netlib BLAS/LAPACK, openBLAS, AMD libs, intel MKL, eigen, armadillo, GLM, Blitz++, PETSc, Trilinos (and I am not even starting on more "specialized" such as sparce matrices).
There are maybe one hundred libraries in the field.
IMO all of them and certainly any new/active one(s) should clearly differentiate (or state) thier purpose/goals and what makes them different. Please note, I am not saying what makes them better but different.
I am also tired of reading/hearing "HPC/simd/parallel" without ANY benchmarks/timings to support such claims. Isn't it strange that software implementing mathematics make claims (almost all of the times) without any measurements/proof?
Thanks for the info though, I might remember to try it in the future.
edit: the rant is not about Blaze, it is more of a general rant about similar libraries. I feel I have to mention that Blaze at least tries to address what I am complaining and I also saw that they have instructions on how to replicate their benchmarks on ones' machine which IMO is what every project should be doing.
There are maybe one hundred libraries in the field.
IMO all of them and certainly any new/active one(s) should clearly differentiate (or state) thier purpose/goals and what makes them different. Please note, I am not saying what makes them better but different.
I am also tired of reading/hearing "HPC/simd/parallel" without ANY benchmarks/timings to support such claims. Isn't it strange that software implementing mathematics make claims (almost all of the times) without any measurements/proof?
Thanks for the info though, I might remember to try it in the future.
edit: the rant is not about Blaze, it is more of a general rant about similar libraries. I feel I have to mention that Blaze at least tries to address what I am complaining and I also saw that they have instructions on how to replicate their benchmarks on ones' machine which IMO is what every project should be doing.