Speaker
Description
HUN-REN Cloud's primary goal is to support the Hungarian scientific community by providing essential e-infrastructure for their research. The HUN-REN Cloud is one of the main infrastructure pillars of the AI4Science program, which aims to enhance the use of artificial intelligence within the HUN-REN Research Network. This new program has opened up even more opportunities for researchers on the HUN-REN Cloud to accelerate their research utilising AI technologies which is necessitating a transformation of the current resource management system. A newly developed and implemented GPU resource management system is introduced to provide a more demand-responsive (differentiated) solution that makes cloud services available to more users in a more personalised way.
The HUN-REN Cloud is extended with a centrally managed, SLURM scheduler-based batch execution service, which aims to allocate GPU resources more dynamically. The SLURM services provide Singularity containers for a customisable execution environment and a Jupyter-based interactive mode for user convenience. In response to the growing interest in large language models (LLM), HUN-REN Cloud has introduced a PaaS service called GenAI4Science, which provides access to open-source LLMs. This service features a user-friendly web interface and OpenAI-compatible API access for LLMs deployed in a distributed environment with streamlined data management.
This talk will describe the new GPU resource allocation system, along with the new SLURM and GenAI4Science service, to support the HUN-REN AI4Science program.
