CUDA Runtime API Reference
CUDA Runtime API Reference
This dedicated server is designed for compute-intensive workloads leveraging NVIDIA CUDA technology, ideal for researchers, developers, and businesses requiring high-performance parallel processing. Offering exceptional performance for tasks like deep learning, scientific simulations, and financial modeling, this server is a core component for robust server hosting solutions within a modern data center environment. It provides a platform for accelerating applications with the CUDA Runtime API.
Technical Specifications
| CPU Model and Cores/Threads | Base/Boost Clock | RAM Type and Size | Storage (NVMe/SATA, Capacity, RAID Options) | Network (Port Speed, Bandwidth) | Virtualization Support | ECC Support | Power Usage | Data Center Location Options |
|---|---|---|---|---|---|---|---|---|
| AMD EPYC 7763 (64 Cores / 128 Threads) | 2.45 GHz / 3.5 GHz | 256GB DDR4-3200 ECC Registered | 2 x 4TB NVMe PCIe Gen4 SSD (RAID 1) | 10 Gigabit Ethernet (100 Gbps shared bandwidth) | KVM, VMware ESXi | Yes | 350W - 500W (configurable) | Amsterdam, Frankfurt, London, New York, Singapore |
Performance Benchmarks
| Benchmark | Result (Approximate) | Notes |
|---|---|---|
| Single-Core Geekbench 5 | 1,600 - 1,800 | Results vary based on OS and background processes. |
| Multi-Core Geekbench 5 | 120,000 - 140,000 | Highly dependent on workload and parallelization. |
| CrystalDiskMark (NVMe Sequential Read) | 6,500 - 7,500 MB/s | Performance influenced by SSD model and controller. |
| iperf3 Network Throughput | 8 - 9 Gbps | Shared bandwidth; actual throughput depends on network congestion. |
| Linpack (HPL) | 800 - 950 TFLOPS | Achieved with optimized CUDA applications. |
Recommended Use Cases
- Deep Learning Training and Inference: Accelerate model training and deployment with CUDA.
- Scientific Computing: Run complex simulations in fields like physics, chemistry, and biology.
- Financial Modeling: Perform high-frequency trading and risk analysis.
- Video Encoding/Decoding: Process large video files efficiently.
- Data Analytics: Analyze massive datasets with parallel processing.
- Machine Learning: Develop and deploy machine learning algorithms.
- GPU Rendering: Utilize GPU power for photorealistic rendering.
Advantages
- Exceptional Performance per Dollar: Delivers high compute power at a competitive price point.
- Ultra-Low NVMe Latency: Fast storage access for demanding applications.
- DDR4-3200 ECC Registered Memory: Enhanced data integrity and reliability.
- Power Efficiency: Optimized power consumption for reduced operating costs.
- High Availability: Redundant power supplies and RAID storage options minimize downtime.
- Rapid Provisioning: Quick server setup and deployment through our control panel.
- Scalability: Easily upgrade RAM and storage as your needs grow.
- Dedicated Resources: Avoid resource contention with a dedicated server environment.
Comparison with Similar Configurations
| Configuration | CPU | RAM | Storage | Typical Use | Pros | Cons |
|---|---|---|---|---|---|---|
| AMD EPYC 7502P Server (256GB/4TB) | AMD EPYC 7502P (32 Cores / 64 Threads) | 256GB DDR4-3200 ECC Registered | 2 x 4TB NVMe PCIe Gen4 SSD (RAID 1) | General Purpose Server, Virtualization | Lower cost, good all-around performance. | Lower core count than the 7763. |
| Intel Xeon Gold 6338 Server (256GB/4TB) | Intel Xeon Gold 6338 (32 Cores / 64 Threads) | 256GB DDR4-3200 ECC Registered | 2 x 4TB NVMe PCIe Gen4 SSD (RAID 1) | Database Server, Web Hosting | Intel ecosystem compatibility, strong single-core performance. | Generally more expensive than comparable AMD EPYC systems. |
| Ryzen 7 7700 Server | AMD Ryzen 7 7700 (8 Cores / 16 Threads) | 64GB DDR5-5200 ECC Registered | 1 x 2TB NVMe PCIe Gen4 SSD | Development, Small Databases | Lower cost, good for single-user development. | Significantly lower core count and RAM capacity. |
Pricing & Ordering
Pricing varies based on RAM configuration (128GB, 256GB, 512GB), SSD tier (Gen3 vs. Gen4), data center region, and bandwidth allocation. A base configuration starts at $799/month. Custom configurations are available. Configure and order
Setup & Management Best Practices
We recommend using a 64-bit Linux distribution such as Ubuntu Server or CentOS for optimal performance. Utilize RAID 1 for data redundancy. Implement a robust backup strategy using tools like rsync or Veeam. Monitor server resources with tools like Grafana and Prometheus. Regularly apply kernel updates and security patches. Consider using a firewall like iptables or ufw to harden security.
Internal Links
- CPUs
- AMD Servers
- Intel Servers
- Server Configurations
- Workstation Configurations
- Operating Systems
- Linux Server Security
- Server Virtualization
- Data Center Networking
- RAID Levels
- ECC Memory
- NVMe Storage
- Ubuntu Server
- CentOS
- Server Monitoring Tools
- CUDA Toolkit
FAQ
What performance can I expect from CUDA applications?
Performance is highly dependent on the specific application and level of CUDA optimization. Expect significant acceleration compared to CPU-only execution, potentially reaching hundreds of times faster for well-parallelized tasks.
Can I upgrade the server's RAM and storage?
Yes, RAM and storage can be upgraded. Contact our support team for available options and pricing.
Does this server support virtualization?
Yes, KVM and VMware ESXi are both supported. Licensing for VMware ESXi is the responsibility of the user.
Is there a network cap on the 10 Gigabit Ethernet connection?
The 10 Gigabit Ethernet connection shares a 100 Gbps bandwidth with other servers in the same data center. Dedicated bandwidth options are available upon request.
Is DDoS protection included?
Yes, basic DDoS protection is included as standard. Enhanced DDoS mitigation services are available as an add-on.
How often are backup snapshots taken?
Backup snapshots are taken daily by default. More frequent snapshots can be configured for an additional fee.
What are the contract terms?
We offer flexible monthly contracts with no long-term commitments.
Notes
Benchmark results are approximate and may vary depending on the specific workload, operating system, and software configuration. Component availability may vary; we will substitute with equivalent or superior components if necessary.
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.* ⚠️