GPU systems - Max IO - Twin - Rackmount servers

Discover our extensive selection of rack servers, ranging from 1U up to 10U, each designed to deliver the highest levels of performance, flexibility, scalability, and serviceability in datacenters. Our rackmount servers are engineered to handle a variety of workloads and applications, making them the backbone of modern enterprise and data center operations.

Key Advantages:

  • Versatile Performance: From 1U to 10U configurations, our servers are built to provide powerful and efficient performance for everything from basic applications to intensive computing tasks.

  • Flexible and Scalable: Easily configurable to meet the growing and changing demands of your business, our rack servers can scale to support increased workloads and expanded storage needs.

  • Wide Application Range: Ideal for a multitude of Enterprise and Data Center applications, including Virtualization, Big Data, Analytics, and Cloud Computing, ensuring that your infrastructure is future-proof.

  • Common Platform: As the most commonly used servers, rackmount units offer unlimited setup variations to perfectly align with your specific requirements.

With our rack servers, you can ensure your operations run smoothly and efficiently, meeting the demands of today while preparing for the challenges of tomorrow. Explore our selection and find the perfect solution to drive your enterprise forward.

GPU systems are specialized hardware solutions with latest NVidia GPU's, AMD GPUs and all the rest on the market. These Integrated GPU servers are designed for accelerated computing tasks such as machine learning, data analysis, and graphics rendering. Widely used in industries like automotive design, healthcare, and scientific research, these systems offer unparalleled performance, scalability, and efficiency.
Twin servers are optimized for high-performance and efficiency, often utilized in data centers, cloud computing, and enterprise IT environments. These systems boast advantages such as modular design for easy scalability, reduced energy consumption, and the capability to handle intensive workloads, making them an excellent choice for businesses looking to maximize ROI and performance.
Max IO solutions have the most IO slots per one server. They are optimized for high-throughput and low-latency data transfer, making them ideal for data-intensive applications like big data analytics, real-time financial transactions, and high-performance computing. These systems offer scalable and efficient I/O capabilities, reducing bottlenecks and enhancing overall system performance.

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  1. GPU System ARS-221GL-NR GPU System ARS-221GL-NR

    High Performance Computing
    AI/Deep Learning Training
    Large Language Model (LLM) Natural Language Processing
    General purpose CPU workloads, including analytics, data science, simulation, HPC, application servers, and more

    32 680.19 €
  2. GPU SuperServer SYS-120GQ-TNRT GPU SuperServer SYS-120GQ-TNRT

    Scientific Virtualization
    Rendering
    Big Data Analytics
    Business Intelligence
    High-performance Computing
    Research Lab, Astrophysics

    15 541.23 €
  3. GPU SuperServer SYS-420GU-TNXR GPU SuperServer SYS-420GU-TNXR

    High-performance Computing (HPC)
    AI / Deep Learning Training
    Nvidia A100 GPUs

    86 786.29 €
  4. GPU SuperServer SYS-1029GQ-TNRT GPU SuperServer 1029GQ-TNRT

    High-performance Computing
    Big Data Analytics
    Business Intelligence
    Research Lab, Astrophysics

    4 501.37 €
  5. GPU System ARS-111GL-NHR GPU System ARS-111GL-NHR

    High Performance Computing
    AI/Deep Learning Training and Inference
    Large Language Model (LLM) and Generative AI

    39 559.92 €
  6. GPU SuperServer SYS-420GP-TNAR GPU SuperServer SYS-420GP-TNAR

    AI / Deep Learning Training
    High-performance Computing (HPC)
    Nvidia A100 GPUs

    153 716.98 €
  7. GPU A+ Server AS-2114GT-DPNR - 2 nodes GPU A+ Server AS-2114GT-DPNR - 2 nodes

    Media/Video Streaming
    AI Inference and Machine Learning
    GPU Virtualization (VDI)
    Industrial Automation, Retail, Smart Medical Expert Systems

    13 541.78 €
  8. GPU A+ Server AS-4125GS-TNRT1 GPU A+ Server AS-4125GS-TNRT1

    AI / Deep Learning
    High Performance Computing
    Single Root
    GPU Virtualization

    13 959.31 €
  9. GPU SuperServer SYS-420GP-TNAR+ GPU SuperServer SYS-420GP-TNAR+

    AI / Deep Learning Training
    High-performance Computing (HPC)
    Nvidia A100 GPUs

    154 831.94 €
  10. GPU A+ Server AS-2114GT-DNR - 2 nodes GPU A+ Server AS-2114GT-DNR - 2 nodes

    Media/Video Streaming
    AI Inference and Machine Learning
    Cloud Gaming
    Industrial Automation, Retail, Smart Medical Expert Systems

    15 173.07 €
  11. GPU A+ Server AS-8125GS-TNHR GPU A+ Server AS-8125GS-TNHR

    High-performance Computing
    AI / Deep Learning Training
    Nvidia H100 GPUs
    NVIDIA® NVLink™ with NVSwitch™

    275 779.01 €
  12. GPU A+ Server AS-4124GO-NART GPU A+ Server AS-4124GO-NART

    AI Compute
    Model Training
    Deep Learning
    High-performance Computing (HPC)

    150 248.21 €
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What is a Rackmount Server?

  • A rackmount server, also known as a rack server, is a computer designed to function as a server and be installed in a rack. The rack contains multiple mounting slots called bays, each designed to hold a hardware unit secured in place with screws. Multinode servers are often deployed in these racks to maximize efficiency and resource utilization.

How to Choose a Rackmount Server

  • When choosing a rackmount server, consider factors such as performance requirements, scalability, and budget. Determine the necessary CPU power, memory, and storage capacity based on your workload. Additionally, evaluate the rack space available and the cooling requirements to ensure optimal server performance.

What Does 1U, 2U, 3U, 4U Mean?

  • The terms 1U, 2U, 3U, and 4U refer to the height of the server in rack units (U). Each "U" is equivalent to 1.75 inches. A 1U server is 1.75 inches tall, a 2U server is 3.5 inches tall, and so on. These measurements help in understanding how much space the server will occupy in the rack.