Engagements tagged allocation-management

The research focus is to apply the pre-training techniques of Large Language Models to the encoding process of the Code Search Project, to improve the existing model and develop a new code searching model. The assistant shall explore a transformer or equivalent model (such as GPT-3.5) with fine-tuning, which can help achieve state-of-the-art performance for NLP tasks. The research also aims to test and evaluate various state-of-the-art models to find the most promising ones.

I am working on a large-scale problem for the first time and would appreciate any form of assistance in understanding concepts that would efficiently allow me to maximize the use of an amazing resource such as the supercomputers at PSC Bridges. What I feel bad about is accidentally using a lot of resources that might only require half of the allocated resource, leading to a waste of allocated computing time and resources, all because I do not understand the allocation process properly. I primarily use Jupyter Labs and TensorFlow for machine learning applications. Additionally, I am responsible in my lab for supervised machine learning and teaching other people, which is why I would appreciate this support.

I am not familiar with exchanging credits for hours on machine and any guidance as which cluster and how many hours needed on it would be great. I am experienced in python coding and would like to work on a python friendly interface and i need to parallelize my code to run for lots of different parameter values and it also involves large matrix so quite some memory overhead.