Computational Resources
- Server Configuration Documentation: Template:DocumentationHeader
This document provides a comprehensive technical specification and operational guide for the server configuration designated internally as **Template:DocumentationHeader**. This baseline configuration is designed to serve as a standardized, high-throughput platform for virtualization and container orchestration workloads across our data center infrastructure.
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- 1. Hardware Specifications
The **Template:DocumentationHeader** configuration represents a dual-socket, 2U rack-mount server derived from the latest generation of enterprise hardware. Strict adherence to component selection ensures optimal compatibility, thermal stability, and validated performance metrics.
- 1.1. Base Platform and Chassis
The foundational element is a validated 2U chassis supporting high-density component integration.
Component | Specification |
---|---|
Chassis Model | Vendor XYZ R4800 Series (2U) |
Motherboard | Dual Socket LGA-5124 (Proprietary Vendor XYZ Board) |
Power Supplies (PSU) | 2x 1600W 80 PLUS Platinum, Hot-Swappable, Redundant (1+1) |
Management Controller | Integrated Baseboard Management Controller (BMC) v4.1 (IPMI 2.0 Compliant) |
Networking (Onboard LOM) | 2x 10GbE Base-T (Broadcom BCM57416) |
Expansion Slots | 4x PCIe Gen 5 x16 Full Height, Half Length (FHFL) |
For deeper understanding of the chassis design principles, refer to Chassis Design Principles.
- 1.2. Central Processing Units (CPUs)
This configuration mandates the use of dual-socket CPUs from the latest generation, balancing core density with high single-thread performance.
Parameter | Specification (Per Socket) |
---|---|
Processor Family | Intel Xeon Scalable Processor (Sapphire Rapids Equivalent) |
Model Number | 2x Intel Xeon Gold 6548Y (or equivalent tier) |
Core Count | 32 Cores / 64 Threads (Total 64 Cores / 128 Threads) |
Base Clock Frequency | 2.5 GHz |
Max Turbo Frequency | Up to 4.1 GHz (Single Core) |
L3 Cache Size | 60 MB (Total 120 MB Shared) |
TDP (Thermal Design Power) | 250W per CPU |
Memory Channels Supported | 8 Channels DDR5 |
The choice of the 'Y' series designation prioritizes memory bandwidth and I/O capabilities critical for virtualization density, as detailed in CPU Memory Channel Architecture.
- 1.3. System Memory (RAM)
Memory capacity and speed are critical for maximizing VM density. This configuration utilizes high-speed DDR5 ECC Registered DIMMs (RDIMMs).
Parameter | Specification |
---|---|
Total Capacity | 1.5 TB (Terabytes) |
Module Type | DDR5 ECC RDIMM |
Module Density | 12x 128 GB DIMMs |
Configuration | Fully Populated (12 DIMMs per CPU, 24 Total) – Optimal for 8-channel interleaving |
Memory Speed | 4800 MT/s (JEDEC Standard) |
Error Correction | ECC (Error-Correcting Code) |
Note on population: To maintain optimal performance across the dual-socket topology and ensure maximum memory bandwidth utilization, the population must strictly adhere to the Dual Socket Memory Population Guidelines.
- 1.4. Storage Subsystem
The storage configuration is optimized for high Input/Output Operations Per Second (IOPS) suitable for active operating systems and high-transaction databases. It employs a combination of NVMe SSDs for primary storage and a high-speed RAID controller for redundancy and management.
- 1.4.1. Boot and System Drive
A small, dedicated RAID array for the hypervisor OS.
Component | Specification |
---|---|
Drives | 2x 480 GB SATA M.2 SSDs (Enterprise Grade) |
RAID Level | RAID 1 (Mirroring) |
Controller | Onboard SATA Controller (Managed via BMC) |
- 1.4.2. Primary Data Storage
The main storage pool relies exclusively on high-performance NVMe drives connected via PCIe Gen 5.
