CUDA Architecture
CUDA Architecture
The CUDA Architecture represents a high-performance dedicated server solution designed for computationally intensive tasks, ideal for server hosting and deployment within a data center environment. This configuration leverages NVIDIA CUDA-enabled GPUs alongside powerful CPUs and high-speed interconnects to accelerate workloads such as AI, machine learning, and scientific computing. It caters to researchers, data scientists, and businesses requiring significant processing power for complex applications.
Technical Specifications
| Feature | Specification |
|---|---|
| CPU Model | AMD EPYC 7763 (64 cores/128 threads) |
| Base/Boost Clock | 2.45 GHz / 3.5 GHz |
| RAM Type | DDR4 ECC Registered |
| RAM Size | 256 GB (8 x 32GB) |
| Storage (Boot) | 500GB NVMe PCIe Gen4 SSD |
| Storage (Data) | 8TB NVMe PCIe Gen4 SSD (RAID 1) |
| Network | 2 x 10 Gigabit Ethernet (100 Gbps bandwidth total) |
| Virtualization Support | AMD-V, Intel VT-x (with compatible OS) |
| ECC Support | Yes (CPU & RAM) |
| Power Usage | 750W 80+ Platinum PSU |
| Data Center Location Options | Amsterdam, New York, Singapore, London |
Performance Benchmarks
| Benchmark | Result (Approximate) |
|---|---|
| Single-Core Performance (PassMark) | 2,500 - 3,000 |
| Multi-Core Performance (PassMark) | 60,000 - 75,000 |
| Disk IO (Sequential Read - NVMe) | 7,000 MB/s |
| Disk IO (Sequential Write - NVMe) | 6,500 MB/s |
| Network Throughput (10GbE) | 9.5 Gbps (sustained) |
| SPEC CPU 2017 Rate (int) | 150-180 |
| SPEC CPU 2017 Rate (fp) | 200-240 |
- Note: Benchmark results will vary depending on the specific workload, software configuration, and system utilization.*
Recommended Use Cases
- AI Inference: Deploying and serving machine learning models for real-time predictions.
- Machine Learning Training: Accelerating the training process for complex neural networks.
- Scientific Computing: Running simulations and analyses in fields like physics, chemistry, and biology.
- Video Rendering: Encoding and decoding high-resolution video content.
- Data Analytics: Processing and analyzing large datasets.
- High-Performance Computing (HPC): Tackling demanding computational tasks.
- Financial Modeling: Complex calculations and simulations.
- Containerization workloads with significant GPU requirements.
Advantages
- Exceptional Performance per Dollar: Offers a high level of computational power at a competitive price point.
- Ultra-Low NVMe Latency: NVMe SSDs deliver fast storage access, crucial for data-intensive applications.
- Enhanced Reliability with DDR4 ECC: ECC RAM minimizes errors and ensures data integrity.
- Power Efficiency: Optimized power supply and cooling systems reduce energy consumption.
- High Availability: Redundant components and robust infrastructure minimize downtime.
- Rapid Provisioning: Servers can be deployed quickly, reducing time-to-market.
- Scalability: Easily scale resources as needed to meet changing demands.
- GPU Acceleration: NVIDIA CUDA enables massive parallel processing capabilities.
Comparison with Similar Configurations
| Configuration | CPU | RAM | Storage | Typical Use | Pros | Cons |
|---|---|---|---|---|---|---|
| Ryzen 9 5950X Server | AMD Ryzen 9 5950X (16 cores/32 threads) | 64GB DDR4 | 2TB NVMe SSD | Game Servers, Software Development | Lower cost, good general-purpose performance | Less powerful CPU, limited GPU capabilities |
| Intel Xeon Silver 4310 Server | Intel Xeon Silver 4310 (12 cores/24 threads) | 128GB DDR4 ECC | 4TB SATA HDD + 500GB NVMe SSD | Virtualization, Databases | ECC RAM, reliable performance | Slower storage, lower CPU core count |
| EPYC 7502P Server (256GB/4TB) | AMD EPYC 7502P (32 cores/64 threads) | 256GB DDR4 ECC | 4TB NVMe SSD (RAID 1) | Virtualization, Data Analytics | Excellent core count, good storage performance | Higher cost than Ryzen, less GPU focused |
Pricing & Ordering
Pricing varies based on RAM configuration (128GB, 256GB, 512GB), SSD tier (Gen3 vs Gen4), and data center location. A base configuration starts at $2,500 per month. Contact our sales team for a customized quote. Configure and order.
Setup & Management Best Practices
We recommend using a 64-bit Linux distribution such as Ubuntu Server or CentOS for optimal performance. Configure RAID 1 for data redundancy. Implement a robust backup strategy using tools like rsync or Veeam. Monitor server resources using tools like Prometheus and Grafana. Regularly apply security updates and kernel updates to mitigate vulnerabilities. Consider using a filesystem like XFS or ext4 for performance and stability.
Internal Links
- CPUs
- AMD Servers
- Intel Servers
- Server Configurations
- Workstation Configurations
- Ubuntu Server
- CentOS
- RAID
- NVMe SSDs
- DDR4 RAM
- ECC RAM
- Virtualization
- Networking
- Server Security
- Kernel Updates
- Data Backup
FAQ
What performance can I expect for AI inference?
Performance will vary greatly based on the model size and complexity. However, this configuration can typically handle hundreds of inferences per second for moderate-sized models.
Can I upgrade the RAM later?
Yes, RAM is expandable up to 512GB, subject to availability and compatibility.
Does this server support nested virtualization?
Support for nested virtualization depends on the hypervisor and OS configuration. Please check compatibility documentation before enabling.
Is there a network cap on bandwidth?
The 10 Gigabit Ethernet connection provides up to 9.5 Gbps sustained throughput. Fair usage policies apply.
What kind of DDoS protection is offered?
We provide basic DDoS mitigation as part of our standard service. More advanced protection is available as an add-on.
How often are backup snapshots taken?
Daily backup snapshots are taken by default. More frequent snapshots can be configured upon request.
What are the contract terms?
We offer flexible monthly and annual contracts. Please refer to our terms of service for details.
Notes
Benchmark results are indicative and can vary based on numerous factors. Component availability may fluctuate due to global supply chain conditions.
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.* ⚠️