Dedicated Server Hosting with NVIDIA Tesla GPU

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What Can Be Run on Tesla GPU Hosting Servers

The Tesla accelerator provides a powerful foundation for customers to leverage best-in-class software and solutions for deep learning.
Caffe
Chainer
DL4J
julia
Keras
MatConvNet
CNTK
mxnet
OpenDeep
TensorFlow
theano
torch

When to choose a Tesla GPU Hosting

Here are the most use cases on dedicated servers with Tesla GPU.

AI and Deep Learning projects

The Nvidia Tesla K80 is a server solution from 2014. It has 24 GB of RAM split between 2 cards and a 2946 CUDA core, and all this is great for AI and Deep Learning projects.

AI

HPC and Data Analytics

Count on NVIDIA Tesla K40 GPU Accelerators to solve your most demanding HPC and big-data challenges. They feature 1.4 TFLOPS performance, 12 GB memory, and ultra-fast 288 GB/s throughput, giving you the power to process large datasets while delivering up to 10X acceleration compared to CPUs.

Data Analytics

Tesla GPUs Specifications & Performance

Tesla GPU hosting servers make your entire PC experience beyond fast.
Specs K80 K40c M40 A30 PCIe A40 PCIe A100 SXM4 80 GB V100 PCIe 16 GB
GPU Architecture Kepler 2.0 Kepler Maxwell 2.0 Ampere Ampere Ampere Volta
CUDA Cores 4992 2880 3072 3584 10752 6912 5120
Core clock speed 562 MHz 745 MHz 948 MHz 930 MHz 1305 MHz 1275 MHz 1246 MHz
Boost clock speed 824 MHz 876 MHz 1114 MHz 1440 MHz 1740 MHz 1410 MHz 1380 MHz
FP16 performance -- -- -- 10.32 TFLOPS 37.42 TFLOPS 77.97 TFLOPS 28.26 TFLOPS
FP32 performance 8.73 TFLOPS 5.05 TFLOPS 6.84 TFLOPS 10.32 TFLOPS 37.42 TFLOPS 19.49 TFLOPS 14.13 TFLOPS
FP64 performance 2.91 TFLOPS 1.68 TFLOPS 0.21 TFLOPS 5.161 TFLOPS 0.58 TFLOPS 9.746 TFLOPS 7.07 TFLOPS
Memory 24GB GDDR5 with ECC 12GB GDDR5 12 GB GDDR5 24 GB HBM2e 48 GB GDDR6 with ECC 80 GB HBM2e 16 GB HBM2
Memory Bandwidth 480 GB/s 288 GB/s 288 GB/s 933.1 GB/s 696 GB/s 2039 GB/s 900 GB/s
Memory Bus Width 384 bit 384 bit 384 bit 3072 bit 384 bit 5120 bit 4096 Bit
Memory Clock Speed 5012 MHz 6008 MHz 6008 MHz 1215 MHz 1812 MHz 1593 MHz 1758 MHz
TDP 300W 230W 250W 165W 300W 400W 250W
System Interface PCIe 3.0x16 PCIe 3.0x16 PCIe 3.0x16 PCIe 4.0 x16 PCIe 4.0 x16 PCIe 4.0 x16 PCIe 3.0 x16
DirectX 12 (11_1) 12 (11_0) 12 (12_1) N/A 12 (12_2) N/A 12.0
Shader Model 5.1 5.1 6.4 N/A 6.7 N/A 5.0
OpenGL 4.6 4.6 4.6 N/A 4.6 N/A 4.6
OpenCL 1.2 1.2 1.2 3.0 3.0 3.0 2.0
CUDA 3.7 3.5 5.2 8.0 8.6 8.0 7.0
Outputs No outputs No outputs No outputs No outputs 3x DisplayPort 1.4a No outputs No outputs
Release date Nov 17th, 2014 Oct 8th, 2013 Nov 10th, 2015 Apr 12th, 2021 Oct 5th, 2020 Nov 16th, 2020 Jun 21st, 2017

Performance

What Nvidia is happy to talk about is the growing gap in floating point performance and memory bandwidth between CPUs and Nvidia Tesla series GPU cards, which is illustrated on the left. Thus far, over 280 applications in modeling, simulation, data analytics, machine learning, and other workloads have been ported to the CUDA environment so Nvidia Tesla series cards can accelerate them.

