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Hosted AI and Deep Learning Dedicated Server
GPUs can offer significant speedups over CPUs when it comes to training deep neural networks. We provide bare metal servers with GPUs that are specifically designed for deep learning and AI purposes.
P1000 is a good choice for Android Emulators, gaming, video editing, OBS streaming, and drawing workstations.
Starting at
$64.00
/month
T1000 is a good choice for Android Emulators, gaming, video editing, OBS streaming, 3D modeling, drawing workstations.
Starting at
$99.00
/month
For high-performance computing and large data workloads, such as deep learning and AI reasoning.
Starting at
$109.00
/month
For high-performance computing and large data workloads, such as deep learning and AI reasoning.
Starting at
$159.00
/month
RTX A4000 delivers real-time ray tracing, AI accelerated computing, and high-performance graphics to desktops.
RTX A5000 achieves an excellent balance between function, performance, and reliability. Assist designers, engineers, and artists to realize their visions.
Starting at
$269.00
/month
Accelerate data science and computation-based workloads. A40 is very suitable for AI and deep learning projects.
Starting at
$369.00
/month
V100 server is a cloud product that can accelerate for more than 600 HPC applications and various deep learning frameworks.
Starting at
$369.00
/month
6 Reasons to Choose our GPU Servers for Deep Learning
DBM enables powerful GPU hosting features on raw bare metal hardware, served on-demand. No more inefficiency, noisy neighbors, or complex pricing calculators.
Intel Xeon CPU
Intel Xeon has extraordinary processing power and speed, which is very suitable for running deep learning frameworks. So you can totally use our Intel-Xeon-powered GPU servers for deep learning and AI.
SSD-Based Drives
You can never go wrong with our own top-notch dedicated GPU servers for PyTorch, loaded with the latest Intel Xeon processors, terabytes of SSD disk space, and 128 GB of RAM per server.
Full Root/Admin Access
With full root/admin access, you will be able to take full control of your dedicated GPU servers for deep learning very easily and quickly.
99.9% Uptime Guarantee
With enterprise-class data centers and infrastructure, we provide a 99.9% uptime guarantee for hosted GPUs for deep learning and networks.
Dedicated IP
One of the premium features is the dedicated IP address. Even the cheapest GPU dedicated hosting plan is fully packed with dedicated IPv4 & IPv6 Internet protocols.
DDoS Protection
Resources among different users are fully isolated to ensure your data security. DBM protects against DDoS from the edge fast while ensuring legitimate traffic of hosted GPUs for deep learning is not compromised.
How to Choose the Best GPU Servers for Deep Learning
When you are choosing GPU servers for deep learning, the following factors should be considered.
Performance
The higher the floating-point computing capability of the graphics card, the higher the arithmetic power that deep learning, and scientific computing use.
Memory Capacity
Large memory can reduce the number of times to read data and reduce latency.
Memory Bandwidth
GPU memory bandwidth is a measure of the data transfer speed between a GPU and the system across a bus, such as PCI Express (PCIe) or Thunderbolt. It's important to consider the bandwidth of each GPU in a system when developing your high-performance Metal apps.
RT Core
RT Cores are accelerator units that are dedicated to performing ray tracing operations with extraordinary efficiency. Combined with NVIDIA RTX software, RT Cores enable artists to use ray-traced rendering to create photorealistic objects and environments with physically accurate lighting.
Tensor Cores
Tensor Cores enable mixed-precision computing, dynamically adapting calculations to accelerate throughput while preserving accuracy.
Budget Price
We offer many cost-effective GPU server plans on the market, so you can easily find a plan that fits your business needs and is within your budget.
TensorFlow is an open-source library developed by Google primarily for deep learning applications. It also supports traditional machine learning.
The Jupyter Notebook is a web-based interactive computing platform. It allows users to compile all aspects of a data project in one place making it easier to show the entire process of a project to your intended audience.
PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing. It provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration, Deep neural networks built on a tape-based autograd system.
Keras is a high-level, deep-learning API developed by Google for implementing neural networks. It is written in Python and is used to implement neural networks easily. It also supports multiple backend neural network computations.
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is written in C++, with a Python interface.
Theano is a Python library that allows us to evaluate mathematical operations including multidimensional arrays so efficiently. It is mostly used in building Deep Learning Projects.
Leave us a note when purchasing, or contact us to apply a trial GPU server. You have enough time to test the performance, network latency, compatibility, multiple instance capacity, etc.
Contact Us$20 will be credited to your account once you recommend a new client to purchase servers. Rewards can be superimposed.
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