GPU Servers for AI Workloads

GPU (Graphics Processing Unit) servers are essential for handling AI (Artificial Intelligence) workloads efficiently.

GPU Servers

GPU (Graphics Processing Unit) servers are specialized servers equipped with one or more high-performance GPUs

AI_HOST 4 x H100

AI_HOST 8 x A100

Enterprise GPU AI-1

Enterprise GPU AI-2

GPU 4 x NVIDIA H100 SXM5 NVLink 8 x NVIDIA A100 80GB 1 x Geoforce RTX 4090 24G OC 2 x Geoforce RTX 4090 24G OC
Processor Intel Xeon Gold 6430 Processor 32-Core 2.10 GHz AMD EPYC 7313 100-000000329 EPYC Milan 16 Core 3.0 GHz Ryzen Threadripper PRO 5965WX, 24 Cores Ryzen Threadripper PRO 5965WX, 24 Cores
RAM 512 GB DDR5 1 TB DDR4 64GB DDR4 128GB DDR4
Storage 2 x 960 GB NVMe 2 x 960 GB NVMe 2 x 960 GB NVMe 2 x 960 GB NVMe
Bandwidth 10 GigE unmetered 10 GigE unmetered -- --
CPU 16 Cores 3.0 Ghz 32 T 16 Cores 3.0 Ghz 32 T 24 Cores / hreads 3.8Ghz 48 Threads 24 Cores / 48 Threads 3.8Ghz

AI Workload GPU Servers

Unlock the potential of AI with our dedicated GPU servers. Harness the immense computational power of GPUs to accelerate your AI workloads, from machine learning to deep learning, and experience faster, more efficient data processing.

Enterprise GPU AI-1

$699
/Month

Enterprise GPU AI-2

$999
/Month

Enterprise GPU AI-3

$1699
/Month

Enterprise GPU AI-3

$1699
/Month

AI Workloads that Benefit from GPU Servers

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Image and Video Processing

AI-driven image recognition, video analysis, and computer vision tasks heavily rely on GPUs for real-time processing and accuracy.

Natural Language Processing (NLP)

NLP models, such as BERT and GPT-3, require significant computational resources for training and fine-tuning. GPUs speed up this process.

Autonomous Vehicles

Self-driving cars depend on AI algorithms for perception and decision-making. GPUs are crucial for processing data from sensors and making split-second decisions.

Healthcare and Drug Discovery

AI assists in diagnosing diseases, drug discovery, and genomics. GPUs enable researchers to process vast datasets and run simulations efficiently.

Financial Modeling

AI is used for risk assessment, fraud detection, and algorithmic trading in the financial sector. GPUs accelerate data analysis and predictive modeling.

Scalability

As your AI projects grow, our scalable solutions let you add more GPUs or resources to accommodate increased workloads.

AI Workloads that Benefit from GPU Servers

Start your hosting journey with AiHost and discover the difference. We’re dedicated to delivering seamless, reliable hosting services that will keep you with us for the long term. Join us today, and let’s build your online future together.

Image and Video Processing

AI-driven image recognition, video analysis, and computer vision tasks heavily rely on GPUs for real-time processing and accuracy.

Natural Language Processing (NLP)

NLP models, such as BERT and GPT-3, require significant computational resources for training and fine-tuning. GPUs speed up this process.

Autonomous Vehicles

Self-driving cars depend on AI algorithms for perception and decision-making. GPUs are crucial for processing data from sensors and making split-second decisions.

Healthcare and Drug Discovery

AI assists in diagnosing diseases, drug discovery, and genomics. GPUs enable researchers to process vast datasets and run simulations efficiently.

Financial Modeling

AI is used for risk assessment, fraud detection, and algorithmic trading in the financial sector. GPUs accelerate data analysis and predictive modeling.

Scalability

As your AI projects grow, our scalable solutions let you add more GPUs or resources to accommodate increased workloads.

