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
Prices:
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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.
IOPS — Input/Output Operations Per Second.
Answers to frequently asked questions
What is the minimum rental period for a virtual GPU-server?
You can rent a virtual server for any period. Make a payment for any amount from 1.3 $ and work within the prepaid balance. When the work is completed, delete the server to stop spending money.
How quickly can I get started with a virtual GPU-server?
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.
What operating systems can be installed on a virtual GPU-server?
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.
How to connect to a virtual GPU-server?
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.
Is it possible to rent a virtual GPU-server with an custom configuration?
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!
Discounts for prepayment
25% and 50% discount on prepayment for 1 and 3 months
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