Comment by teleforce
7 months ago
Notice that all the all the languages mentioned depends on the external BLAS library for example OpenBLAS for performance.
D language have excellent support functional and array features with parallel support. On top that not known to others it has high performance native BLAS kind of library with ergonomic and intuitiveness similar to python [1].
[1] Numeric age for D: Mir GLAS is faster than OpenBLAS and Eigen (2016):
http://blog.mir.dlang.io/glas/benchmark/openblas/2016/09/23/...
"Notice that all the all the languages mentioned depends on the external BLAS library". I didn't notice this 'cause I don't think it's true. For example, it highly implausible that APL[1] would depend on BLAS[2] considering APL predates BLAS by 5-10 years ("developed in the sixties" versus "between 1971 and 1973"). I don't think Futhark uses BLAS either but in modern stupidity, this currently two hour old parent has taken over Google results so it's hard to find references.
[1] https://en.wikipedia.org/wiki/APL_(programming_language)
[2] https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprogra...
> Notice that all the all the languages mentioned depends on the external BLAS library for example OpenBLAS for performance.
That's incorrect. Futhark doesn't even have linear algebra primitives---everything has to be done in terms of map/reduce/etc: https://github.com/diku-dk/linalg/blob/master/lib/github.com...
The same holds for Accelerate, and I'm fairly sure also SaC and APL. DaCe even gets a special mention in the paper in section 10.5 stating that they specifically _do_ use BLAS bindings.