For the Alice experiment most jobs are IO limited. Although throughput should be improved by run 3 via backend changes (I hope so at least, currently doing my M

For the Alice experiment most jobs are IO limited. Although throughput should be improved by run 3 via backend changes (I hope so at least, currently doing my MSc. thesis on exactly that...). Simulations are compute heavy, but analysis tasks vary, with the speed of a modern processor future analysis is still likely to be IO/bandwidth limited. The ratio of RAM to core on the test server I have access to is 128/20 so 6.4 GiB per core. But for (future) analysis the plan is to use, or at least try to use, shared memory and grouping users tasks together based on the required data (They speak of an analysis train with wagons). So a large part of the ram requirements, namely the backing data, should be shared among the cores. I think ideally there will be a top-level scheduler for each node which tries to minimize the required bandwidth (but that is outside the scope of my work so who knows how it's implemented). With a few "best practices" it should be possible for most analysis to consume a 'reasonable' amount of memory at any given time in that case.