Performance

GPU Features in NVIDIA Tesla GPU Hosting Server

Hosted dedicated servers with Tesla GPU deliver superior performance over integrated graphics.
Massively Multi-threaded Computing Architecture

Massively Multi-threaded Computing Architecture

Executes thousands of concurrent processing threads for high throughput parallel processing of mathematically intensive problems.
NVIDIA GPU Computing Drivers

NVIDIA GPU Computing Drivers

It helps with the management of the GPU resources and an extensive runtime library for enhanced data management and program execution and offers a high-speed data transfer path and streamlined driver for computing, independent of the graphics driver.
Supercomputing Performance

Supercomputing Performance

Peak performance of over 500 gigaflops per GPU on floating point operations in data-intensive applications.
Multi-GPU Computing

Multi-GPU Computing

Multiple Tesla GPUs can be controlled by a single CPU via the GPU computing driver, delivering incredible throughput on computing applications. The power of the GPU to solve large-scale problems can be multiplied by splitting the problem across multiple GPUs.

Dedicated Servers with Tesla GPU Hosting Pricing

Telsa K80/K40 pairs with Intel® Xeon® Processor E5 Family CPU and 64GB+ RAM, delivering high performance for your engineering and HPC applications.
Basic GPU Server

Nvidia Tesla K40

For high-performance computing and large data workloads, such as deep learning and AI reasoning.
GPU: Nvidia Tesla K40
Microarchitecture: Kepler
Max GPU: 2
CUDA Cores: 2880
GPU Memory: 12GB
Performance: 4.29 TFLOPS
64 GB RAM
Eight-Core Xeon E5-2670
120GB SSD + 960GB SSD
100Mbps-1Gbps Bandwidth
Supported OS: Windows & Linux
24M
12M
3M
1M

$109.00/m

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$115.00/m

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$119.00/m

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$129.00/m

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Professional GPU Server

Nvidia Tesla K80

For high-performance computing and large data workloads, such as deep learning and AI reasoning.
GPU: Nvidia Tesla K80
Microarchitecture: Kepler
Max GPU: 2
CUDA Cores: 4992
GPU Memory: 24GB
Performance: 8.73 TFLOPS
128 GB RAM
Dual 10-Core E5-2660v2
120GB SSD + 960GB SSD
100Mbps-1Gbps Bandwidth
Supported OS: Linux & Windows
24M
12M
3M
1M

$159.00/m

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$179.00/m

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$189.00/m

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$199.00/m

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Enterprise GPU Server

Nvidia A40

Accelerate data science and computation-based workloads. A40 is very suitable for AI and deep learning projects.
GPU: Nvidia A40
Microarchitecture: Ampere
Max GPU: 1
CUDA Cores: 10,752
Tensor Cores: 336
GPU Memory: 48GB
Performance: 37.4 TFLOPS
256 GB RAM
Dual E5-2697v4
240GB SSD + 2TB SSD + 2TB NVMe
100Mbps-1Gbps Bandwidth
Supported OS: Linux & Windows 10
24M
12M
3M
1M

$369.00/m

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$419.00/m

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$459.00/m

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$499.00/m

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Enterprise GPU Server

Nvidia V100

V100 server is a cloud product that can accelerate for more than 600 HPC applications and various deep learning frameworks.
GPU: Nvidia V100
Microarchitecture: Volta
Max GPU: 1
CUDA Cores: 5,120
Tensor Cores: 640
GPU Memory: 16GB
Performance: 14 TFLOPS
256 GB RAM
Dual E5-2697v4
240GB SSD + 2TB SSD + 2TB NVMe
100Mbps-1Gbps Bandwidth
Supported OS: Linux & Windows 10
24M
12M
3M
1M

$369.00/m

Order Now

$419.00/m

Order Now

$459.00/m

Order Now

$499.00/m

Order Now

Alternatives to Dedicated Servers with Tesla GPU

If you want to do image rendering, video editing, or play games, these would be better alternatives.
RTX A5000 Hosting

RTX A5000 Hosting

Achieve an excellent balance between function, performance, and reliability. Assist designers, engineers, and artists to realize their visions.

