- What is CREODIAS?
- Computing & Cloud
- Data & Processing
- Pricing Plans
- Fight with COVID-19
- Examples of usage
- Applications of CREODIAS data
- Useful tools for data processing, available on CREODIAS platform
- CREODIAS for hydrological drought modelling
- CREODIAS for managing Urban Heat Islands
- CREODIAS for Digitising Green Spaces
- CREODIAS for Air Quality
- Advanced data processors on CREODIAS
- CREODIAS for your application
- Solutions for agriculture with CREODIAS
- Earth Observation data for Emergency response
- Security Applications with Satellite Data
- Climate Monitoring with Satellite Data
- Water Analysis on CREODIAS
- CREODIAS for land and agriculture monitoring
- Solutions for atmospheric analysis
- Example of tool usage
- Processing EO Data and Serving www services
- Processing and Storing EO
- Embedding OGC WMS Services into Your website
- GPU Use Case
- Using the EO Browser
- EO Data Finder API Manual
- Use of SNAP and QGIS on a CREODIAS Virtual Machine
- Use of WMS Configurator
- DNS as a Service - user documentation
- Use of Sinergise Sentinel Hub on the CREODIAS EO Data Hub
- Load Balancer as a Service
- Jupyter Hub
- Use of CREODIAS Finder for ordering data
- ESRI ArcGIS on CREODIAS
- Use of CEMS data through CREODIAS
- Searching, processing and analysis of Sentinel-5P data on CREODIAS
- ASAR data available on CREODIAS
- Public Reporting Dashboards
- Sentinel Hub Documentation
- Integration Guides
- OGC API
- Custom Processing Scripts
- Legal Matters
- Partner Services
- About Us
Computing & Cloud
CREODIAS GPU product line-up
Our GPU offer is divided into three product lines that represent different use scenarios. Although they offer comprehensive computing power and are built around same building block use cases are different for each of those configurations.
VM configurations are faster to deploy and can be provisioned instantly, they are aimed for quick tests or quick computing tasks. Like all our VMs they have access to all cloud features and EODATA thru NFS and S3 protocols with speed up to 10 Gbit/s.
DS are single VM on one computer node, dedicating whole node to only one customer. This grants and guarantees the client not only computing resources but network bandwidth and enables local storage with passsthrough speeds. Local NVMe drives dedicated to one customer guarantee 30k+ IOPS.
BM are classical dedicated stand alone servers. Equipped by default with only 2x1 Gbit/s interfaces and only capable of accessing EODATA with External S3 Unlimited Access. Client has full and exclusive access to remote management card and can setup virtualization layers of his choosing. This grants better security and simpler architecture but disconnects BM from most of the Creodias Cloud features.
GPU flavors available on the platform
GPU in Virtual Machines (VM)
- gpu.medium 12vcore 118GB RAM 128GB SSD Network Storage
GPU in Dedicated server virtual machines (DS)
- ds.large.gpu 40 HT Cores (20 cores) 112GB RAM 128 GB SSD Network Storage for OS 2x 960 GB NVMe Local Data Storage GeForce RTX 2080Ti (4352 CUDA Cores, 11GB GDDR6)
- ds.3xlarge.4gpu 48 HT Cores (24 cores) 496 GB RAM 128 GB SSD Network Storage for OS 2x 1920 GB NVMe Local Data Storage 4xGeForce RTX 2080Ti (4352 CUDA Cores, 11GB GDDR6)
GPU in Bare Metal Servers (BM)
- c20.r128.gpu 40 HT Cores (20 cores) 128GB RAM 2x 480 GB SATA SSD FOR OS 2x 960 GB NVMe Local Data Storage GeForce RTX 2080Ti (4352 CUDA Cores, 11GB GDDR6)
- c24.r512.4gpu 48 HT Cores (24 cores) 512 GB RAM 2x 480 GB SATA SSD FOR OS 2x 1920 GB NVMe Local Data Storage 4xGeForce RTX 2080Ti (4352 CUDA Cores, 11GB GDDR6)
Graphics Processing Units (GPU) are recently the biggest source of increase in computing power. They were developed as a specialized tool for processing of images mainly in gaming. But currently they are applied in a growing number of CPU heavy applications: not only related to image processing but also to artificial intelligence (AI), deep learning and others.
In the Earth Observation domain (EO), graphics processors are used, among others for radar interferometry. Currently, software development is focused on gaining more and more benefits from the use of calculation accelerators. We install graphic processors in Virtual Machines on a Dedicated Server (DS). These are virtual cloud machines that fill a full physical server that cannot contain any other virtual machines. These physical machines are additionally equipped with one or many GPU cards to which the user gets access through the "passsthrough" mechanism. Thanks to this, the hypervisor overhead for computational operations is virtually eliminated. In addition, these machines are equipped with very fast NVMe storage enabling appropriate supply of the system with data for calculations.
For more information about the GPU services please contact our sales department.