Hacker News new | ask | show | jobs
by jandrewrogers 31 days ago
Almost literally what I stated. Consider a row in Postgres table or similar. Convert the entire WHERE clause across all columns in that table into a very short sequence of SIMD instructions against the same memory. All of the columns, regardless of type, are evaluated simultaneously using SIMD. For many complex constraints you can match rows in single digit clock cycles even across many unrelated types. This is much faster than using secondary indexes in many cases.

It isn’t hypothetical, I’ve shipped systems that worked this way. You can match search patterns across a random dozen columns across a schema of hundreds of columns at essentially full memory bandwidth.
1 comments
camel-cdr 31 days ago
OK, I thought it couldn't be that, because that should be doable with std::simd or a SIMD abstraction. Well, unless you JIT it, in which case intrinsics wouldn't help either.

> You can match search patterns across a random dozen columns across a schema of hundreds of columns at essentially full memory bandwidth

Do I underatand it correctly, that this would only work, if you have multiple of the same comparisons (e.g. equality check with same sized data) in the WHERE clause and the relevant collumns are within one multiple of the SIMD width of each other?

link
jandrewrogers 31 days ago
Every column has its own independent constraint: equality, order, range intersection, bit sets, etc that is evaluated concurrently in single operations. Independent per column in parallel. It does require handling the representation of columns to enable it but that isn’t onerous in practice.

It isn’t intuitive but it is one of those things that is obvious in hindsight once you see how it works. The gap is that people struggle to understand how to make this something SIMD native, especially in high-performance systems.

link
camel-cdr 31 days ago
Ah, so you're just doing SoA or AoSoA layout? It sounded like you where doing something more special than the standard SIMD usecase.

This does easily work with SIMD abstractions and even length-agnostic vector ISAs, unless you're doing AoSoA and your storage format has to match your memory format and it has the be the same on all machines. In which case you probably want to do something like 4K blocks anyways, in which case you can make it agnostic for all vector length anybody reasonably cares about for this type of application anyways.

link