Benchmarking Procedures Document
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- 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.
---
- 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.
---
- 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.
---
- 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.
---
- 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.
---
- 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.
---
- 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.
---
- 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.* ⚠️
Benchmarking Procedures Document: "Project Chimera" Server Configuration
This document details the technical specifications, performance characteristics, recommended use cases, comparisons, and maintenance considerations for the "Project Chimera" server configuration. This configuration is designed for high-performance computing, virtualization, and data-intensive applications. This document is intended for internal use by system administrators, engineers, and support staff. See Server Naming Conventions for the origin of the project name.
1. Hardware Specifications
The "Project Chimera" server configuration is built around a dual-socket motherboard designed for maximum throughput and scalability. Detailed specifications are outlined below. Refer to Hardware Component Selection Process for the rationale behind component choices.
| Component | Specification | Manufacturer | Model Number | Notes |
|---|---|---|---|---|
| CPU | Dual Intel Xeon Platinum 8480+ | Intel | P-8480+ | 56 Cores/112 Threads per CPU, 3.2 GHz Base Frequency, 4.0 GHz Max Turbo Frequency, 320MB L3 Cache |
| Motherboard | Supermicro X13 Series | Supermicro | X13DEI-N6 | Dual Socket LGA 4677, DDR5 ECC Registered Memory Support, PCIe 5.0 Support |
| RAM | 2TB DDR5 ECC Registered | Samsung | M393A4K40DB8-CWE | 16 x 128GB Modules, 5600 MHz, CL36, Buffered |
| Storage – OS/Boot | 1TB NVMe PCIe Gen4 x4 SSD | Western Digital | SN850X | Read: 7300 MB/s, Write: 6600 MB/s |
| Storage – Application/Data | 8 x 16TB SAS 12Gbps 7.2K RPM Enterprise HDD | Seagate | Exos X16 | RAID 10 Configuration (4 x Drives per VDG) |
| Storage – Cache | 2 x 3.2TB NVMe PCIe Gen4 x4 SSD | Micron | 9400 Pro | Used as Read/Write Cache for the HDD RAID array via Hardware RAID Controller |
| GPU | NVIDIA A100 80GB | NVIDIA | A100-80G | PCIe 4.0 x16, Tensor Cores for AI/ML workloads |
| Network Interface Cards (NICs) | 2 x 200GbE QSFP28 | Mellanox (NVIDIA) | ConnectX7-QSFP28 | RDMA capable, supports RoCEv2 and iWARP |
| Power Supply Units (PSUs) | 2 x 3000W 80+ Titanium | Supermicro | PWS-3000T | Redundant Power Supplies, N+1 Configuration |
| RAID Controller | Broadcom MegaRAID SAS 9660-8i | Broadcom | 9660-8i | Hardware RAID Controller, supports RAID levels 0, 1, 5, 6, 10, and more. See RAID Configuration Guidelines. |
| Chassis | 4U Rackmount Chassis | Supermicro | 847E16-R1200B | Supports dual CPUs, multiple GPUs, and extensive storage |
| Cooling | Redundant Hot-Swap Fans with High-Efficiency Heat Sinks | Supermicro | Integrated with Chassis | Designed for optimal airflow and thermal management. See Thermal Management Procedures. |
2. Performance Characteristics
The "Project Chimera" configuration was subjected to a series of benchmarks to evaluate its performance capabilities. All benchmarks were run in a controlled environment with consistent configurations. Benchmark results are detailed below. Refer to Benchmark Methodology for detailed testing procedures.
- CPU Performance:* Using SPEC CPU 2017, the server achieved a SPECrate2017_fp_base2 score of 485 and a SPECrate2017_int_base2 score of 612. These scores demonstrate excellent performance in both floating-point and integer workloads. Detailed results can be found in SPEC CPU 2017 Results Archive.
- Storage Performance:* IOmeter tests with a 4KB random read/write workload on the RAID 10 array yielded an average IOPS of 85,000 and a latency of 0.8ms. Sequential read/write speeds averaged 1.8 GB/s. Cache performance with the Micron 9400 Pro NVMe drives resulted in approximately 300,000 IOPS with a latency of 0.2ms. See Storage Performance Analysis for a comprehensive report.
- Network Performance:* Using iperf3, the 200GbE NICs achieved a sustained throughput of 185 Gbps with negligible packet loss. RDMA testing with RoCEv2 showed a latency of under 10 microseconds. Details are available in the Network Performance Report.
- GPU Performance:* Using the MLPerf benchmark suite, the NVIDIA A100 GPU achieved a score of 450 TFLOPS for FP16 training and 300 TFLOPS for FP32 inference. This highlights the server’s suitability for AI and machine learning tasks. Refer to GPU Benchmarking Documentation.
- Virtualization Performance:* Running VMware vSphere 7.0, the server was able to support 64 virtual machines (VMs) with 16 vCPUs and 64GB of RAM each, maintaining acceptable performance levels. VMware performance metrics are documented in Virtualization Performance Monitoring.
- Real-World Performance:**
In real-world scenarios, the server demonstrated exceptional performance. A large-scale database migration (50TB) completed in under 8 hours. High-resolution video rendering tasks were completed 30% faster compared to a baseline configuration. Machine learning model training times were reduced by 40% due to the powerful GPU and CPU combination.