The Role of GPUs in AI: Unleashing Computational Power

At the heart of AI’s success lies the Graphics Processing Unit (GPU). GPUs, originally designed for rendering graphics in gaming, have emerged as the workhorses of AI computing. These specialized processors excel at handling the intense computational work required for training and running AI models. Here’s why GPUs are crucial for AI workloads:
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Applications of GPU Servers

AI and Machine Learning

Training deep neural networks, natural language processing, image recognition, and recommendation systems all benefit from GPU acceleration.

Scientific Research

GPUs enable researchers to run simulations, analyze complex datasets, and model phenomena in fields like physics, chemistry, and astronomy.

Healthcare and Genomics

GPU servers expedite medical imaging, drug discovery, genome sequencing, and disease modeling, advancing healthcare and life sciences.

Finance and Cryptography

GPU servers drive high-frequency trading, risk analysis, portfolio optimization, and cryptographic tasks, ensuring financial security and efficiency.

Redefining Hosting: AI Host's Dedicated Servers Revolutionize the Landscape

Cloud Flexability Combined with GPU Dedicated Servers

  • Flexibility: You can adjust computing resources to match AI workloads, ensuring cost-efficiency.
  • On-Demand Access: Resources are available when needed, eliminating the need for upfront hardware investments.
  • Enhanced Security: Higher security levels protect sensitive AI data and models.
  • High Computing Power: Powerful GPUs accelerate AI model development and complex computations.
  • Optimized for AI: Pre-configured setups reduce setup time and optimize AI model performance.
  • Scalability: Easily expand resources to handle growing AI workloads.
  • Reliability: Dedicated servers offer high uptime, critical for real-time AI applications.
  • Technical Support: Access to comprehensive support for troubleshooting and guidance.

Cloud Flexability Combined with GPU Dedicated Servers

A GPU server, or Graphics Processing Unit server, is a computer system designed specifically to handle tasks that require heavy graphics processing or parallel computing power. GPUs are specialized hardware components that excel at tasks like rendering images, performing complex calculations for scientific simulations, deep learning, machine learning, and cryptocurrency mining. GPU servers are used to accelerate these types of workloads.

Ownership and Location

  • Dedicated GPU Server: This type of server is a physical machine owned or leased by an organization and located in their own data center or a colocation facility. It is entirely dedicated to the organization’s use and managed by their IT team.
  • Cloud-based GPU Server: Cloud GPU servers are virtual instances provided by cloud service providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and others. These instances are hosted in the provider’s data centers and can be rented on-demand.

Resource Scalability

  • Dedicated GPU Server: The resources (including GPUs) on a dedicated server are fixed and typically require a significant upfront investment. Scaling up or down may require purchasing additional hardware or migrating to a different server.
  • Cloud-based GPU Server: Cloud GPU servers offer scalability, allowing users to easily change the number and type of GPUs, CPU cores, and memory based on their current needs. This flexibility can be cost-effective and efficient for variable workloads.

Cost Structure

  • Dedicated GPU Server: Organizations incur fixed costs, including hardware purchase, maintenance, electricity, and space. There may also be costs associated with cooling and data center infrastructure.
  • Cloud-based GPU Server: Users pay for cloud GPU resources on a pay-as-you-go basis. This can be more cost-effective for sporadic or variable workloads because you only pay for what you use, with no upfront hardware costs.

Management and Maintenance

  • Dedicated GPU Server: Organizations are responsible for managing, maintaining, and troubleshooting their dedicated servers. This includes hardware maintenance, software updates, security, and backups.
  • Cloud-based GPU Server: Cloud providers handle the infrastructure maintenance and management, including hardware upkeep, security, and software updates. Users can focus on their workloads without worrying about server maintenance.
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Frequently Asked Questions:

here are some frequently asked questions (FAQs) for AiHost GPU Servers for AI Workloads:
AiHost GPU Servers are dedicated servers equipped with high-performance GPUs designed specifically for handling AI and machine learning workloads.
GPU Servers accelerate AI tasks by performing parallel processing, making them essential for faster model training and inference.
You can access and control your GPU Server remotely using SSH or Remote Desktop, depending on the operating system you choose.
AiHost GPU Servers are secured with firewalls, regular security updates, and intrusion detection systems to protect against threats and attacks.
AiHost provides monitoring tools and performance metrics to help you track GPU usage, resource utilization, and server performance.