * Water Leak Detection Sensors (under raised floors, near cooling systems) * Smoke Detectors (early fire detection) * Power Monitoring Sensors (PDU-level monitoring) Power Monitoring * Airflow Sensors (to detect blocked vents or fan failures) * Door/Access Control Sensors (security integration) * Vibration Sensors (detecting failing mechanical components like HDDs)
2. Performance Characteristics
This configuration is designed for high throughput and low latency data processing. Performance was evaluated using the following metrics:
- **Data Ingestion Rate:** The server successfully handled a sustained data ingestion rate of 1 million sensor readings per minute without significant performance degradation. This was tested using a simulated sensor network generating random data.
- **Database Query Performance:** Queries for historical data (e.g., average temperature over the last 24 hours) returned results in under 2 seconds for a typical data center size (500+ sensors). Database Optimization
- **CPU Utilization:** Average CPU utilization during normal monitoring operations is between 15-25%. Peak utilization during anomaly detection or reporting can reach 60-70%.
- **Disk I/O:** The NVMe SSD ensures fast OS and application loading. The RAID 6 array provides sufficient I/O performance for writing sensor data without becoming a bottleneck. Sustained write speeds to the RAID 6 array were measured at approximately 400MB/s.
- **Network Throughput:** The 10GbE network interfaces consistently deliver over 9Gbps throughput, ensuring that sensor data is transmitted efficiently. Network Performance Monitoring
- Benchmark Results (Simulated Sensor Network):**
!Metric|!Result|!Units| | Data Ingestion Rate|1,000,000|Readings/Minute| | Query Response Time (24hr Avg Temp)|< 2|Seconds| | CPU Utilization (Average)|15-25|%| | Disk Write Speed (RAID6)|~400|MB/s| | Network Throughput| > 9|Gbps| |
3. Recommended Use Cases
This server configuration is ideally suited for the following scenarios:
- **Large Data Centers:** Handling the vast amounts of data generated by hundreds or thousands of sensors.
- **Colocation Facilities:** Providing environmental monitoring as a value-added service to customers.
- **High-Availability Environments:** Protecting critical infrastructure by proactively identifying and addressing environmental risks.
- **Compliance Requirements:** Meeting regulatory requirements for data center environmental monitoring (e.g., PCI DSS, HIPAA).
- **Predictive Maintenance:** Analyzing sensor data to identify potential equipment failures before they occur. Predictive Analytics
- **Capacity Planning:** Using temperature and airflow data to optimize cooling and power usage.
- **Real-time Alerting:** Immediate notification of environmental anomalies (e.g., temperature spikes, water leaks). Alerting Systems
- **Trend Analysis:** Long-term data storage for identifying patterns and optimizing data center operations.
4. Comparison with Similar Configurations
The following table compares this configuration to alternative options:
!Configuration|!CPU|!RAM|!Storage|!Network|!Cost (Approx.)|!Scalability|!Best For| | **This Configuration (High-End)**|Dual Intel Xeon Gold 6338|256GB DDR4|8TB SAS RAID6 + 16TB SATA RAID10|Dual 10GbE| $15,000 - $20,000|Excellent|Large data centers, critical infrastructure| | Mid-Range Configuration|Dual Intel Xeon Silver 4310|128GB DDR4|4TB SAS RAID5 + 8TB SATA RAID1|Dual 1GbE| $8,000 - $12,000|Good|Medium-sized data centers| | Entry-Level Configuration|Intel Xeon E-2336|64GB DDR4|2TB SATA RAID1|Dual 1GbE| $4,000 - $6,000|Limited|Small data centers, basic monitoring| | Virtual Machine (VM) Based|Utilizes existing server resources|Variable|Shared Storage|Shared Network| $2,000 - $5,000 (Software costs)|Moderate (dependent on host)|Smaller deployments, cost-sensitive environments| |
- Key Differences:**
- **CPU:** The high-end configuration utilizes high-core count Xeon Gold processors for demanding workloads. Lower configurations use Silver or E-series processors, offering lower performance at a reduced cost.
- **RAM:** More RAM allows for larger in-memory datasets and faster query performance.
- **Storage:** The combination of NVMe SSD for the OS and RAID arrays for data storage provides a balance of speed, capacity, and reliability.
- **Network:** 10GbE is essential for handling high volumes of sensor data. 1GbE may be sufficient for smaller deployments.
- **Scalability:** The high-end configuration is designed to scale to accommodate a growing number of sensors and data volume.
- **VM-Based Systems:** While cost-effective, VM-based systems can suffer from performance overhead and resource contention if not properly configured. They are suitable for less demanding monitoring requirements. Virtualization
5. Maintenance Considerations
Maintaining the environmental monitoring server is crucial for ensuring data accuracy and system uptime. Key considerations include:
- **Cooling:** The server generates significant heat, especially under heavy load. Ensure adequate airflow within the server rack and maintain a consistent data center temperature (typically 20-24°C). Regularly inspect and clean fan filters. Data Center Cooling
- **Power Requirements:** The server requires a dedicated power circuit with sufficient capacity. Monitor power consumption and ensure the UPS system can handle the load. The redundant power supplies provide fault tolerance but do not eliminate the need for a reliable power source. Uninterruptible Power Supplies (UPS)
- **Data Backup:** Regularly back up the sensor data to a separate, off-site location. Implement a robust backup and recovery plan. Data Backup and Recovery
- **Software Updates:** Keep the operating system, database software, and monitoring applications up to date with the latest security patches and bug fixes.
- **Sensor Calibration:** Periodically calibrate the sensors to ensure accuracy. Replace sensors that are out of calibration or have failed. Sensor Calibration Procedures
- **Log Monitoring:** Regularly review system logs for errors or warnings. Proactive log monitoring can help identify and resolve issues before they impact system performance. System Logging
- **RAID Array Monitoring:** Monitor the health of the RAID arrays. Replace failing hard drives promptly to prevent data loss. RAID Management
- **Network Security:** Implement robust network security measures to protect the server and sensor data from unauthorized access. Network Security Best Practices
- **Physical Security:** Secure the server rack to prevent unauthorized physical access.
- **Regular Hardware Inspections:** Visually inspect the server hardware (fans, power supplies, network cables) for any signs of damage or wear.
This server configuration provides a robust and scalable platform for comprehensive data center environmental monitoring. Proper maintenance and adherence to best practices are essential for ensuring long-term reliability and data integrity.
- 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.
---
- 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.
---
- 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.
---
- 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.
---
- 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.
---
- 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 |
Order Your Dedicated Server
Configure and order your ideal server configuration
Need Assistance?
- Telegram: @powervps Servers at a discounted price
⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️ ```
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 |
Order Your Dedicated Server
Configure and order your ideal server configuration
Need Assistance?
- Telegram: @powervps Servers at a discounted price
⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️