Component | Specification |
---|---|
Drive Type | NVMe PCIe Gen 4/5 U.2 SSDs |
Total Drives | 8x 3.84 TB Drives |
RAID Controller | Dedicated Hardware RAID Card (e.g., Broadcom MegaRAID 9750-8i Gen 5) |
RAID Level | RAID 10 (Striped Mirrors) |
Usable Capacity (Approx.) | 12.28 TB (Raw 30.72 TB) |
Interface | PCIe Gen 5 x8 (via dedicated backplane) |
The use of a dedicated hardware RAID controller is mandatory to offload parity calculations from the main CPUs, adhering to RAID Controller Offloading Standards. Further details on NVMe drive selection can be found in NVMe Drive Qualification List.
- 1.5. Networking Interface Cards (NICs)
While the LOM provides 10GbE connectivity for management, high-throughput data plane operations require dedicated expansion cards.
Slot | Adapter Type | Quantity | Configuration |
---|---|---|---|
PCIe Slot 1 | 100GbE Mellanox ConnectX-7 (2x QSFP56) | 1 | Dedicated Storage/Infiniband Fabric (If applicable) |
PCIe Slot 2 | 25GbE SFP+ Adapter (Intel E810 Series) | 1 | Primary Data Plane Uplink |
PCIe Slot 3 | Unpopulated (Reserved for future expansion) | 0 | N/A |
The 100GbE card is typically configured for RoCEv2 (RDMA over Converged Ethernet) when deployed in High-Performance Computing (HPC) clusters, referencing RDMA Implementation Guide.
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- 2. Performance Characteristics
The **Template:DocumentationHeader** configuration is tuned for balanced throughput and low latency, particularly in I/O-bound virtualization scenarios. Performance validation is conducted using industry-standard synthetic benchmarks and application-specific workload simulations.
- 2.1. Synthetic Benchmark Results
The following results represent average performance measured under controlled, standardized ambient conditions ($22^{\circ}C$, 40% humidity) using the specified hardware components.
- 2.1.1. CPU Benchmarks (SPECrate 2017 Integer)
SPECrate measures sustained throughput across multiple concurrent threads, relevant for virtual machine density.
Metric | Result (Average) | Unit |
---|---|---|
SPECrate_int_base | 580 | Score |
SPECrate_int_peak | 615 | Score |
Notes | Results achieved with all 128 threads active, optimized compiler flags (-O3, AVX-512 enabled). |
These figures confirm the strong multi-threaded capacity of the 64-core platform. For single-threaded performance metrics, refer to Single Thread Performance Analysis.
- 2.1.2. Memory Bandwidth Testing (AIDA64 Read/Write)
Measuring the aggregate memory bandwidth across the dual-socket configuration.
Operation | Measured Throughput | Unit |
---|---|---|
Memory Read Speed (Aggregate) | 320 | GB/s |
Memory Write Speed (Aggregate) | 285 | GB/s |
Latency (First Access) | 58 | Nanoseconds (ns) |
The latency figures are slightly elevated compared to single-socket configurations due to necessary NUMA node communication overhead, discussed in NUMA Node Interconnect Latency.
- 2.2. Storage Performance (IOPS and Throughput)
Storage performance is the primary differentiator for this configuration, leveraging PCIe Gen 5 NVMe drives in a RAID 10 topology.
- 2.2.1. FIO Benchmarks (Random I/O)
Testing small, random I/O patterns (4K block size), critical for VM boot storms and transactional databases.
Queue Depth (QD) | IOPS (Read) | IOPS (Write) |
---|---|---|
QD=32 (Per Drive Emulation) | 280,000 | 255,000 |
QD=256 (Aggregate Array) | > 1,800,000 | > 1,650,000 |
Sustained performance at higher queue depths demonstrates the efficiency of the dedicated RAID controller and the NVMe controllers in handling parallel requests.
- 2.2.2. Sequential Throughput
Testing large sequential transfers (128K block size), relevant for backups and large file processing.
Operation | Measured Throughput | Unit |
---|---|---|
Sequential Read (Max) | 18.5 | GB/s |
Sequential Write (Max) | 16.2 | GB/s |
These throughput figures are constrained by the PCIe Gen 5 x8 link to the RAID controller and the internal signaling limits of the NVMe drives themselves. See PCIe Gen 5 Bandwidth Limitations for detailed analysis.
