The ICEI project expects to be able to provide researchers with access to resources listed in the table below by end of 2020:
Component | Site (Country) | Total ICEI (100%) | Minimum Request | Technical Details | Expected* Availability |
---|---|---|---|---|---|
Scalable Computing Services | |||||
CINECA-ICEI | CINECA (IT) | 348 nodes (TBD) | 1 node |
Thin nodes |
April 2021 (TBD) |
Interactive Computing Services | |||||
Interactive Computing Cluster | CINECA (IT) | 216 nodes (TBD) | 1 node |
Fat nodes + GPU nodes |
April 2021 |
Interactive Computing Cluster | BSC (ES) | 6 nodes | 1 node | Nodes for interactive access with dense memory | January 2021 (TBD) |
Virtual Machine (VM) Services | |||||
Openstack Compute Cluster | CEA (FR) | 20 servers (up to 600 VMs) |
1 VM | 20 nodes with 2 CPUs (18 cores @ 2.6GHz each), 192GB of RAM | March 2021 |
Nord3 | BSC (ES) | 84 nodes | 1 node |
- Nord3: Intel Sandybridge cluster being able to be used as VM host or scalable cluster. 84 nodes dx360m4. - Each node has the following configuration: 2x Intel SandyBridge-EP E5-2670/1600 20M 8-core at 2.6 GHz and 32 GB RAM |
January 2021 |
CINECA-ICEI Openstack cluster | CINECA (IT) | 77 nodes (TBD) | 1 VM | - 2x CPU 8260 Intel CascadeLake, 24 cores, 2.4 GHz - 768 GB RAM DDR4 2933MT/s - 2 TB SSD |
May 2021 (TBD) |
Archival Data Repositories | |||||
Archival Data Repository | CINECA (IT) | 10000 TB (TBD) | 1 TB | Object store with Swift interface | April 2021 (TBD) |
Active Archive 2 | BSC (ES) | 6000 TB | 1 TB | HSM system with Object storage interface based on Spectrum Scale and Spectrum Archive technology | December 2020 |
Active Data Repositories | |||||
HPC Storage @ CINECA |
CINECA (IT) |
10000 TB (TBD) |
1 TB |
Lustre Storage (w DDN IME) accessed from HPC clusters |
April 2021 (TBD) |
HPC Storage @ BSC |
BSC (ES) |
70 TB |
1 TB |
GPFS Storage accessed from HPC clusters |
January 2021 |
*The provided time frame is subject to change
Fenix Virtual Machine Services Models
For detailed information on the Fenix Virtual Machine Services (VM) Models, download the document in PDF. This file offers a description of the Fenix VM Models that may be useful for potential applicants.