I read the post and decided to investigate libblas, and OpenBLAS because I had no idea what they were. To benchmark I used R and followed these instructions https://www.r-bloggers.com/for-faster-r-use-openblas-instead-better-than-atlas-trivial-to-switch-to-on-ubuntu/ It turns out that R is not installed so you need to install R with
sudo apt-get install -y r-base r-base-dev
When you install r-base it installs libblas as a dependency. The package r-cran-suppdists is no longer valid so when I ran the benchmark I got an error message indicating the package is missing, but the test appears to run completely.
I then installed OpenBLAS and reran the benchmark.
sudo apt-get install libopenblas-base libopenblas-dev
This installs OpenBLAS and replaces the basic libblas-base when you are running R.
I found timing results for the R benchmark here: http://r.research.att.com/benchmarks/ . When I ran the benchmarks on the 410c, they are running on a single core and are is not quite as fast as a Mac Pro, about 7x slower when using libblas.s0.3.7.0, and about 3.5x slower when using libopenblas_arm8vp-r0.2.19.so
In my initial testing I had used the prebuilt packages, so I decided to build OpenBLAS from scratch:
git clone https://github.com/xianyi/OpenBLAS.git
sudo make install PREFIX=/usr
This was quick and easy, everything went smooth (including the parallel build with -j4). I didn’t have to change anything to get it compiled and installed. R is now running with libopenblas_armv8p-r0.3.0.dev.so rerunning the benchmarks (still single core) with the newest version gets down to only 3.4x slower than a Mac Pro.
Full disclosure: I am an employee of Qualcomm Canada, any opinions I may have expressed in this or any other post may not reflect the opinions of my employer.