- 2.3. Real-World Workload Simulation
Performance validation involves simulating container density and general-purpose virtualization loads using established internal testing suites.
- Scenario: Virtual Desktop Infrastructure (VDI) Density**
Running 300 concurrent light-use VDI sessions (Windows 10/Office Suite).
- Observed CPU Utilization: 75% sustained.
- Observed Memory Utilization: 95% (1.42 TB used).
- Result: Stable performance with <150ms average desktop latency.
- Scenario: Kubernetes Node Density**
Deploying standard microservices containers (average 1.5 vCPU, 4GB RAM per pod).
- Maximum Stable Pod Count: 180 pods.
- Failure Point: Exceeded IOPS limits when storage utilization surpassed 85% saturation, leading to increased container startup times.
This analysis confirms that storage I/O is the primary bottleneck when pushing density limits beyond the specified baseline. For I/O-intensive applications, consider the configuration variant detailed in Template:DocumentationHeader_HighIO.
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- 3. Recommended Use Cases
The **Template:DocumentationHeader** configuration is specifically engineered for environments demanding a high balance between computational density, substantial memory allocation, and high-speed local storage access.
- 3.1. Virtualization Hosts (Hypervisors)
This is the primary intended role. The combination of 64 physical cores and 1.5 TB of RAM provides excellent VM consolidation ratios.
- **Enterprise Virtual Machines (VMs):** Hosting critical Windows Server or RHEL instances requiring dedicated CPU cores and large memory footprints (e.g., Domain Controllers, Application Servers).
- **High-Density KVM/VMware Deployments:** Ideal for running a large number of small to medium-sized virtual machines where maximizing the core-to-VM ratio is paramount.
- 3.2. Container Orchestration Platforms (Kubernetes/OpenShift)
The platform excels as a worker node in large-scale container environments.
- **Stateful Workloads:** The fast NVMe RAID 10 array is perfectly suited for persistent volumes (PVs) used by databases (e.g., PostgreSQL, MongoDB) running within containers, providing low-latency disk access that traditional SAN/NAS connections might struggle to match.
- **CI/CD Runners:** Excellent capacity for parallelizing build and test jobs due to high core count and fast local scratch space.
- 3.3. Data Processing and Analytics (Mid-Tier)
While not a dedicated HPC node, this server handles substantial in-memory processing tasks.
- **In-Memory Caching Layers (e.g., Redis, Memcached):** The 1.5 TB of RAM allows for massive, high-performance caching layers.
- **Small to Medium Apache Spark Clusters:** Suitable for running Spark Executors that benefit from both high core counts and fast access to intermediate shuffle data stored on the local NVMe drives.
- 3.4. Database Servers (OLTP Focus)
For Online Transaction Processing (OLTP) databases where latency is critical, this configuration is highly effective.
- The high IOPS capacity (1.8M Read IOPS) directly translates to improved transactional throughput for systems like SQL Server or Oracle RDBMS.
Configurations requiring extremely high sequential throughput (e.g., large-scale media transcoding) or extreme single-thread frequency should look towards configurations detailed in High Frequency Server SKUs.
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- 4. Comparison with Similar Configurations
To contextualize the **Template:DocumentationHeader**, it is essential to compare it against two common alternatives: a memory-optimized configuration and a storage-dense configuration.
- 4.1. Configuration Variants Overview
| Configuration Variant | Primary Focus | CPU Cores (Total) | RAM (Total) | Primary Storage Type | | :--- | :--- | :--- | :--- | :--- | | **Template:DocumentationHeader (Baseline)** | Balanced I/O & Compute | 64 | 1.5 TB | 8x NVMe (RAID 10) | | Variant A: Memory Optimized | Max VM Density | 64 | 3.0 TB | 4x SATA SSD (RAID 1) | | Variant B: Storage Dense | Maximum Raw Capacity | 48 | 768 GB | 24x 10TB SAS HDD (RAID 6) |
- 4.2. Performance Comparison Matrix
This table illustrates the trade-offs when selecting a variant over the baseline.
