# NAISS ```{objectives} - Let's step up and have an overview of NAISS ``` ## NAISS HPC Clusters - Mostly Intel-based CPU:s and Nvidia GPU:s - UPPMAX: - Rackham - General computational resource and also focused towards Life Science - Bianca - NAISS-SENS, resource dedicated to research on sensitive data - PDC (KTH): - Dardel - General computational resource - Not intel/Nvidia but Cray/AMD CPU:s and GPU:s - NSC, Linköping: - Tetralith - General computational resource - C3SE, Chalmers: - Alvis - Accelerator-based resource dedicated to research using AI techniques AND the international - LUMI, Finland - LUMI - General computational resource, aimed at larger projects in Sweden - Not intel/Nvidia but Cray/AMD CPU:s and GPU:s ### Locally financed systems for local users - UPPMAX - Snowy - GPU:s and long runs - LUNARC, Lund - Aurora - C3SE, Chalmers - Vera - NSC, Linköping: - BerzeLiUs - for AI and machine learning - HPC2N, Umeå: - Kebnekaise - General computational resource ## Swedish Science Cloud (SSC) - Complement, offering "advanced functionality" to users who: - need more flexible access to resources - e.g. more control over the OS:s and software environments - want to develop software as a service - want to explore recent technology such as for - IoT applications - “Big Data” e.g. Apache Hadoop/Spark - The UPPMAX cloud Dis (Swedish word for "haze") was introduced in October 2017 and upgraded during 2020. - East region in the Swedish Science Cloud - Other clouds - Umeå University (North, HPC2N). - Chalmers University (West, C3SE). ## STORAGE ### SNIC Storage: Swestore - The purpose of Swestore allocations, granted by Swedish National Allocations Committee (SNAC), is to provide large scale data storage for “live” or “working” research data, also known as active research data. - [https://www.snic.se/resources/swestore/](https://www.snic.se/resources/swestore/) - [https://supr.naiss.se/round/storage/](https://supr.naiss.se/round/storage/) ## The projects - No cost to researchers all over Sweden. - 3 different levels regarding storage and core hours per month ### Compute at UPPMAX - Small: 2000 cpu-hrs/month and 128 GB of storage. - Can be increased to 10,000 hrs - PI: PhD student or higher. - Medium: 10,000-200,000 cpu-hs/month - PI: Assistant professor (forskarassistent) or higher.  - Large 100,000 cpu-hs/month - PI: Assistant professor (forskarassistent) or higher.  ### Storage at UPPMAX - Small: 128 GB-10 TB of storage. - Can be increased to 10,000 hrs - PI: PhD student or higher. - Medium: 10-100 TB - PI: Assistant professor (forskarassistent) or higher.  - Large: More than 100 TB - PI: Assistant professor (forskarassistent) or higher.  ### Application rounds ## NAISS training