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GPU Server

A GPU server, also known as a GPU-accelerated server, is a type of server that is equipped with one or more Graphics Processing Units (GPUs). GPUs are specialized hardware components primarily designed for rendering graphics and performing parallel processing tasks. However, their capabilities extend beyond graphics processing and can be leveraged for various compute-intensive workloads..

CPU RAM Storage GPU Data Transfer Data Center Monthly Price
Intel® Xeon® E3 1220v5 8 GB 1 TB SATA 3 or 240 GB SSD GF GT 710 1 GB 1 Gbps unmetered France $70 ORDER NOW
Intel® Core i3 8100 8 GB 1 TB SATA 3 Intel Graphics UHD 630 1 Gbps unmetered France $90 ORDER NOW
Quad-Core Xeon E3-1230 16GB RAM 120GB + 960GB SSD Nvidia GeForce GT710 100Mbps Dallas $110 ORDER NOW
Intel Xeon E3-1284L v3 Quad Core 1.80 GHz 8 GB​ SATA-SSD 480 GB Intel Iris Pro 5200 300 Mbps Unmetered New York $115 ORDER NOW
Quad-Core Xeon E3-1270v3 16GB RAM 120GB + 960GB SSD Nvidia Quadro K620 100Mbps Denver $115 ORDER NOW
Quad-Core Xeon E5-2643 32GB RAM 120GB + 960GB SSD Nvidia Quadro P600 100Mbps Kansas City $125 ORDER NOW
Intel Xeon E3-1284L v4 Quad Core 2.90 GHz ​16 GB SATA-SSD 240 GB Intel Iris Pro P6300 300 Mbps Unmetered New York $135 ORDER NOW
Core i3-9350KF 4.0GHz (4 cores) 64 GB 10Tb free (1Gbps) GTX 1080Ti+ASMB9-IKVM 10Tb free (1Gbps) Netherland $378 ORDER NOW
2 x Intel Xeon L5640 Hex Core 2.26 GHz ​32 GB SATA 250 GB NVIDIA GeForce GTX 1080 2560 CUDA Cores 300 Mbps Unmetered Bucharest $380 ORDER NOW
CPU : 8core 32GB 250GB SSD NVIDIA Tesla M40 12GB*1 10 Mbps Seoul $402 ORDER NOW
AMD Ryzen 9 5900X 3.7GHz (12 cores) ​32GB 500Gb NVMe SSD ​RTX 3080+PSU 700W 10Tb free (1Gbps) Moscow $450 ORDER NOW
Intel Xeon E5-2630L v2 Hex Core 2.40 GHz ​ 64 GB 2 x SATA-SSD 120 GB NVIDIA GeForce GTX 1070 1920 CUDA Cores 300 Mbps Unmetered Bucharest $450 ORDER NOW
Xeon E-2288G 3.7GHz (8 cores) 32 GB 10Tb free (1Gbps) 1 × RTX A4000 10Tb free (1Gbps) Netherland $480 ORDER NOW

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Types of GPU Servers

There are different types of GPU servers available, designed to cater to various use cases and performance requirements. Here are some common types of GPU servers:

  • Single-GPU Servers: These servers are equipped with a single GPU, making them suitable for entry-level or small-scale GPU computing needs. They are often used for tasks such as basic AI inference, desktop virtualization, or small-scale data analytics.
  • Multi-GPU Servers: Multi-GPU servers are designed to accommodate multiple GPUs within a single server chassis. They can range from servers with two or four GPUs to high-density servers with dozens or even hundreds of GPUs. Multi-GPU servers offer increased computational power and are suitable for more demanding workloads, such as deep learning model training, large-scale data processing, and scientific simulations.
  • High-Performance Computing (HPC) Servers: HPC servers are specifically designed for intensive computational tasks. They typically feature multiple high-end GPUs optimized for parallel computing. HPC servers are used in scientific research, weather modeling, molecular dynamics simulations, computational fluid dynamics, and other applications that require massive parallel processing capabilities.
  • AI Training Servers: AI training servers are purpose-built for training large-scale deep learning models. They feature multiple high-performance GPUs, optimized memory configurations, and fast interconnects to handle the data-intensive nature of AI training workloads. These servers enable faster model convergence and reduced training time for AI applications.
  • AI Inference Servers: AI inference servers are designed for deploying trained deep learning models and performing real-time inference tasks. They typically feature GPUs optimized for inference workloads, with lower power consumption and reduced memory requirements compared to training-focused GPUs. AI inference servers are used in applications such as computer vision, natural language processing, recommendation systems, and speech recognition.