Metric | Baseline (Header) | Variant A (Memory Optimized) | Variant B (Storage Dense) |
---|---|---|---|
Max VM Count (Estimated) | High | Very High (Requires more RAM per VM) | Medium (CPU constrained) |
4K Random Read IOPS | **> 1.8 Million** | ~400,000 | ~50,000 (HDD bottleneck) |
Memory Bandwidth (GB/s) | 320 | 400 (Higher DIMM count) | 240 (Slower DIMMs) |
Single-Thread Performance | High | High | Medium (Lower TDP CPUs) |
Raw Storage Capacity | 12.3 TB (Usable) | ~16 TB (Usable, Slower) | **> 170 TB (Usable)** |
- Analysis:**
1. **Variant A (Memory Optimized):** Provides double the RAM but sacrifices 66% of the high-speed NVMe IOPS capacity. It is ideal for applications that fit entirely in memory but do not require high disk transaction rates (e.g., Java application servers, large caches). See Memory Density Server Profiles. 2. **Variant B (Storage Dense):** Offers massive capacity but suffers significantly in performance due to the reliance on slower HDDs and a lower core count CPU. This is suitable only for archival, large-scale cold storage, or backup targets.
The **Template:DocumentationHeader** configuration remains the superior choice for transactional workloads where I/O latency directly impacts user experience.
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- 5. Maintenance Considerations
Proper maintenance protocols are essential to ensure the longevity and sustained performance of the **Template:DocumentationHeader** deployment. Due to the high-power density of the dual 250W CPUs and the NVMe subsystem, thermal management and power redundancy are critical focus areas.
- 5.1. Power Requirements and Redundancy
The system is designed for resilience, utilizing dual hot-swappable Platinum-rated PSUs.
- **Peak Power Draw:** Under full load (CPU stress testing + 100% NVMe utilization), the system can draw up to 1350W.
- **Recommended Breaker Circuit:** Must be provisioned on a 20A circuit (or equivalent regional standard) for the rack PDU to ensure headroom for power supply inefficiencies and inrush current during boot cycles.
- **Redundancy:** Operation must always be maintained with both PSUs installed (N+1 redundancy). Failure of one PSU should trigger immediate alerts via the BMC, as detailed in BMC Alerting Configuration.
- 5.2. Thermal Management and Cooling
The 2U chassis relies heavily on optimized airflow management.
- **Airflow Direction:** Standard front-to-back cooling path. Ensure adequate clearance (minimum 30 inches) behind the rack for hot aisle exhaust.
- **Ambient Temperature:** Maximum sustained ambient intake temperature must not exceed $27^{\circ}C$ ($80.6^{\circ}F$). Exceeding this threshold forces the BMC to throttle CPU clock speeds to maintain thermal limits, resulting in performance degradation (see Section 2).
- **Fan Configuration:** The system uses high-static pressure fans. Noise levels are high; deployment in acoustically sensitive areas is discouraged. Refer to Data Center Thermal Standards for acceptable operating ranges.
- 5.3. Component Replacement Procedures
Due to the high component count (24 DIMMs), careful procedure is required for upgrades or replacements.
- 5.3.1. Storage Replacement (NVMe)
If an NVMe drive fails in the RAID 10 array: 1. Identify the failed drive via the RAID controller GUI or BMC interface. 2. Ensure the system is operating in a degraded state but still accessible. 3. Hot-swap the failed drive with an identical replacement part (same capacity, same vendor generation if possible). 4. Monitor the rebuild process. Full rebuild time for a 3.84 TB drive in RAID 10 can range from 8 to 14 hours, depending on ambient temperature and system load. Do not introduce high I/O workloads during the rebuild phase if possible.
- 5.3.2. Memory Upgrades
Memory upgrades require a full system shutdown. 1. Power down the system gracefully. 2. Disconnect power cords. 3. Grounding procedures (anti-static wrist strap) are mandatory. 4. When adding or replacing DIMMs, always populate slots strictly following the Dual Socket Memory Population Guidelines to maintain optimal interleaving and avoid triggering memory training errors during POST.
- 5.4. Firmware and Driver Lifecycle Management
Maintaining the firmware stack is crucial for stability, especially with PCIe Gen 5 components.
