OLCF ML/DL Short Survey Question Title * 1. What is your overall level of interest in machine learning-related projects (e.g. Unsupervised, Supervised, Reinforcement learning, etc.)? If you answer “no interest”, you may skip to the end of the survey, and we hope you would be willing to share your personal opinions about the current and future state of machine learning within science and HPC in the comment box for Q10. No interest Little interest Moderate interest Considerable interest Question Title * 2. What is your overall personal level of experience in machine learning model development? (Please select all that apply) Have ran existing scripts on a local machine Have made modifications and/or added features to an existing codebase Are a main developer of a machine learning project/codebase using a common framework (e.g. PyTorch, Tensorflow, Scikit-learn) Have optimized model hyperparameters to improve accuracy Have used specialized packages for hyperparameter optimization Have self-implemented new machine learning techniques Other (please specify) Question Title * 3. Which type of ML models do you primarily use for your work? (Please select all that apply) Unsupervised learning models Supervised learning models Reinforcement learning models Graph neural network models Other (please specify) Question Title * 4. What is the highest scale that you have trained machine learning models using data parallelism? Single GPU/CPU >1 GPU >10 GPU scale >100 GPU scale >1,000 GPU scale >10,000 GPU scale Question Title * 5. Do you have experience working with model parallelism (as opposed to data parallelism)? Yes No Question Title * 6. What is your experience with machine learning inference? (Please select all that apply) Have evaluated model accuracy on a test set Have used trained models on data outside of the test dataset Have provided trained models to external users Have served/deployed the model to external users Have parallelized inferencing for greater throughput Have used trained models in a data-streaming context Have deployed trained models inside a traditional HPC simulation/application Other (please specify) Question Title * 7. For the current FY, is machine learning exploration or development included as part of a project milestone? Yes, a major milestone Yes, a minor milestone No, not a milestone I'm not sure Question Title * 8. In your field of research, what innovations or breakthroughs if any do you believe are required to advance machine learning adoption? Please feel free to provide as much detail as necessary. Question Title * 9. For those developing or interested in machine learning projects, how difficult do you estimate data-collection to be for your projects of interest? (Please select all that apply) Data exists in organized form Data exists but requires collection/organization Data can be passively collected over time Data can be generated and is computationally “cheap” Data can be generated and is computationally “expensive” Data collection is currently infeasible Other (please specify) Question Title * 10. Is there anything else you would like to tell us on this subject that we did not ask? Question Title * 11. Please provide your contact information if you wish. Name Email Address Done
