avo VS gollum

I wonder whether avo could have been useful here?[1] I mention it because it came up the last time we were talking about AVX operations in go.[2]

1 = https://github.com/mmcloughlin/avo

2 = https://news.ycombinator.com/item?id=34465297

I thought the /r/golang comments on this post were pretty useful[1]. They also introduced me to avo[2], a tool for generating x86 assembly from go that I hadn't seen before. There are some examples listed on the avo github page for generating AVX512 instructions with avo.

1 = https://www.reddit.com/r/golang/comments/10hmh07/how_to_use_...

2 = https://github.com/mmcloughlin/avo

For writing AVX512 from scratch avo is a much better alternative.

Avo is a library that simplifies writing complex go assembly, I found it very useful to figure out how instructions map onto Go's asm syntax. But you could definitely do the translation directly, it's what c2goasm did (couldn't get it to work reliably unfortunately).

Curious if you're looking at using avo to write the assembly

You can use github.com/mmcloughlin/avo for generating the assembly use Go.

For normal and "better" mode I am using avo to generate different encoders for different input sizes, with and without Snappy compatibility. That currently outputs about 17k lines of assembly.

You could perhaps just have the Go compiler generate the assembler for your code:

go tool compile -S file.go > file_amd64.s

Then you could verify it doesn't change over time, and choose to begin maintaining by hand if it makes sense.

If you do want to go the route of rolling it yourself, I'd suggest looking into something like Avo: https://github.com/mmcloughlin/avo

If you have to go with Assembly, try Avo https://github.com/mmcloughlin/avo

I did a similar optimization via https://github.com/viterin/vek as the SIMD version. Some somewhat unscientific calculations showed a 10x improvement staying in float32: https://github.com/stillmatic/gollum/blob/07a9aa35d2517af8cf...

TBH my takeaway was that it was more useful to use smaller vectors as a representation

I like Go a lot for working with OpenAI etc, it's 'just' API calls and Go is great at that. I've opensourced some bits here: https://github.com/stillmatic/gollum -- in particular, function dispatch (given a prompt, return an arbitrary Go struct) is really nice, as is a very fast in-memory KNN index.

I've written a version of this in Golang: https://github.com/stillmatic/gollum/blob/main/dispatch.go

```go

I have gotten 10x speedups with SIMD on modern hardware. Goroutines make this actually fairly tricky, as you essentially have to process all the events and then sort the entire array, which is usually the bottleneck. The heap adds a small amount of complexity but is significantly more efficient, feels like good ROI.

https://github.com/stillmatic/gollum/blob/main/vectorstore.g...