Nvidia GPU Cluster for Deep Learning and HPC

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Hot Deals

Rent HPC GPU Servers for Building Your GPU Cluster

Looking to create a powerful GPU cluster? Rent HPC GPU servers from us and supercharge your computing capabilities now!

Black Friday Sale

Advanced GPU Dedicated Server - A4000

$ 89.28/mo

68% OFF Recurring (Was $279.00)

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128GB RAM
GPU: Nvidia Quadro RTX A4000
Dual 12-Core E5-2697v2
240GB SSD + 2TB SSD
100Mbps-1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 6144
Tensor Cores: 192
GPU Memory: 16GB GDDR6
FP32 Performance: 19.2 TFLOPS

Special 3-Year Billing — Fix your rate and enjoy savings longer.

Advanced GPU Dedicated Server - V100

$ 229.00/mo

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128GB RAM
GPU: Nvidia V100
Dual 12-Core E5-2690v3
240GB SSD + 2TB SSD
100Mbps-1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Volta
CUDA Cores: 5,120
Tensor Cores: 640
GPU Memory: 16GB HBM2
FP32 Performance: 14 TFLOPS

Black Friday Sale

Advanced GPU Dedicated Server - A5000

$ 150.07/mo

57% OFF Recurring (Was $349.00)

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128GB RAM
GPU: Nvidia Quadro RTX A5000
Dual 12-Core E5-2697v2
240GB SSD + 2TB SSD
100Mbps-1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 8192
Tensor Cores: 256
GPU Memory: 24GB GDDR6
FP32 Performance: 27.8 TFLOPS

Enterprise GPU Dedicated Server - RTX 4090

$ 409.00/mo

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256GB RAM
GPU: GeForce RTX 4090
Dual 18-Core E5-2697v4
240GB SSD + 2TB NVMe + 8TB SATA
100Mbps-1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ada Lovelace
CUDA Cores: 16,384
Tensor Cores: 512
GPU Memory: 24 GB GDDR6X
FP32 Performance: 82.6 TFLOPS

Black Friday Sale

Enterprise GPU Dedicated Server - RTX A6000

$ 247.04/mo

55% OFF Recurring (Was $549.00)

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256GB RAM
GPU: Nvidia Quadro RTX A6000
Dual 18-Core E5-2697v4
240GB SSD + 2TB NVMe + 8TB SATA
100Mbps-1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 10,752
Tensor Cores: 336
GPU Memory: 48GB GDDR6
FP32 Performance: 38.71 TFLOPS

Enterprise GPU Dedicated Server - A40

$ 409.00/mo

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256GB RAM
GPU: Nvidia A40
Dual 18-Core E5-2697v4
240GB SSD + 2TB NVMe + 8TB SATA
100Mbps-1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 10,752
Tensor Cores: 336
GPU Memory: 48GB GDDR6
FP32 Performance: 37.48 TFLOPS

Multi-GPU Dedicated Server - 3xV100

$ 469.00/mo

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256GB RAM
GPU: 3 x Nvidia V100
Dual 18-Core E5-2697v4
240GB SSD + 2TB NVMe + 8TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Volta
CUDA Cores: 5,120
Tensor Cores: 640
GPU Memory: 16GB HBM2
FP32 Performance: 14 TFLOPS

Multi-GPU Dedicated Server - 3xRTX A5000

$ 539.00/mo

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256GB RAM
GPU: 3 x Quadro RTX A5000
Dual 18-Core E5-2697v4
240GB SSD + 2TB NVMe + 8TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 8192
Tensor Cores: 256
GPU Memory: 24GB GDDR6
FP32 Performance: 27.8 TFLOPS

Black Friday Sale

Enterprise GPU Dedicated Server - A100

$ 399.20/mo

50% OFF Recurring (Was $799.00)

1mo3mo12mo24mo

Order Now

256GB RAM
GPU: Nvidia A100
Dual 18-Core E5-2697v4
240GB SSD + 2TB NVMe + 8TB SATA
100Mbps-1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 6912
Tensor Cores: 432
GPU Memory: 40GB HBM2
FP32 Performance: 19.5 TFLOPS