- **BIOS/UEFI:** Must be kept within one major revision of the vendor's latest release. Critical firmware updates often address memory training instability or NVMe controller compatibility issues.
- **RAID Controller Firmware:** Must be synchronized with the operating system's driver version to prevent data corruption or performance regressions. Check the Storage Controller Compatibility Matrix quarterly.
- **BMC Firmware:** Regular updates are required to patch security vulnerabilities and improve remote management features.
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- 6. Advanced Configuration Notes
- 6.1. NUMA Topology Management
With 64 physical cores distributed across two sockets, the system operates under a Non-Uniform Memory Access (NUMA) architecture.
- **Policy Recommendation:** For most virtualization and database workloads, the host operating system (Hypervisor) should enforce **Prefer NUMA Local Access**. This ensures that a VM or container process primarily accesses memory physically attached to the CPU socket it is scheduled on, minimizing inter-socket latency across the UPI (Ultra Path Interconnect).
- **NUMA Spanning:** Workloads that require very large contiguous memory blocks exceeding 768 GB (half the total RAM) will inevitably span NUMA nodes. Performance impact is acceptable for non-time-critical tasks but should be avoided for sub-millisecond latency requirements.
- 6.2. Security Hardening
The platform supports hardware-assisted security features that should be enabled.
- **Trusted Platform Module (TPM) 2.0:** Must be enabled and provisioned for secure boot processes and disk encryption key storage.
- **Hardware Root of Trust:** Verify the integrity chain from the BMC firmware up through the BIOS during every boot sequence. Documentation on validating this chain is available in Hardware Root of Trust Validation.
- 6.3. Network Offloading Features
To maximize CPU availability, NICS should have offloading features enabled where supported by the workload.
- **Receive Side Scaling (RSS):** Mandatory for all 25GbE interfaces to distribute network processing load across multiple CPU cores.
- **TCP Segmentation Offload (TSO) / Large Send Offload (LSO):** Should be enabled for high-throughput transfers to minimize CPU cycles spent preparing network packets.
The selection of the appropriate NIC drivers, especially for the high-speed 100GbE adapter, is critical. Generic OS drivers are insufficient; vendor-specific, certified drivers must be used, as outlined in Network Driver Certification Policy.
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- Conclusion
The **Template:DocumentationHeader** server configuration provides a robust, high-performance foundation for modern data center operations, striking an excellent balance between processing power, memory capacity, and low-latency storage access. Adherence to the specified hardware tiers and maintenance procedures outlined in this documentation is mandatory to ensure operational stability and performance consistency.
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.* ⚠️
Computational Resources
This document details a high-performance server configuration optimized for computationally intensive tasks. This configuration, designated "CR-7000", is designed to provide significant processing power, large memory capacity, and fast storage access. It targets workloads such as scientific simulations, machine learning, data analytics, and high-frequency trading. This documentation provides detailed specifications, performance characteristics, recommended use cases, comparisons, and maintenance guidelines.
1. Hardware Specifications
The CR-7000 configuration utilizes a dual-socket server platform with cutting-edge components. All components are enterprise-grade and selected for reliability and performance. A detailed breakdown is provided below.
