Computational Resources

Lab  

Kieppi 3rd floor:  

  • “ASTRA” has a Quadro P6000 24GB GPU (granted to us by NVIDIA), 16GB RAM, and an Intel Xeon e51620 v3 CPU  

  • “AIDMEI” has two RTX 2080Ti 11GB GPUs, 64GB RAM, and an AMD Ryzen Threadripper 2950X CPU  

 Kieppi 2nd floor:  

  • TEKES (room 262B):   
    • CPU: Intel core i7 7829X @ 3.60GHz  
    • RAM: 64Gb  
    • GPU: Nvidia GeForce GTX 1080 Ti  
       
  •   Think Station (room 262B):  
    • CPU: Intel core i7 8700 @ 3.20GHz   
    • RAM: 64Gb  
    • GPU: Nvidia Quadro P4000  
       
  • Old Raman (room 2112B):  
    • CPU: Intel Xeon E5-2620 v3 @ 2.40GHz  
    • RAM: 128Gb  
    • GPU: Nvidia NVS 310  
       
  • uCT (room 204B):  
    • CPU: Intel Xeon E5-2687W v2 @ 3.40GHz  
    • RAM: 128Gb  
    • GPU: Nvidia Quadro K4000 // Nvidia tesla K20c  

Lab infrastructure  

The laboratory computational resources consist of a total of 6 personal computers from high- to top-tier performance. Equipment ranges from multi-core CPUs, 16-128GB of RAM and GPUs of varying performance. The computers have approximately 1TB of storage space and access to various network drives for extended space.  

Center for Science (CSC)  

The MIPT-unit actively uses CSC cluster resources for research purposes.   

Machine learning infrastructure  

The computational resources comprise 10 personal computers (high- to top-tier), each equipped with a powerful multi-core CPU, 1-2 high performance GPUs, 32-64GB of RAM, and 1TB or more of local storage space. These computers can be used to develop solutions for a wide range of medical imaging problems and also to prototype the most computationally-heavy algorithms for their further training and implementation on the CSC cluster.  

Network-Attached Storage (NAS) 

To support local analysis of large-scale medical datasets, we employ a NAS system with 46.8 TB of fully backed up storage space. The NAS is run by Dell PowerEdge R320 rack server with uninterruptible power supply system. 

 

Three high-performance computers are intended for student use and can be reserved. For details, contact  Santeri Rytky (santeri.rytky(at)oulu.fi).

Last updated: 27.5.2020