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Erlang style immutable reference counted shared memory is not at all state of the art. Persistent data structures are common and effective. I have implemented s
by reitzensteinm 7y ago
Erlang style immutable reference counted shared memory is not at all state of the art. Persistent data structures are common and effective. I have implemented several myself, to store and update trees that don't fit in main memory. If you're updating one byte of your physicist's (say) 1 petabyte dataset, it requires ten memory allocations (log[branch factor] of the size of the dataset).
If you're updating the whole thing linearly, do consider that updating something in place or creating an updated copy is identical in terms of performance; a storage device doesn't care whether the bits streaming back are overwriting the same locations or new ones. Though of course you end up with both copies at the end.
- mafribe 7y agoAre there high-performance matrix multiplication libraries, e.g. for fluid-dynamics simulations, that are implemented using persistent data structures?
- deleted 7y ago[deleted]
- reitzensteinm 7y agoAre there any where multiple threads are mutating overlapping sections of memory? How exactly do you think a GPU matrix multiply violates my initial assertion?