The function `memory_bandwidth()` estimates the memory bandwidth in megabytes per second (MB/s). It returns a named tuple indicating the median, minimum, and maximum of the four measurements.
**Note:** To obtain a reasonable estimate you should start julia with `N` threads, where `N` should match the number of cores (e.g. of a NUMA domain).
**Linux note:** If possible, you should pin the Julia threads (for example to the cores of a NUMA domain) to decrease the variance of the benchmark. The simplest ways to pin `N` Julia threads to the first `N` cores (compact pinning) are 1) settings `JULIA_EXLUSIVE=1` or 2) using [ThreadPinning.jl's](https://github.com/carstenbauer/ThreadPinning.jl)`pinthreads(:compact)`.
A few **important remarks** upfront:
* To obtain a reasonable estimate you should start julia with enough threads (e.g. as many as you have physical cores).
* You should play around with the length of the vectors, used in the streaming kernels, via the keyword argument `N`. Make it large enough (e.g. # of NUMA nodes times four times the size of the outermost cache size) in particular if you get unreasonably high bandwidths.
* If possible, you should pin the Julia threads to separate cores. The simplest ways to pin `N` Julia threads to the first `N` cores (compact pinning) are 1) settings `JULIA_EXLUSIVE=1` or 2) using [ThreadPinning.jl's](https://github.com/carstenbauer/ThreadPinning.jl)`pinthreads(:compact)`. We will use the latter below.
