The principal disciplines of the project were (1) quantum computing and (2) machine learning, a subset of Artificial Intelligence. This project research led us into the furthest out on the edge of quantum computing, which is using quantum computation for machine learning and the latest in research on the parameter shift rule necessary for tuning the weights in back propagation for deep learning. This turned out to be possible because of the capabilities of the AiMOS supercomputer to effectively simulate quantum computing by doing the mathematics with ease.
This mostly impacts the discipline of mathematics and computer science, with some impact on quantum physics, which is the "hardware" of quantum computing - quantum bits, known as "qubits" are subatomic particles of pure energy, or sometimes very small atoms, used for the engineering of the calculations. The mathematics are all dealing with vector spaces, using linear algebra and especially matrices. The computer science subtopic is artificial intelligence, specifically machine learning, and more specifically, deep learning, as the neural networks did both forward and backward propagation, with learning algorithms on unlabeled data.
Yes, Pace University does not have a working supercomputer, so to be able to utilize the RPI's high performance computer, the AiMOS, through this program was an opportunity that would not have existed without the CAREERS program making the introductions possible for us and the availability of computer time on the AiMOS, which is the largest supercomputer in New York State.
Both the mentor, myself, and the student facilitator, Gio, learned a great deal about the steps necessary to present a program to a supercomputer for queuing in the batch, preparing it for running, running it after staging it in the right place, and then getting the output of results and concurrent output of any errors. We had to learn about placing the appropriate supporting software packages on the super computer from approved white list sources and then accessing them with the right security permissions on the work folders. We learned a great deal about supercomputing.
Pace university faculty are following our progress with great interest and asking how to also present topics to the steering committee at CAREERS for potential inclusion. The Career Services office for the Seidenberg School of Computer Science and Information Systems at Pace University has a Handshake software program and they will be posting there in their Internships section the job postings for student facilitators for projects that are posted as Recruiting on the CAREERS portal for other Pace University students to learn to about the opportunity to become student facilitators. So a relationship has begun from this one project, that hopefully will lead to more projects proposed and more skills building.
Pace university did purchase a supercomputer but did not get it running, some years ago, before the pandemic. We lost the faculty who were its advocates both at our computer science school and our business school - it was a partnership purchase between both schools. There is now great new interest in getting it running effectively. This is not easy and requires buy in from the younger faculty, but the Dean is very pleased at the new interest.
The software and the steps necessary to run our programs on the AiMOS are universal and used on high performance computers worldwide. This means that the skills learned during this experience are totally transferable to new situations. The student facilitator shared his AiMOS experience during his job interviews, and successfully got a job offer, to start at his graduation in May 2022, at TD Bank in the FinTech industry because he has had this introductory experience with a HPC from the CAREERS project. So the student facilitator is ecstatic, as even though our project had nothing to do with FinTech, it did use a HPC, which is a technology transfer of the best kind, supporting capital investments.
Yes, we have a isolated tower situation between schools. One school does not know what the other is doing with much awareness, and there is waste in duplicate areas that could be overcome by better sharing of information. However, we are in a competitive environment, so there is reticence in that. The CAREERS program causes collaboration and sharing by the way it is structured. It was hard to understand the program at first, and that meant about six weeks from starting on an idea until we finally had a successful approved launch to our project. However, once we got into it, it was a joy to learn from the more experienced mentors in HPC that were introduced to us by CAREERS at RPI.
One lesson learned was the steady reporting of progress on a firm schedule and sharing our results with other researchers, while we felt pressured some weeks, it was always a great experience once we were in the meeting, with either the bi-weekly meeting with our Mentors, or the monthly meeting with our region. This collegial feeling was a great environment to be free to ask questions and get detailed responses. One time during the monthly meeting, another student-facilitator reached out to my student-facilitator and they exchanged Python help to one another for machine learning that was a big boost to my student-facilitator, Gio.
Overall, the project was a highly ambitious one, on the edge of the latest innovations in quantum computing and machine learning, and it was pushing the boundaries of what was possible. However, because of the very high quality of collaborators, we were able to make a significant, if incremental, step forward into that mind-bending space of quantum machine learning. We succeeded in getting our research accepted for publication in the Future of Information and Communications Conference (FICC) 2022, and we presented our research in Super Computing Conference 2021 in the Birds Of A Feather session with CAREERS, and we presented our research in two posters at the Machine Intelligence Day 2021 at Pace University's Seidenberg School of Computer Science and Information Systems.