Isn’t this pretty traditional stuff? What is modern about it?
Does any of this map to a GPU for column-oriented analytical data processing? Basically, machines are only good at reading and writing large, contiguous chunks of data. As these machines evolve, the optimal width of those chunks keeps getting larger. The volume of data available is growing. And the types of operations being done on data are becoming more “analytical” (meaning column-oriented and streaming access, rather than row-oriented random access). I would expect “modern storage” algorithms to therefore be cache friendly, column oriented and take the modern, in-memory storage hierarchy into account (from on-chip registers to, to high bandwidth GPU type parallel devices, to NVRAM system memory).
This article comes off to me like a CS101 intro doing Big-O asymptotic analysis on linked lists, without even mentioning the existence and effects of memory caches.
Does any of this map to a GPU for column-oriented analytical data processing? Basically, machines are only good at reading and writing large, contiguous chunks of data. As these machines evolve, the optimal width of those chunks keeps getting larger. The volume of data available is growing. And the types of operations being done on data are becoming more “analytical” (meaning column-oriented and streaming access, rather than row-oriented random access). I would expect “modern storage” algorithms to therefore be cache friendly, column oriented and take the modern, in-memory storage hierarchy into account (from on-chip registers to, to high bandwidth GPU type parallel devices, to NVRAM system memory).
This article comes off to me like a CS101 intro doing Big-O asymptotic analysis on linked lists, without even mentioning the existence and effects of memory caches.