3. Recommended Use Cases
The "Project Chimera" server configuration is ideally suited for the following applications:
- **High-Performance Computing (HPC):** Its powerful CPUs, large memory capacity, and high-speed network connectivity make it ideal for scientific simulations, financial modeling, and other computationally intensive tasks. See HPC Application Deployment Guide.
- **Virtualization:** The server can efficiently host a large number of virtual machines, making it suitable for server consolidation and cloud infrastructure. Consider Virtualization Best Practices.
- **Data Analytics & Big Data:** The fast storage subsystem and high memory capacity enable efficient processing of large datasets for data analytics and business intelligence applications.
- **Artificial Intelligence (AI) & Machine Learning (ML):** The NVIDIA A100 GPU provides the necessary processing power for training and deploying AI/ML models. Refer to AI/ML Infrastructure Guidelines.
- **Database Servers:** The server's performance and reliability make it well-suited for hosting large, mission-critical databases. See Database Server Configuration.
- **Video Rendering & Encoding:** The powerful CPUs and GPUs accelerate video rendering and encoding tasks.
4. Comparison with Similar Configurations
The "Project Chimera" configuration is positioned as a high-end solution. Here's a comparison with similar configurations:
| Configuration | CPU | RAM | Storage | GPU | Price (Estimate) | Use Case |
|---|---|---|---|---|---|---|
| **Project Chimera** | Dual Intel Xeon Platinum 8480+ | 2TB DDR5 | 1TB NVMe + 128TB SAS RAID 10 | NVIDIA A100 80GB | $45,000 - $55,000 | HPC, Virtualization, AI/ML, Data Analytics |
| **Configuration A (Mid-Range)** | Dual Intel Xeon Gold 6348 | 512GB DDR4 | 512GB NVMe + 32TB SAS RAID 5 | NVIDIA RTX A4000 | $20,000 - $25,000 | Virtualization, Small-Scale Data Analytics |
| **Configuration B (Entry-Level)** | Single Intel Xeon Silver 4310 | 256GB DDR4 | 512GB NVMe | None | $8,000 - $12,000 | Web Hosting, Small Business Applications |
| **Configuration C (AMD EPYC)** | Dual AMD EPYC 7763 | 2TB DDR4 | 1TB NVMe + 128TB SAS RAID 10 | NVIDIA A100 80GB | $40,000 - $50,000 | HPC, Virtualization, AI/ML, Data Analytics (AMD alternative) |
- Key Differences:**
- **CPU:** The Intel Xeon Platinum 8480+ offers superior core count and clock speeds compared to the Gold and Silver series. AMD EPYC 7763 provides a competitive alternative with similar performance characteristics.
- **RAM:** 2TB of DDR5 RAM provides significantly more capacity and bandwidth compared to the 512GB and 256GB options.
- **Storage:** The combination of NVMe cache and SAS RAID 10 provides a balance of speed and capacity.
- **GPU:** The NVIDIA A100 is a high-end GPU designed for demanding AI/ML workloads, offering significant performance advantages over the RTX A4000. See GPU Comparison Matrix for detailed specifications.
5. Maintenance Considerations
Maintaining the "Project Chimera" server configuration requires careful consideration of several factors.
- **Cooling:** The high-power components generate significant heat. Ensure the server room has adequate cooling capacity and that the chassis fans are functioning properly. Regularly check for dust accumulation. See Data Center Cooling Best Practices. Monitor CPU and GPU temperatures using Server Monitoring Tools.
- **Power Requirements:** The server requires a dedicated power circuit with sufficient amperage to handle the peak power draw of approximately 6000W. Ensure the power supply units are connected to separate power feeds for redundancy. See Power Distribution Unit (PDU) Configuration.
- **RAID Maintenance:** Regularly monitor the health of the RAID array and replace any failing hard drives promptly. Implement a robust backup and disaster recovery plan. Refer to Data Backup and Recovery Procedures.
- **Firmware Updates:** Keep the server's BIOS, firmware, and drivers up to date to ensure optimal performance and security. Use Firmware Update Management System.
- **Network Configuration:** Properly configure the network interfaces and ensure adequate bandwidth for all applications. See Network Configuration Guide.
- **Physical Security:** The server should be housed in a secure data center with restricted access. Implement physical security measures to prevent unauthorized access. Refer to Data Center Security Policies.
- **Regular Diagnostics:** Run regular system diagnostics to identify potential hardware failures. Utilize Server Diagnostic Tools.
- **Component Lifecycles:** Understand the expected lifecycles of each component and plan for replacements accordingly. See Hardware Lifecycle Management.
- 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.
---
- 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
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- Telegram: @powervps Servers at a discounted price
⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️ Hardware RAID Controller Thermal Management Procedures Benchmark Methodology SPEC CPU 2017 Results Archive Storage Performance Analysis Network Performance Report GPU Benchmarking Documentation Virtualization Performance Monitoring HPC Application Deployment Guide Virtualization Best Practices Database Server Configuration AI/ML Infrastructure Guidelines GPU Comparison Matrix Data Center Cooling Best Practices Server Monitoring Tools Power Distribution Unit (PDU) Configuration Data Backup and Recovery Procedures Firmware Update Management System Network Configuration Guide Data Center Security Policies Server Diagnostic Tools Hardware Lifecycle Management Hardware Component Selection Process RAID Configuration Guidelines Server Naming Conventions ```
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.* ⚠️