AMD EPYC 7000 series - AMD EPYC 9004 series - Dual CPU - Windows Server 2019 compatible - GPU servers
Enhance your computational capabilities with our versatile servers designed for data center environments. Tailored for demanding tasks across various domains, our servers integrate cutting-edge technology to meet your specific needs.
Key Advantages:
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Diverse Configurations: Select from top-of-the-line NVIDIA and AMD GPUs like the Nvidia Tesla V100 and Nvidia A100, suitable for various professional needs from HPC to enterprise solutions.
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Massive Parallel Processing Power: Ideal for AI, machine learning, and complex simulations, our servers offer unparalleled processing capabilities to handle intensive data tasks efficiently.
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Optimized for AI and Deep Learning: Specifically designed for deep learning and AI applications, ensuring optimal performance for AI-driven projects.
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Advanced Connectivity: Featuring GPU-Direct technology for superior data transfer speeds, crucial for high-load computational tasks.
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Flexible Form Factors: From compact 1U GPU servers to robust 4U GPU configurations, we offer a variety of form factors to meet your specific requirements.
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Reliability and Scalability: Built to support long-term, intensive operations with options to scale as your computational needs grow.
Explore our extensive range of GPU servers and discover the perfect solution tailored to meet your specific computational needs.
Servers using WS2K19, also known as Windows Server 2019, are widely utilized in enterprise data centers, private clouds, and remote offices for applications like server virtualization, Active Directory, and container orchestration. The server OS offers advantages such as robust security features, improved scalability, and enhanced support for hybrid cloud scenarios.
Dual CPU servers offer enhanced performance and are ideal for mid to large-sized enterprises running compute-intensive applications or virtualized environments. With two processors, these servers provide higher throughput and are commonly deployed in data centers for machine learning, complex simulations, and high-traffic web services, maximizing operational efficiency and scalability.
The AMD EPYC 7000 series processors are designed for scalable data center and enterprise applications, excelling in tasks like virtualization, high-performance computing, and cloud-based solutions. Leveraging a significant number of cores and an architecture optimized for efficiency, these processors offer high performance, robust security features, and an attractive TCO (Total Cost of Ownership), making them a favored choice for organizations aiming to achieve operational excellence.
The AMD EPYC 9004 processor series offers unparalleled performance and efficiency, making it a go-to choice for data centers, enterprise applications, and complex computational workloads. With its scalable architecture and high core-count, this processor type enables faster data processing, lowers operational costs, and delivers robust security features for a wide range of use cases.
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How to choose a GPU server for GPU acceleration?
- To select the right GPU server, consider your specific workload requirements, such as AI server capabilities, machine learning server demands, or deep learning server needs. Look for a server equipped with advanced processors like AMD EPYC 9004 Series, which balances performance, connectivity, and power efficiency—key factors for high-performance GPU solutions like NVIDIA or AMD server GPUs. Additionally, servers with the latest Intel Xeon Scalable processors are optimized for high-density computing, supporting advanced technologies and parallel computing for high-performance applications.
What is the best GPU for servers?
- The best GPU for servers depends largely on the specific applications and computational demands. For high-performance computing, AI training, and deep learning, NVIDIA GPUs, such as the A100 and the newer H100, are currently among the most powerful options. The NVIDIA A100 is designed to handle diverse workloads efficiently, making it ideal for everything from AI to scientific computing. On the other hand, the NVIDIA H100, part of NVIDIA’s Hopper architecture, provides exceptional performance for AI and machine learning, pushing the boundaries of what server GPUs can accomplish in terms of speed and processing power. Both these models offer massive improvements in throughput, energy efficiency, and AI feature sets, delivering the highest performance for enterprise-grade, GPU-accelerated servers.
How many cores are in a GPU?
- The number of cores in a GPU server, often integrated with scalable processors like the 3rd Gen Intel Xeon Scalable Processors, can vary widely depending on the model and manufacturer. High-end GPUs, particularly those designed for supercomputing or deep learning, can house thousands of cores to efficiently manage multiple parallel tasks in computationally intensive environments.
Best GPU servers
- SYS-4029GP-TRT2 Supermicro GPU SuperServer: Engineered for Artificial Intelligence and High-performance Computing with a focus on Big Data Analytics and Astrophysics.
- GPU A+ Server AS-4125GS-TNRT1: Designed for Single Root AI / Deep Learning applications and GPU Virtualization, offering High Performance Computing capabilities.
- GPU A+ Server AS-4124GS-TNR+: Specialized for Cloud Gaming and Molecular Dynamics Simulation with Nvidia A100 GPUs, making it ideal for rigorous scientific applications.
- GPU SuperServer SYS-421GE-TNRT3: Perfect for Design & Visualization, Diagnostic Imaging, and intensive 3D Rendering.
- GPU A+ Server AS-8125GS-TNHR-LC: The ultimate in liquid-cooled technology for High-performance Computing and AI / Deep Learning Training, featuring NVIDIA® NVLink™ with NVSwitch™.
GPU Server Cost
- At Server Simply, our GPU servers are priced to accommodate a variety of budgetary and performance needs. Prices range from approximately €3,700 for entry-level models suitable for basic machine learning tasks, to over €280,000 for advanced models equipped with the latest technologies for intensive computational tasks such as deep learning, high-performance computing, and AI training. This wide range ensures options for both startups and large enterprises looking to enhance their computing power.