Multi-GPU Dedicated Server- 2xRTX 4090

$ 729.00/mo

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256GB RAM
GPU: 2 x GeForce RTX 4090
Dual 18-Core E5-2697v4
240GB SSD + 2TB NVMe + 8TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ada Lovelace
CUDA Cores: 16,384
Tensor Cores: 512
GPU Memory: 24 GB GDDR6X
FP32 Performance: 82.6 TFLOPS

Multi-GPU Dedicated Server - 3xRTX A6000

$ 899.00/mo

1mo3mo12mo24mo

Order Now

256GB RAM
GPU: 3 x Quadro RTX A6000
Dual 18-Core E5-2697v4
240GB SSD + 2TB NVMe + 8TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 10,752
Tensor Cores: 336
GPU Memory: 48GB GDDR6
FP32 Performance: 38.71 TFLOPS

Black Friday Sale

Multi-GPU Dedicated Server- 2xRTX 5090

$ 659.40/mo

40% OFF Recurring (Was $1099.00)

1mo3mo12mo24mo

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256GB RAM
GPU: 2 x GeForce RTX 5090
Dual E5-2699v4
240GB SSD + 2TB NVMe + 8TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Blackwell 2.0
CUDA Cores: 21,760
Tensor Cores: 680
GPU Memory: 32 GB GDDR7
FP32 Performance: 109.7 TFLOPS

This is a pre-sale product. Delivery will be completed within 2–10 days after payment.

Multi-GPU Dedicated Server - 4xRTX A6000

$ 1199.00/mo

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512GB RAM
GPU: 4 x Quadro RTX A6000
Dual 22-Core E5-2699v4
240GB SSD + 4TB NVMe + 16TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 10,752
Tensor Cores: 336
GPU Memory: 48GB GDDR6
FP32 Performance: 38.71 TFLOPS

Multi-GPU Dedicated Server - 4xA100

$ 1899.00/mo

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Order Now

512GB RAM
GPU: 4 x Nvidia A100
Dual 22-Core E5-2699v4
240GB SSD + 4TB NVMe + 16TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 6912
Tensor Cores: 432
GPU Memory: 40GB HBM2
FP32 Performance: 19.5 TFLOPS

Multi-GPU Dedicated Server - 8xRTX A6000

$ 2099.00/mo

1mo3mo12mo24mo

Order Now

512GB RAM
GPU: 8 x Quadro RTX A6000
Dual 22-Core E5-2699v4
240GB SSD + 4TB NVMe + 16TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 10,752
Tensor Cores: 336
GPU Memory: 48GB GDDR6
FP32 Performance: 38.71 TFLOPS

New Arrival

Multi-GPU Dedicated Server - 8xA100

$ 3399.00/mo

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Order Now

512GB RAM
GPU: 8 x Nvidia A100
Dual 22-Core E5-2699v4
240GB SSD + 4TB NVMe + 16TB SATA
1Gbps
OS: Windows / Linux

Single GPU Specifications:
Microarchitecture: Ampere
CUDA Cores: 6912
Tensor Cores: 432
GPU Memory: 40GB HBM2
FP32 Performance: 19.5 TFLOPS

What's GPU Cluster?

GPU cluster typically refers to a collection of interconnected computers, each equipped with one or more GPUs, working together as a unified system. These systems often run on specialized software, such as HPC (High-Performance Computing) clusters, which facilitate distributed computing tasks. Clusters are generally designed for diverse workloads and research projects, where individual nodes can be dedicated to specific tasks or run different parts of a larger computation concurrently. They often operate within a managed environment, offering advanced scheduling and resource management capabilities.

There are three main advantages of GPU cluster:

High availability

The GPU cluster reroutes requests to different nodes in the event of a failure.

High performance

The GPU cluster uses multiple parallel slave nodes to increase compute power for more demanding tasks.

