Turn what exists into a measurable baseline
The A100 SXM offered has 80 GB of HBM2e and uses the NVIDIA Ampere architecture. Gather the code version, dependencies, a sample input and the parameters that currently produce an accepted result. This baseline lets you verify the new run without changing the processing rules at the same time.
Even within the same GPU family, check the software environment actually in use. A different library version can change the application's behavior. The handover folder must allow a colleague to reproduce the test without having to dig through a message history for the decisions.
Organize a catch-up queue
Sort the jobs by deadline, dependency and restartability. Separate urgent tasks from optional experiments; assign each one an expected output and a rerun rule. Check that a checkpoint can actually be read back. Its existence on disk does not by itself prove that the work can resume correctly.
Move to H100 for a verifiable reason
The H100 SXM also offers 80 GB, on a different architecture and with HBM3. Moving to this model therefore does not mechanically solve an 80 GB capacity overrun. Consider it with a precise application test; if per-card memory is the main bottleneck, also compare a higher-capacity configuration.
Choose a duration based on your job queue
For 3 days, keep a short list with an acceptance result. For 7 days, group together jobs whose data is already prepared. For 30 days, spread deliveries across several milestones and regularly check the outputs retrieved.
Order the required number of A100 lots, the duration and the appropriate environment. The order contact details designate the follow-up contact. Then share the summary with the technical team so that one person does not reserve the capacity while another prepares a different schedule.