Learn More
RTX 3060 Ti Hosting

RTX 3060 Ti Hosting

For professionals. It delivers real-time ray tracing, AI accelerated computing, and high-performance graphics to desktops.

Learn More
Geforce GT 730 Hosting

Geforce GT 730 Hosting

Mainly suitable for home games and Android emulators, such as BlueStacks and MEmu Play.

Learn More

FAQ of NVIDIA Tesla Series Hosting

Answers to more questions about the Tesla GPU cards can be found here.

Is the Tesla GPU hosting server self-managed?

Yes, but our experienced staff is always here and willing to help you with any problems you have with your rental GPU dedicated server. Please reach us online in a live chat or in an email if you need help

How long will it take to set up GPU dedicated servers with Tesla GPU?

We usually need 24-48 hours for preparing a GPU dedicated server.

What is NVIDIA Tesla series?

NVIDIA Tesla was the name of Nvidia's line of products. The Nvidia Tesla series is targeted at stream processing or general-purpose graphics processing units (GPGPU), named after pioneering electrical engineer Nikola Tesla. Its products began using GPUs from the G80 series, and have continued to accompany the release of new chips.

What are NVIDIA Tesla GPU servers used for?

NVIDIA Tesla is a line of GPU accelerator boards optimized for high-performance, general-purpose computing. Tesla GPUs are used for parallel scientific, engineering, and technical computing, and they are designed for deployment in supercomputers, clusters, and workstations.

Can NVIDIA Tesla GPU hosting server be used for gaming?

Tesla GPU servers are designed for High-Performance Computing (HPC) and are aimed at an enterprise market. Therefore, gaming isn't exactly the plug-n-play experience of NVIDIA's consumer line. For starters, the K80 doesn't have IO to output to a display where you need to use either motherboard graphics or another GPU as your display adapter. Even then, the Tesla needs to be configured with specialized software. However, if you don't already own one, buy a RTX 2060 instead.

Are NVIDIA Tesla GPU hosting servers good for rendering?

NVIDIA Tesla GPU servers will render Blender scenes just fine. Though for just rendering, you might not see much of an advantage since the Tesla's main benefit is its ability to do double-precision floating point numbers quickly (Blender only uses single precision).

Are NVIDIA Tesla GPU hosting servers good for video editing?

NVIDIA Tesla GPUs are not your ordinary graphics cards -- they won't work for video editing. They have one job, and that is computing (number crunching), high-precision computing to the 17th decimal place. These cards DO NOT have any output ports on them -- you cannot connect any monitors to them.

Can you use a Tesla k80 server for Premiere Pro?

The NVIDIA Tesla GPU server is designed for data centers and extreme computing applications, such as web servers. It isn't the right kind of card for what you intend to use it for. Even if you could, they can only accelerate GPUs on the Kepler architecture (as in Geforce 600 and 700 series) and certainly not integrated graphics or discrete graphics cards from any other architecture.
For this, a standard consumer GPU (especially with Nvidia's CUDA cores) will do fine for Adobe applications, especially something from the 16/20/30 series for their H.265 encoding compatibility. an RTX 3070 can chew through 10 minutes of 4K video, rendering it in about 15-20 minutes, often less.

Can I use a Tesla K80 server for rendering with Blender?

Yes, you can. But if you're planning to use it at home or in an office environment, you should take into account the fact that the K80 boards are built for a data center environment. They don't have video output, so you'll need a secondary graphics card to connect your monitor.
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