Load balancing

The GPU cluster spreads compute workloads evenly across slave nodes to handle a large volume of jobs.

How to Choose GPU Cluster Hosting

Choosing a GPU cluster hosting provider requires careful consideration of several factors to ensure that it meets your specific needs for performance, scalability, and cost-effectiveness. Here are some key points to consider:

Hardware Specifications

Verify the types of GPUs offered (e.g., NVIDIA A100, V100, RTX 4090). Ensure they are suitable for your workload, whether it be deep learning, rendering, or scientific computing.

Scalability

Check if the provider allows you to scale up or down based on your project needs. Ensure the provider can handle the scale of your projects, from small tests to large-scale deployments.

Network and Connectivity

High-speed internet and low-latency network connections are crucial for transferring large datasets and ensuring efficient GPU communication.

Software and Compatibility

Look for providers that offer pre-installed and optimized software for your specific needs. Ensure you can install and configure your own software as needed.

Cost and Pricing Model

Understand the pricing model and compare the cost relative to the performance and capabilities offered. Look for any hidden fees.

Customer Support

Ensure there is 24/7 customer support available to assist with any issues. Check the uptime guarantees and reliability promises made by the provider.

Accelerated Computation

GPU clusters can process large datasets quickly, making them suitable for tasks like image and video processing, big data analytics, and more.

Scalability

Multiple GPUs can be pooled together to tackle large computational problems, allowing for efficient use of resources.

Cost Efficiency

Faster computation times mean projects can be completed more quickly, reducing overall costs.

Improved Reliability and Redundancy

High-quality GPU clusters often include features for fault tolerance and redundancy, ensuring that tasks can continue to run smoothly even if some components fail.

Benefits of Using GPU Cluster

Using a GPU cluster provides numerous benefits, particularly for tasks that require significant computational power such as deep learning, scientific simulations, and 3D rendering. Here are some key benefits of using a GPU cluster:

GPU Cluster vs GPU Farm

Features	GPU Cluster	GPU Farm
Architecture	Simple, concise, readable	Not easy to use
Nodes	Highly integrated, tightly interconnected GPU nodes	Distributed, independent GPU computing resources
Management	Unified management system (such as Slurm, Kubernetes)	Batch processing system or cloud management platform
Interconnection	High-speed network interconnection	General network interconnection
Task type	Highly parallel computing tasks, such as scientific computing and deep learning training	Distributed rendering, data mining, batch processing tasks
Scalability	Easy to expand by adding nodes	More independent GPUs can be added, but there may be no cluster coordination
Typical applications	Supercomputing centers, technology companies	Animation studios, video production companies

Faqs of Nvidia GPU Clusters

Frequently Asked Questions about Nvidia Clusters (GPU-Enabled Clusters)

What is Nvidia cluster?

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An NVIDIA cluster refers to a group of computers or servers that are networked together and equipped with NVIDIA GPUs (Graphics Processing Units) to perform high-performance computing tasks.

How to build a GPU cluster?

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Building a GPU cluster involves several steps, from planning the hardware and network infrastructure to configuring the software and deploying the system.

What are A100 clusters used for?

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NVIDIA A100 clusters are used for a wide range of high-performance computing (HPC) applications due to their exceptional processing power, memory bandwidth, and versatility.

When do you need to build a GPU cluster for AI?

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Building a GPU cluster for AI can provide significant benefits when you have specific computational needs that exceed the capabilities of individual GPUs or standard computing environments. It is beneficial when dealing with large-scale, complex models and datasets, requiring scalable and efficient computational resources. It supports high-throughput, real-time applications, and enables cutting-edge research and rapid development.

What is the difference between HPC cluster and GPU cluster?

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In HPC clusters, CPUs are ideally suited for serial instruction processing. GPUs are not suitable for serial instruction processing, and slow down algorithms requiring serial execution compared to CPUs. CPUs come with large local cache memory which empowers them to handle multiple sets of linear instructions.

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Contact us now to learn more about our GPU cluster, and let our high-performance GPU solutions propel your business forward!

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