Cloud servers with Tesla V100

Accelerate the solution of artificial intelligence, HPC, data science and graphics tasks

Graphics servers with Tesla V100

All graphics servers with Tesla V100 are based on two Intel Xeon Gold 6240 CPUs with a base clock speed of 2.6 GHz and a maximum clock speed with Turbo Boost technology of 3.9 GHz.

Each processor contains two Intel® AVX-512 units and supports Intel® AVX-512 Deep Learning Boost functions. This set of instructions speeds up multiplication and addition operations with reduced accuracy, which are used in many internal cycles of the deep learning algorithm.

Each server has 512 GB of DDR4 ECC Reg 2933 MHz RAM. Local storage with a total capacity of 1920 GB is organized on Intel® solid-state drives, designed specifically for data centers.

GPU Tesla V100

Equipped with 43 thousand Tensor cores, the Tesla V100 is the first accelerator to overcome the performance barrier of 100 tera-operations per second (TOPS) in deep learning tasks. Models that took weeks to train on previous generation systems can now be trained in just a few days. Thanks to such a serious reduction in the time spent on training algorithms, artificial intelligence will help solve completely new problems.

HPC (High Performance Computing) is the fundamental pillar of modern science. From weather forecasting and the creation of new medicines to the search for energy sources, scientists are constantly using large computing systems to model our world and predict events in it. Artificial intelligence expands the capabilities of HPC, allowing scientists to analyze large amounts of data and extract useful information where simulations alone cannot provide a complete picture of what is happening.

The Tesla V100 graphics accelerator is designed to provide a fusion of HPC and artificial intelligence. This is a solution for HPC systems, which will perfectly prove itself both in computing for simulations and data processing for extracting useful information from them. By combining CUDA and Tensor cores in one architecture, a server equipped with Tesla V100 graphics accelerators can replace hundreds of traditional CPU servers, performing traditional HPC and artificial intelligence tasks. Now every scientist can afford a supercomputer that will help in solving the most difficult problems.

Video memory capacity 32 GB
Type of video memory HBM2 (ECC)
Memory bandwidth 900 Gb/s
Tensor cores 640
CUDA cores 5120

GPU performance benchmarks

Performance benchmarks results in a virtual environment for 1 Tesla V100 graphics card.
  • OctaneBench 2020

    up to
    360
    pts
  • Matrix multiply example

    2430
    GFlop/s
  • Hashcat bcrypt

    46 600
    H/s

Basic configurations with Tesla V100 32 GB

Name vCPU RAM, MB Disk, GB GPU Price, hour
teslav100-1.8.64.60 8 65536 60 1 Launch
teslav100-1.8.64.80 8 65536 80 1 Launch
teslav100-1.8.64.160 8 65536 160 1 Launch
teslav100-1.12.64.160 12 65536 160 1 Launch
teslav100-1.16.64.160 16 65536 160 1 Launch
teslav100-1.16.128.160 16 131072 160 1 Launch
teslav100-1.32.128.160 32 131072 160 1 Launch
teslav100-2.32.128.160 32 131072 160 2 Launch
teslav100-2.32.192.160 32 196608 160 2 Launch
teslav100-4.32.64.160 32 65536 160 4 Launch
teslav100-4.32.96.160 32 98304 160 4 Launch
teslav100-4.32.256.160 32 262144 160 4 Launch

100% performance

Each physical core or GPU adapter assigned only to a single client.
It means that:

  • Available vCPU time is 100%
  • Physical pass through of GPU inside a VM
  • Less storage and network load on hypervisors, more storage and network performance for a client.

Up to 75 000 IOPS1 for the RANDOM READ and up to 20 000 IOPS for the RANDOM WRITE for the Virtual Machines with local SSDs.

Up to 22 500 IOPS1 for the RANDOM READ and up to 20 000 IOPS for the RANDOM WRITE for the Virtual Machines with block storage Volumes.

You can be sure that Virtual Machines are not sharing vCPU or GPU among each other.

  1. IOPS — Input/Output Operations Per Second.

Answers to frequently asked questions

You can rent a virtual server for any period. Make a payment for any amount from 1.7 $ and work within the prepaid balance. When the work is completed, delete the server to stop spending money.

