Performance variability

I am observing a lot of performance variability for matrix multiplication in sizes ranging from ~100 to ~1000 I have been investigating this without a lot of success. The timing can be up to twice as large, depending on the order in which I run the benchmarks. However, for any chosen order, the accuracy of the timing is high.

I am a bit at a loss here. Because the order only influences the position in memory of the input data to the benchmarks, I am inclined to think that this may be a memory alignment issue. The position of the matrices in the heap is rounded only to 16 bytes (double floats, alignment imposed by C++), but not to any other size and perhaps there is some kind of SIMD code making some kind of ugly magic that disturbs my benchmarks?

I have tested this with serial, openmp and pthreads versions, on Linux and on Windows, with similar outcomes. This is an AMD Ryzen processor, but I have witnessed even greater variability on Intel.

No files, tests, or entry points are named. Start by reproducing matrix-multiplication timings for sizes around 100–1000 in the serial, OpenMP, and pthreads variants on the reported platforms and processor types. Done means identifying the source of the order-dependent variability and documenting a reproducible fix or confirmed cause.