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Comment by stuartaxelowen | Hacker News Reader

That is definitely false - single core performance still matters a lot in many ML applications, where utilizing many (>8) cores is still difficult.

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If by ML, you mean machine learning (and not, e.g., Ocaml et al.), I thought those people were actually into GPUs.

GPUs are useful for deep learning and a few other easily parallelizable algos, but the majority of open source ML software is still stuck in the CPU.

Redis is mostly single thread.

This is not really a great thing about Redis.

It would be a more powerful tool if it was multi-threaded. I'm not an expert, but my impression that it was able to be more powerful in other ways (stability, features) because of the choice to make it mostly single threaded (given labor and complexity constraints).

Is there an alternative RAM database that you like better that is multi-threaded?

As much as Redis is an incredibly potent tool and the quality of craftsmanship on it is very high, there are some incredibly peculiar design decisions that have been made.

Single-treading is one of those. There are times when having more than one thread to help process things would come in very handy, though I recognize that the cost of adding this can be very high.

It's something that will have to be addressed eventually for a single Redis process to take advantage of newer hardware with very low ceilings on CPU power, but huge numbers of cores.

ML on CPUs?

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