Add quickselect algorithm. Quickselect is a selection algorithm to find the kth smallest element in an unordered list.

In,
https://github.com/flame/blis/blob/master/docs/Performance.md
I noticed that MKL on EPYC was abysmal, but that's just because it uses SSE2 on AMD by default.
You can set the following (undocumented!) environment variable to tell MKL to use AVX2 CPU instructions:
export MKL_DEBUG_CPU_TYPE=5

The fp_reduction_latency benchmarks were the very first benchmark, optimization and primitive code tested in Laser.

Unfortunately it is currently very confusing.

It should be reorganized:

• 1. Multiple accumulators: https://github.com/numforge/laser/blob/af191c086b4a98c49049ecf18f5519dc6856cc77/benchmarks/fp_reduction_latency/reduction_bench.nim and https://github.com/numforge/laser/blo

Hi,

Your glas library is very interesting, and the benchmark for your gemm is impressive. I think users and potential contributors would benefit greatly from a series of blogs or documentation explaining the design approach you have taken for the whole library and for the gemm algorithm.

One of the issues about D is that the advanced methods, idioms, and techniques are not particularly well

Machine learning libraries have found a nice API for tensor contractions, which is based on the Einstein notation. Examples are PyTorch, Tensorflow, and NumPy. I guess, it would be rather strai