CloudDC - GPU systems - Multi Processor - 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:
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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.
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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.
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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.
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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.
Multi-processor systems are engineered to handle high-performance computing tasks, machine learning, and data analytics by utilizing multiple CPUs to execute parallel operations efficiently. Deployed in research labs, data centers, and enterprises, these systems offer significant advantages in terms of computational speed and multitasking capabilities, thereby optimizing workload management and resource utilization.
CloudDC is a versatile cloud infrastructure solution tailored for data centers, public cloud services, and hybrid cloud configurations, focusing on scalability, security, and efficiency. Its benefits include automated resource allocation, robust data recovery options, and seamless integration capabilities, making it ideal for businesses aiming for digital transformation and optimized IT costs.
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.
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GPU SuperServer SYS-521GU-TNXR
High-performance Computing (HPC)
AI / Deep Learning Training
Nvidia H100 GPUs132 187.39 € -
GPU SuperServer SYS-120GQ-TNRT
Scientific Virtualization
Rendering
Big Data Analytics
Business Intelligence
High-performance Computing
Research Lab, Astrophysics15 633.88 € -
GPU A+ Server AS-8125GS-TNMR2
High-performance Computing
AI / Deep Learning Training
Industrial Automation, Retail
Climate and Weather Modeling236 561.30 € -
GPU SuperServer SYS-420GU-TNXR
High-performance Computing (HPC)
AI / Deep Learning Training
Nvidia A100 GPUs87 394.51 € -
GPU SuperServer SYS-4029GP-TRT
3D rendering, Astrophysics
Chemistry, Cloud Computing
Virtualization
Compute intensive application6 537.00 € -
GPU SuperServer SYS-821GE-TNHR
Conversational AI
Industrial Automation, Retail
AI/Deep Learning Training
High Performance Computing
Drug Discovery
Finance & Economics
Healthcare
Business Intelligence & Analytics
Climate and Weather Modeling253 050.81 € -
CloudDC SuperServ SYS-620C-TN12R
Web Servers, Firewall Application
Data Center Optimized
Value IaaS
Cloud Computing
Edge Nodes
Content Delivery Network (CDN)
Compact Server
DNS & Gateway Servers3 907.03 € -
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 more32 819.58 € -
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 Systems13 651.53 € -
GPU SuperServer SYS-1029GQ-TRT
GPU Server, Mission-critical app.
enterprise server, HPC
oil & gas, financial, 3D rendering
chemistry4 442.59 € -
CloudDC SuperServer SYS-521C-NR
Data Center Optimized
Cloud Computing
Network Appliance
Database/Storage
AI inferencing
ML training3 264.62 € -
CloudDC A+ Server AS-1114CS-TNR
Content Delivery Network
Financial Services
Cloud Computing
Network Appliance
Private Cloud
Deep Learning Inferencing2 676.40 € -
GPU System ARS-111GL-NHR
High Performance Computing
AI/Deep Learning Training and Inference
Large Language Model (LLM) and Generative AI39 728.66 € -
SuperServer SYS-420GH-TNGR
Purpose Built for AI/Deep Learning Training
Computer Vision
Natural Language Processing
Recommendation45 147.45 € -
GPU SuperServer SYS-1029GP-TR
2D/3D and CAD Applications
Astrophysics, Chemistry
Cloud and Virtualization3 750.61 €
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.