oneDNN VS cedro

If you are talking about non-small matrix multiplication in MKL, is now in opensource as a part of oneDNN. It literally has exactly the same code, as in MKL (you can see this by inspecting constants or doing high-precision benchmarks).

For small matmul there is libxsmm. It may take tremendous efforts make something faster than oneDNN and libxsmm, as jit-based approach of https://github.com/oneapi-src/oneDNN/blob/main/src/gpu/jit/g... is too flexible: if someone finds a better sequence, oneDNN can reuse it without major change of design.

But MKL is not limited to matmul, I understand it...

For completeness, it looks like this question was posted to the oneDNN GitHub repo and the response was to stay tune for updates.

From the release note of oneDNN v2.5:

Intel are trying to support their oneAPI compute framework on Arm and IBM POWER and z/Architecture (s390x) but since they ever released only a single discrete GPU with the Xe architecture it's unclear whether they'll support Xe GPU compute on e.g. ARM https://github.com/oneapi-src/oneDNN

I’ve built it for now in a separate branch called “self”:

    git clone -b self https://github.com/Sentido-Labs/cedro.git

Currently, it does not make any difference whether this is one token or more because it is sent to the compiler exactly the same as it came in, but you could write a macro/plugin (src/macros/] that recognized this pattern and inserted a space right before the minus “-” sign.

Hi, when I presented the first release here 8 months ago (https://news.ycombinator.com/item?id=28166125) it got interesting comments and today I’ve made a new release with additional features:

- Break out of nested loops: break label; (https://sentido-labs.com/en/library/cedro/202106171400/#labe...)

- Notation for array slices: array[start..end] (https://sentido-labs.com/en/library/cedro/202106171400/#slic...)

- Loop macros: #foreach { ... #foreach } (https://sentido-labs.com/en/library/cedro/202106171400/#loop...)

The possibility of loop macros was discussed in this thread: https://news.ycombinator.com/item?id=28166698

At the time I hadn’t figured out how to make it useful without type information, but now it works. The same for the array slice notation: it took me a while to figure out how to make it do something useful without reflection, with a purely syntantical transformation.

Loop macros are useful for the kind of things for which you would use x-macros (https://en.wikipedia.org/wiki/X_Macro), with the advantage that it does not pollute the global namespace with macro names and the body of the macro stays more similar to the final result, which makes big macros easier to read.

Since it runs before the standard C preprocessor it can do things like building up `_Generic` macros as shown in the loop macro vec example: https://sentido-labs.com/en/library/cedro/202106171400/#loop...

Source code (Apache 2.0 license): https://sentido-labs.com/en/library/ or https://github.com/Sentido-Labs/cedro

If pre-processing your code is an acceptable compromise, my Cedro pre-processor has that feature: passing a file through it produces standard C code for your compiler, and it includes a wrapper cedrocc that can be used in Unix/POSIX-style systems like Linux as a drop-in replacement for GCC: https://github.com/Sentido-Labs/cedro/

What I’d like to do is a quick proof-of-concept to see whether whatever instructions are available in my CPU can be leveraged for UTF-8 en-/decoding.

For instance, does it work any better than my C implementation? https://github.com/Sentido-Labs/cedro/blob/master/src/cedro....

Maybe the compiler already compiles that to an optimal SIMD version, I don’t know.