Component | Specification | Details |
---|---|---|
CPU | Dual Intel Xeon Platinum 8480+ | 56 Cores / 112 Threads per CPU, 2.0 GHz Base Frequency, 3.8 GHz Max Turbo Frequency, 96MB L3 Cache, TDP 350W. Supports Advanced Vector Extensions 512 (AVX-512). |
Motherboard | Supermicro X13DEI-N | Dual Socket LGA 4677, Supports DDR5 ECC Registered Memory, 8 x PCIe 5.0 x16 slots, 2 x 10GbE LAN ports, IPMI 2.0 remote management. See Server Motherboard Architecture for detailed information. |
RAM | 2TB DDR5 ECC Registered RAM | 16 x 128GB DDR5-5600 MHz modules. Utilizes 8 DIMM slots per CPU. Supports Memory Channel Interleaving for enhanced bandwidth. |
Storage - Primary | 2 x 4TB NVMe PCIe 4.0 SSD (RAID 1) | Samsung PM1733 Series, Sequential Read: 7,000 MB/s, Sequential Write: 6,500 MB/s. Configured in a mirrored RAID 1 array for redundancy. See RAID Levels for more details. |
Storage - Secondary | 8 x 16TB SAS HDD (RAID 6) | Seagate Exos X16, 7200 RPM, 256MB Cache, 12Gb/s SAS interface. Configured in a RAID 6 array for high capacity and fault tolerance. Storage Area Networks (SAN) compatibility is considered. |
GPU | 2 x NVIDIA H100 Tensor Core GPU | 80GB HBM3, 3.35 TFLOPS FP64, 67 TFLOPS FP32, 1979 TFLOPS TensorFloat-32. Optimized for Deep Learning Workloads. Requires dedicated power cabling. |
Power Supply | 2 x 1600W 80+ Titanium | Redundant power supplies for high availability. Supports peak power demands of the system. See Power Supply Units (PSU) for details. |
Network Interface | 2 x 10GbE + 1 x 100GbE | Intel X710-DA4 10GbE adapters, Mellanox ConnectX-6 100GbE adapter. Supports Virtual Extensible LAN (VXLAN) for network virtualization. |
Cooling | Liquid Cooling System | Custom loop liquid cooling for both CPUs and GPUs. Includes redundant pumps and radiators. See Server Cooling Technologies for information. |
Chassis | Supermicro 8U Rackmount Chassis | Supports dual double-width GPUs, optimized for airflow. Complies with Server Rack Standards. |
2. Performance Characteristics
The CR-7000 configuration is rigorously tested to ensure optimal performance across a range of workloads. The following benchmark results are indicative of its capabilities.
CPU Performance:
- SPECint_rate2017:** 185.2 – Demonstrates strong integer processing performance.
- SPECfp_rate2017:** 210.5 – Shows excellent floating-point performance, crucial for scientific computing.
- Linpack:** 1.2 PFLOPS – Peak performance for high-performance computing applications.
GPU Performance:
- Deep Learning (ResNet-50 Training):** 1,800 images/second – High throughput for image recognition tasks.
- HPC (Molecular Dynamics):** 50 nanoseconds/day per protein – Accelerates complex simulations.
- Tensor Core Performance (FP16):** 395 TFLOPS – High performance for mixed-precision training.
Storage Performance:
- Primary Storage (RAID 1):** Sequential Read: 14,000 MB/s, Sequential Write: 13,000 MB/s (Combined). Low latency access for demanding applications.
- Secondary Storage (RAID 6):** Sequential Read: 800 MB/s, Sequential Write: 700 MB/s. High capacity for large datasets.
Network Performance:
- 10GbE Throughput:** 9.5 Gbps – Sustained throughput for high-bandwidth applications.
- 100GbE Throughput:** 90 Gbps – Enables rapid data transfer and network communication.
Real-World Performance Examples:
- **Financial Modeling:** Monte Carlo simulations complete 3x faster compared to a similar configuration with older generation CPUs.
- **Video Encoding:** 8K video rendering completed in 45 minutes, significantly faster than traditional server setups.
- **Data Analytics:** Processing of 1TB datasets completed in under 2 hours, enabling faster insights.
- **Machine Learning Training:** Training of large language models (LLMs) reduced by 20% compared to previous generation hardware.
3. Recommended Use Cases
The CR-7000 configuration is ideal for applications demanding substantial computational resources. These include:
- **Scientific Computing:** Simulations in fields like physics, chemistry, and biology. Applications like computational fluid dynamics (CFD) and molecular modeling benefit significantly.
- **Machine Learning & Artificial Intelligence:** Training and inference of deep learning models, including image recognition, natural language processing, and predictive analytics. GPU Acceleration is crucial.
- **Data Analytics & Big Data Processing:** Analyzing large datasets to identify trends, patterns, and insights. Suitable for applications like data mining, fraud detection, and business intelligence.
- **High-Frequency Trading (HFT):** Low-latency processing of financial data for algorithmic trading. Requires extremely fast processing and network connectivity.
- **Video Rendering & Encoding:** Rendering high-resolution video content for film, television, and online streaming.
