Er, no. I do that stuff (well, I'm not clever enough for C++ generally, and it would be OpenMP rather than plain pthreads) on the sort of nodes that Sierra uses. However they mostly use the GPUs, for which POWER9 has particular support. Then I can tell there isn't currently any GEMV or FFT running on this system, and not "all the time" even on our HPC nodes.

While it isn't necessarily clear what peak performance means, MKL or OpenBLAS, for instance, is only ~100% of serial peak on large DGEMM for a value of 100 = 90; ESSL is similar. I haven't measured GEMV (ultimately memory-bound), but I got ~75% of hand-optimized DGEMM performance on Haswell with pure C, and I'd expect similar on POWER if I measured. Those orders of magnitude are orders off, even for, say, reference BLAS. I don't know why I need Python, but the software clearly exists -- all those things and more (like vectorized libm). You can even compile assorted x86 intrinsics on POWER, though I don't know how well they perform relative to on equivalent x86, but I think you're typically better off with an optimizing compiler anyway.

I've packaged a lot of HPC/research software, which is almost all available for ppc64le; the only things missing are dmtcp, proot, and libxsmm (if libsmm isn't good enough).