Awarded Projects

This project will perform cross-datacenter training of a stage-of-the-art multilingual LLM at an unprecedented scale (tens of billions of parameters trained on tens of trillions of tokens) using coordinated allocations across multiple supercomputers.

The primary aim of this project is to develop large-scale brain-like machine learning algorithms.

Vision language models (VLM) represent a multimodal extension of text-based language models that allow to incorporate visual information into the generation process of the output text.

This proposal portrays several extensions to this discovery, which involve optical manipulation of the laser beam to achieve brighter radiation beams. The main strong-suit of the proposed research is that it is closely followed by experiments using our 20 Terawatt (TW) laser lab.

The free-surface flow induced by progressive non-breaking wind waves propagating in shallow waters over a  horizontal bottom will be investigated by means of Direct Numerical Simulations (DNS).

This project aims to construct a comprehensive map of drag reduction as a function of Reynolds number and verify the reliability of finite-Reynolds-number extrapolations.

This research project investigates the structure and dynamics of wall-bounded turbulence in adverse and favorable pressure gradient (APG and FPG) turbulent boundary layers (TBLs) using direct numerical simulation (DNS).

Among the solutions used to control shock wave/turbulent boundary layer interaction (SBLI) in practical applications, several studies in recent years have demonstrated the effectiveness of micro vortex generators (MVGs) to successfully delay shock-induced separation with reduced device drag.

This project will perform cross-datacenter training of a stage-of-the-art multilingual LLM at an unprecedented scale (tens of billions of parameters trained on tens of trillions of tokens) using coordinated allocations across multiple supercomputers.