The logic in memory devices can leverage the physical data proximity and immense internal bandwidth to perform memory-intensive functionalities.
First, some applications exhibit poor temporal and spatial locality.
The widening discrepancy between computation speed and data transfer speed, commonly known as the memory wall [49], motivates the need for a different computing paradigm.
Anton 3 achieves order-of-magnitude improvements in time-to-solution over its predecessor, Anton 2 (the current state of the art), and is over 100-fold faster than any other currently available supercomputer, thereby enabling broad new avenues of research on critical questions in biology and drug discovery.
We developed a multi-tier parallelization scheme across valence/conduction bands, quasiparticle states, and planewave basis elements to allow for an efficient and flexible multi-GPU, multi-node implementation.
However, differences in the distribution and memory wastage is not a big concern, as it can be eliminated by handling the mbuf allocation at the application level (e.g., in FastClick [3]).
Employing slice-aware memory management requires some consideration, as it might cause performance degradation.
In short, slice-aware memory management partitions LLC similar to CAT but with a granularity of a slice, which means an application is limited to a smaller portion of LLC, but with faster access, i.e., lower latency.