CUDA Programming Model
CUDA Programming Model
The CUDA Programming Model represents a high-performance dedicated server configuration optimized for parallel processing workloads, particularly those leveraging NVIDIA GPUs. This server is ideal for researchers, data scientists, and businesses requiring intensive computation for applications like machine learning, scientific simulations, and video rendering. Our server hosting solutions provide a robust and scalable platform within a secure data center environment.
Technical Specifications
| Feature | Specification |
|---|---|
| CPU Model and Cores/Threads | AMD EPYC 7763 (64 Cores / 128 Threads) |
| Base/Boost Clock | 2.45 GHz / 3.5 GHz |
| RAM Type and Size | 256GB DDR4 ECC Registered, 3200MHz |
| Storage (NVMe/SATA, Capacity, RAID Options) | 2 x 4TB NVMe PCIe Gen4 SSD (RAID 1), 2 x 8TB SATA HDD (RAID 1) |
| Network | 10 Gigabit Ethernet, 100 Tbps Bandwidth |
| Virtualization Support | Full Virtualization Support (KVM, VMware ESXi) |
| ECC Support | Yes (CPU and RAM) |
| Power Usage | 850W 80+ Platinum Power Supply |
| Data Center Location Options | US East (Virginia), US West (California), Europe (Frankfurt) |
Performance Benchmarks
| Benchmark | Result (Approximate) |
|---|---|
| Single-Core Performance (PassMark) | 2,500 – 3,000 |
| Multi-Core Performance (PassMark) | 40,000 – 45,000 |
| Disk IO (NVMe, Sequential Read) | 7,000 MB/s |
| Disk IO (NVMe, Sequential Write) | 6,500 MB/s |
| Network Throughput | 9.5 Gbps (Realistic sustained throughput) |
- Note: Benchmark results will vary depending on the specific workload, software, and configuration.*
Recommended Use Cases
- **Machine Learning Training:** Accelerate the training of deep learning models using NVIDIA GPUs.
- **Scientific Simulations:** Run complex simulations in fields like computational fluid dynamics and molecular dynamics.
- **Video Rendering:** Efficiently render high-resolution videos and animations.
- **Data Analytics:** Process and analyze large datasets with high throughput.
- **AI Inference:** Deploy and scale AI models for real-time inference.
- **Financial Modeling:** Perform complex financial calculations and risk analysis.
- **High-Performance Computing (HPC):** General-purpose HPC workloads benefiting from parallel processing.
Advantages
- **High Performance per Dollar:** Optimized hardware configuration delivers excellent performance for the cost.
- **Ultra-Low NVMe Latency:** NVMe SSDs provide extremely fast storage access.
- **DDR4 ECC Registered RAM:** Ensures data integrity and system stability.
- **Power Efficiency:** 80+ Platinum power supply minimizes energy consumption.
- **High Availability:** RAID configurations and redundant power supplies minimize downtime.
- **Rapid Provisioning:** Quickly deploy and configure the server to meet your needs.
- **Scalability:** Ability to scale resources as your requirements grow.
- **Dedicated Resources:** Enjoy exclusive access to all server resources.
Comparison with Similar Configurations
| Configuration | CPU | RAM | Storage | Typical Use | Pros | Cons |
|---|---|---|---|---|---|---|
| EPYC 7502P Server (256GB/4TB) | AMD EPYC 7502P (32 Cores / 64 Threads) | 256GB DDR4 ECC Registered | 4TB NVMe SSD | General Purpose Server, Virtualization | Lower cost, good all-around performance | Lower core count, less GPU potential |
| Ryzen 9 5950X Server | AMD Ryzen 9 5950X (16 Cores / 32 Threads) | 128GB DDR4 ECC | 2TB NVMe SSD | Gaming, Content Creation | Excellent single-core performance, lower price | Limited scalability, fewer cores than EPYC |
| Intel Xeon Gold 6338 Server | Intel Xeon Gold 6338 (32 Cores / 64 Threads) | 256GB DDR4 ECC Registered | 4TB NVMe SSD | Enterprise Applications, Databases | Strong Intel ecosystem support | Generally higher cost than comparable AMD options |
Pricing & Ordering
Pricing varies based on RAM tier (DDR4 vs. DDR5), SSD capacity, RAID configuration, and datacenter region. A base configuration starts at $3,500 per month. Contact our sales team for a customized quote. Configure and order
Setup & Management Best Practices
We recommend using a Linux distribution like Ubuntu Server or CentOS for optimal performance. Utilize RAID 1 or RAID 10 for data redundancy. Implement a robust backup strategy, including offsite backups. Monitor server resources with tools like Grafana and Prometheus. Regularly apply kernel updates and security patches. Consider using a firewall and intrusion detection system to enhance security.
Internal Links
- CPUs
- AMD Servers
- Intel Servers
- Server Configurations
- Workstation Configurations
- Ubuntu Server
- CentOS
- RAID
- Virtualization
- Networking
- ECC Memory
- NVMe SSDs
- Data Centers
- Server Security
- GPU Computing
- Kernel Updates
FAQ
What performance can I expect for deep learning training?
Performance will depend on the specific model and dataset. However, you can expect significant acceleration compared to CPU-only training, often achieving speedups of 5x to 20x or more.
Can I upgrade the RAM or storage after purchase?
Yes, RAM and storage are generally upgradeable, but availability may vary. Contact our support team for assistance with upgrades.
Is virtualization supported on this server?
Yes, full virtualization support is included with KVM and VMware ESXi. You can run multiple virtual machines on this server.
What is the maximum network throughput I can achieve?
The server offers 10 Gigabit Ethernet connectivity with a sustained throughput of approximately 9.5 Gbps.
Is DDoS protection included?
Yes, we offer basic DDoS protection as part of our standard service. Enhanced DDoS mitigation options are available for an additional fee.
How often are backup snapshots taken?
Backup snapshots are taken daily by default. More frequent snapshots can be configured upon request.
What are the contract terms?
We offer flexible contract terms, including monthly, quarterly, and annual options.
Notes
Benchmark results are approximate and can vary significantly based on the workload and configuration. Component availability is subject to change 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.* ⚠️