Artificial intelligence (AI) and machine learning (ML) encompass technologies that will impact industry, science and society in unprecedented ways. Speech and image recognition are just two of the tangible examples of applications that have proven to be reliably applicable in recent years.
HAICORE: Resources for AI/ML
Research and education in AI and ML primarily require large amounts of computing power, most of which is provided by GPUs. To meet the short-term demand for AI hardware, dedicated hardware platforms for all researchers working on AI in the Helmholtz Association have been created with the "Helmholtz AI Computing Resources" (HAICORE) at both the SCC (HAICORE@KIT) and the Forschungszentrum Jülich (HAICORE@FZJ).
HAICORE@KIT, with its 72 NVIDIA A100-40 GPUs, is primarily geared towards a prototypical usage mode of the resources, e.g. for interactive use with Jupyter, and the easiest possible access. For projects with higher demand, the large GPU systems such as HoreKa at SCC are available in addition to HAICORE@FZJ.
Self-registration and more capacity
Access to HAICORE@KIT was already very low-threshold, but required some manual steps such as filling out a short application form or maintaining guest and partner accounts for all non-KIT users.
Therefore, as of Sept. 22, 2022, the previous operating model was changed. Employees of all 18 Helmholtz institutions can now log in to the Federated Login Service (FeLS) of the SCC via the Helmholtz-AAI with their usual accounts and register themselves for the new HAICORE@KIT service. Access to up to four GPUs simultaneously per job is thus immediately enabled. An increase of this limit is possible on request.
The new feature "Multi Instance GPU" (MIG) is used to further increase the capacity of HAICORE@KIT. This allows multiple users to access the same GPU at the same time without processes interfering with each other.
More information about HAICORE@KIT can be found on the Helmholtz AI website or in the user documentation.
Simon Raffeiner