- **Virtualization & Cloud Computing:** Hosting virtual machines and providing cloud-based services. Server Virtualization is a key application.
- **Genomics Research:** Analyzing genomic data for research and development purposes.
- **Weather Forecasting:** Running complex weather models to predict future weather patterns.
4. Comparison with Similar Configurations
The CR-7000 configuration represents a high-end solution. Here's a comparison with alternative server configurations:
Configuration | CPU | RAM | GPU | Storage | Approximate Cost | Ideal Use Case |
---|---|---|---|---|---|---|
CR-6000 (Mid-Range) | Dual Intel Xeon Gold 6338 | 512GB DDR4 ECC Registered | 2 x NVIDIA A40 | 2 x 2TB NVMe + 4 x 8TB SAS | $60,000 | General-purpose server, moderate machine learning, data analytics |
CR-7000 (High-End - This Document) | Dual Intel Xeon Platinum 8480+ | 2TB DDR5 ECC Registered | 2 x NVIDIA H100 | 2 x 4TB NVMe + 8 x 16TB SAS | $150,000 | High-performance computing, large-scale machine learning, data analytics, HFT |
CR-8000 (Extreme) | Dual AMD EPYC 9654 | 4TB DDR5 ECC Registered | 4 x NVIDIA H100 | 4 x 8TB NVMe + 16 x 22TB SAS | $250,000+ | Extreme-scale computing, massive data analysis, cutting-edge AI research |
Standard 1U Server | Single Intel Xeon Silver 4310 | 64GB DDR4 ECC Registered | None | 1 x 1TB SATA SSD | $5,000 | Web hosting, application servers, basic database servers |
The CR-7000 offers a significant performance advantage over the CR-6000 due to its more powerful CPUs, larger memory capacity, and superior GPUs. While the CR-8000 provides even greater performance, it comes at a substantially higher cost. Standard 1U servers are not suitable for computationally intensive workloads due to their limited resources. The choice of configuration depends on specific application requirements and budget constraints. Consider Total Cost of Ownership (TCO) when evaluating options.
5. Maintenance Considerations
Maintaining the CR-7000 requires careful attention to several key areas to ensure optimal performance and reliability.
- **Cooling:** The liquid cooling system requires regular monitoring of coolant levels and pump performance. Dust accumulation on radiators should be addressed weekly. See Data Center Cooling for best practices.
- **Power:** Redundant power supplies are essential, but UPS (Uninterruptible Power Supply) protection is highly recommended to safeguard against power outages. Monitor power consumption to avoid exceeding PSU capacity. Power Distribution Units (PDUs) should be monitored closely.
- **Storage:** Regularly monitor RAID array health and proactively replace failing drives. Implement a robust backup strategy to protect against data loss. Data Backup and Recovery procedures should be documented and tested.
- **Networking:** Monitor network bandwidth utilization and ensure network connectivity is stable. Keep network drivers up-to-date.
- **Software Updates:** Apply firmware updates for all components, including motherboards, GPUs, and storage controllers. Keep the operating system and applications patched with the latest security updates.
- **Physical Environment:** Maintain a clean and dust-free environment to prevent overheating and component failure. Ensure adequate airflow around the server chassis.
- **Remote Management:** Utilize the IPMI 2.0 interface for remote monitoring and management of the server. This allows for proactive troubleshooting and maintenance. See Server Management Protocols
- **Regular Diagnostics:** Run regular diagnostic tests on all components to identify potential issues before they cause downtime.
- **Component Lifespan:** Be aware of the expected lifespan of each component and plan for replacements accordingly. Specifically, SSDs and HDDs have limited write endurance.
- **Environmental Monitoring:** Implement a system for monitoring temperature, humidity, and other environmental factors in the server room.
- **Documentation:** Maintain detailed documentation of the server configuration, including hardware specifications, software versions, and network settings. This is crucial for troubleshooting and disaster recovery.
- **Security:** Implement robust security measures to protect the server from unauthorized access and cyber threats. This includes firewalls, intrusion detection systems, and regular security audits. Server Security Best Practices should be followed.
- 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
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⚠️ *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.* ⚠️
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