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 2nd generation 6240R CPUs with a base clock speed of 2.4 GHz and a maximum clock speed with Turbo Boost technology of 4.0 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 up to 3072 GB of DDR4 ECC Reg 2993 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 640 Tensor Cores, the Tesla V100 is the first accelerator to overcome the performance barrier of 100 teraoperations per second (TOPS) in deep learning tasks. Models that took weeks and months to train on previous generation systems can now be trained in just a few days.
High Performance Computing (HPC) is the fundamental pillar of modern science. From weather forecasting and the creation of new medicines to the search for energy sources, scientists constantly employ large computing systems to model our world and predict events within it. AI expands the capabilities of HPC, enabling scientists to analyze vast 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 AI. This is a solution for HPC systems, which will prove itself adept 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 augment or replace hundreds of traditional CPU servers, performing both traditional HPC and AI tasks. Now, every scientist can access a supercomputer to tackle the most challenging 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 is assigned only to a single client. It means that:
Available vCPU time is 100%;
Physical pass-through of GPU inside a virtual server;
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 Servers with local SSDs.
Up to 70 000 IOPS1 for the RANDOM READ and up to 60 000 IOPS for the RANDOM WRITE for the Virtual Servers with block storage Volumes.
You can be sure that Virtual Servers are not sharing vCPU or GPU between 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 starting from 1.1 $ 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 can create GPU-servers yourself under the control panel, choosing the hardware configuration and operating system. 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 to 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.
A bit more about us
Per-second billing
and free VM pause (shelve). You pay for the actual use of your VMs
24/7/365
Tech support is always available via chat and responds within minutes
Free traffic
Speed up to 20 Gb/s without extra charge for incoming and outgoing traffic
Our data centers
Built according to the TIER III standard
100% of power is yours
We do not share resources you purchased with other users