2U - 3 GPU - 32 Dimms - Certified with Oracle Linux - Dual CPU - NVMe native - GPU servers
Enhance your computational capabilities with our versatile GPU servers. 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 GPU servers for scalable, high-quality computing solutions tailored to your project's needs.
Servers Certified for Oracle's enterprise software solutions are predominantly used in large corporations and data centers, focusing on use-cases like database management, ERP, and cloud services. These products offer key benefits such as robust data analytics, high-level security features, and seamless integration capabilities, making them essential for data-intensive and mission-critical operations.
2U is two rack unit size devices, that are 19" wide in standard rack enclosures.
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.
Servers equipped with three GPUs provide an enhanced level of computational power, perfectly suited for high-performance computing applications, such as machine learning training, scientific simulations, and real-time analytics. The trio of GPUs allows for greater parallel processing capabilities, thereby optimizing workload performance and offering increased redundancy and reliability.
Servers with 32 memory sockets are designed to handle extreme computational challenges, making them the go-to choice for government agencies and scientific institutions focusing on areas like nuclear simulations, climate modeling, and large-scale data analytics. These servers deliver not only unmatched memory capacity but also optimal resource utilization, helping to solve complex problems more efficiently.
Servers with native NVMe (Non-Volatile Memory Express) support are designed for the most demanding data-intensive tasks, such as big data analytics, machine learning, and high-frequency trading. Native NVMe offers unparalleled speed and low-latency data access, revolutionizing the data processing capabilities of enterprises and HPC centers.
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GPU optimized SYS-221H-TNR
AI Inference and Machine Learning
Virtualization
Enterprise Server
Cloud Computing
Software Defined Storage8 762.55 € -
GPU optimized SYS-621H-TN12R
AI Inference and Machine Learning
Virtualization
Enterprise Server
Cloud Computing
Software Defined Storage8 798.64 €
How to choose a GPU server?
- 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 that balances performance, connectivity, and power efficiency—key factors for high-performance GPU solutions like NVIDIA or AMD server GPUs.
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's A100 and the newer H100 GPUs 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, making them top choices for enterprise-grade, GPU-accelerated servers.
How many cores are in a GPU?
- The number of cores in a GPU server can vary widely depending on the model and manufacturer. High-end GPUs, particularly those designed for supercomputing GPU servers or deep learning GPU servers, 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.