In particle physics, processing jobs face a limit of about 2GB/core. This is driven by the realities of "grid computing". The hardware in the computing facilities have approximately 2GB/core and jobs allocate based on number of core. This ratio has been fairly stable for a long time. Some facilities may have a bit more RAM per CPU core but 2GB/core is the general rule of thumb. I hazard a guess that this will not change throughout the (hopefully small number of) years that this memory cost bubble persists. In fact, the increase in cost may lead some facilities to keep older hardware going beyond its EOL/warranty period, prolonging a ratio that may actually be relatively generous compared to today's hardware systems.

As a consequence of this fixed RAM/core ratio, substantial software development effort goes to either making jobs fit in 2GB or if that is not possible then to utilize multithreading. Generally, particle physics processing does not particularly benefit from MT except in this fixed RAM/core situation. Sometimes large memory jobs are needed (inherently or because of bloat that is too costly to improve). When run on the "grid", these jobs must allocate multiple cores just to get "their" memory. If those jobs can use the extra cores, overall throughput does not have to suffer.

That's for conventional software, which still makes up the bulk of the computing. The situation for the growing amount of GPU-accelerated software is different and more varied. One trend can be seen relating to VRAM. Research groups with easy access to big GPUs like A100 write code to fit or exceed the relatively copious VRAM limits of the data-center GPUs, while groups that lack easy access to DC GPUs but have access to more modest "gamer" GPUs write more advanced software that can fit the smaller VRAM. In some cases, they write the software so it can scale the computation, keeping GPU utilization high while staying just under the VRAM limit.

General budget crisis and limited resources in the particle physics field are in part responsible for all of this tailoring of the software to fit the hardware. If better funded, particle physicists could spend more time doing physics and less time squeezing last drops of processing power.