You create GPU-servers yourself in the control panel, choosing the hardware configuration and operating system. As a rule, the ordered capacities are available for use within a few minutes.

If something went wrong-write to our round-the-clock support service: https://t.me/immerscloudsupport.

You can choose from basic images: Windows Server 2019, Windows Server 2022, Ubuntu, Debian, CentOS, Fedora, OpenSUSE. Or use a pre-configured image from the Marketplace.

All operating systems are installed automatically when the GPU-server is created.

By default, we provide connection to Windows-based servers via RDP, and for Linux-based servers-via SSH.

You can configure any connection method that is convenient for you yourself.

Yes, it is possible. Contact our round-the-clock support service (https://t.me/immerscloudsupport) and tell us what configuration you need.

Why immers.cloud?

  • Cheapest GPU rates

    Find cheaper — get a discount!
  • Second
    billing

    Use virtual machines just as much, as needed.

  • No
    waiting

    Automatic OS installation. Virtual machines are ready in a few minutes.
  • Free
    Internet

    Up to 1 Gb/s incoming and outgoing traffic for free.
  • Round-the-clock
    support

    Live chat and Telegram support — 24/7.
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Pre-installed images

Create virtual machines based on any of the pre-installed operating systems with the necessary set of additional software.
  • Ubuntu
     
  • Debian
     
  • CentOS
     
  • Fedora
     
  • OpenSUSE
     
  • MS Windows Server
     
  • 3ds Max
     
  • Cinema 4D
     
  • Corona
     
  • Deadline
     
  • Blender
     
  • Archicad
     
  • Ubuntu
    Graphics drivers, CUDA, cuDNN
  • MS Windows Server
    Graphics drivers, CUDA, cuDNN
  • Nginx
     
  • Apache
     
  • Git
     
  • Jupyter
     
  • Django
     
  • MySQL
     
View all the pre-installed images in the Marketplace.

Pure OpenStack API

Developers and system administrators can manage the cloud using the full OpenStack API.
Authenticate ninja_user example: $ curl -g -i -X POST https://api.immers.cloud:5000/v3/auth/tokens \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "User-Agent: YOUR-USER-AGENT" \
-d '{"auth": {"identity": {"methods": ["password"], "password": {"user": { "name": "ninja_user", "password": "ninja_password", "domain": {"id": "default"}}}}, "scope": {"project": {"name": "ninja_user", "domain": {"id": "default"}}}}}'
Create ninja_vm example: $ curl -g -i -X POST https://api.immers.cloud:8774/v2.1/servers \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "User-Agent: YOUR-USER-AGENT" \
-H "X-Auth-Token: YOUR-API-TOKEN" \
-d '{"server": {"name": "ninja_vm", "imageRef": "8b85e210-d2c8-490a-a0ba-dc17183c0223", "key_name": "mykey01", "flavorRef": "8f9a148d-b258-42f7-bcc2-32581d86e1f1", "max_count": 1, "min_count": 1, "networks": [{"uuid": "cc5f6f4a-2c44-44a4-af9a-f8534e34d2b7"}]}}'
Delete ninja_vm example: $ curl -g -i -X DELETE https://api.immers.cloud:8774/v2.1/servers/{server_id} \
-H "User-Agent: YOUR-USER-AGENT" \
-H "X-Auth-Token: YOUR-API-TOKEN"
Create ninja_network example: $ curl -g -i -X POST https://api.immers.cloud:9696/v2.0/networks \
-H "Content-Type: application/json" \
-H "User-Agent: YOUR-USER-AGENT" \
-H "X-Auth-Token: YOUR-API-TOKEN" \
-d '{"network": {"name": "ninja_net", "admin_state_up": true, "router:external": false}}'
Documentation
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Any questions?

Write to us via live chat, email, or call by phone:
@immerscloudsupport
support@immers.cloud
+7 499 110-44-94

Any questions?

Write to us via live chat, email, or call by phone:
@immerscloudsupport support@immers.cloud +7 499 110-44-94
Sign up

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