Features of GPU Servers

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Powerful GPU Acceleration

GPU servers leverage high-performance Graphics Processing Units (GPUs) to accelerate compute-intensive tasks, delivering significantly faster processing times compared to traditional CPU-based servers.

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Enhanced Parallel Processing

GPUs are designed for parallel processing, enabling simultaneous execution of multiple tasks or data streams. This feature makes GPU servers highly efficient for workloads that can be parallelized, such as AI training, scientific simulations, and data analytics.

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Deep Learning and AI Capabilities

GPU servers are essential for deep learning and AI applications. They provide the computational power required for training complex neural networks, accelerating model convergence, and enabling faster inference for real-time AI applications.

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Specialized GPU Software Ecosystem

GPU servers benefit from a robust software ecosystem, including GPU-accelerated libraries, frameworks, and programming languages. This ecosystem, often provided by GPU manufacturers such as NVIDIA, facilitates development, optimization, and deployment of GPU-accelerated applications.

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Virtualization and GPU Sharing

Some GPU servers support virtual GPU (vGPU) technology, allowing efficient GPU sharing among multiple virtual machines (VMs). This feature enables virtual desktop infrastructure (VDI) and GPU-accelerated cloud services, optimizing resource utilization and enabling cost-effective deployments.

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Advanced Cooling and Power Management

GPU servers incorporate specialized cooling mechanisms and power management systems to handle the higher power requirements and heat generation of GPUs. These features ensure optimal performance, reliability, and energy efficiency.

GPU Server FAQs

What is a GPU server?

A GPU server is a type of server equipped with powerful Graphics Processing Units (GPUs) that accelerate compute-intensive tasks, such as AI training, deep learning, scientific simulations, and data analytics.

How does a GPU server differ from a CPU server?

While traditional CPU servers are designed for general-purpose computing, GPU servers leverage the parallel processing capabilities of GPUs to deliver significantly faster performance for tasks that can be parallelized, making them ideal for AI, ML, and computationally intensive workloads.

What are the benefits of using a GPU server?

GPU servers offer enhanced compute performance, faster data processing, accelerated AI training, and improved simulation capabilities. They enable organizations to achieve faster insights, train complex models, and handle large-scale data processing with higher efficiency.

Which industries benefit from GPU servers?

GPU servers are widely used in industries such as AI research, machine learning, deep learning, data science, autonomous vehicles, healthcare imaging, finance, scientific research, and gaming. They empower organizations to tackle complex computational challenges and drive innovation

What types of GPU configurations are available?

GPU servers come in various configurations, ranging from single-GPU servers to high-density servers with multiple GPUs. The choice depends on workload requirements, budget, and scalability needs. Some servers support mixed GPU configurations to cater to diverse workload demands.

Can GPU servers be used for AI inference?

Yes, GPU servers are suitable for AI inference as well. They can efficiently deploy trained deep learning models and perform real-time inference tasks, enabling applications such as computer vision, natural language processing, recommendation systems, and speech recognition.

Can GPU servers be virtualized?

Yes, many GPU servers support virtual GPU (vGPU) technology, allowing GPU sharing and virtualization. This enables the efficient utilization of GPU resources, making GPU-accelerated virtual desktop infrastructure (VDI) and cloud services possible.

What is the software ecosystem for GPU servers?

GPU servers benefit from a robust software ecosystem provided by GPU manufacturers, such as NVIDIA's CUDA platform and libraries like cuDNN and TensorRT. These tools facilitate GPU-accelerated application development, optimization, and deployment.

Are GPU servers suitable for small businesses or startups?

GPU servers can benefit small businesses and startups by providing cost-effective access to powerful compute resources. Cloud-based GPU instances and GPU-as-a-Service offerings make it easier for smaller organizations to leverage GPU acceleration without upfront hardware investments.