On Tuesday, 13 March 2018 at 04:35:53 UTC, jmh530 wrote:
5. Clever `=` expression based syntax. For example:
// performs CBLAS call of GEMM and does zero memory
allocations
C = alpha * A * B + beta * C;
You might want to explain this in more detail. I saw expression
and my head went to expression templates, but that doesn't seem
to be what you're talking about (overloading opAssign?)
Expression templates plus overloading opAssign.
I have a lot of work for next months, but looking for a good
opportunity to make Mat happen.
+1
With respect to the title, the benefit of special matrix types
is when we can call functions (lapack or otherwise) that are
optimized for those types. If you want the best performance for
mir, then I think that's what it would take. I'm not sure how
much you've thought about this. For instance, I understand from
graphics libraries that if you're only working with a
particular size matrix (say 3x3), then you can generate faster
code than if you're working with general matrices.
In addition, performance is not the only thing a new user to
mir would care about They likely would also care about
ease-of-use [1] and documentation. Hopefully these continue to
improve.
What's TMMat?
TMat is a transposed matrix. Not sure for now if it would be
required.
Diag seems like it would be a special case of sparse matrices,
though diag is probably simpler to implement.
Diag should be an independent type. But not in the first release.
[1] Would it be seamless to add a Mat to a Diag?
Mat C = M + D; // D - diagonal.
D += M; // Fails at compile time, but
D += M.diag; // pass
Also what happens to the api when you add 10 different matrix
types and need to think about all the interactions.
User API would be simple. But it requires clever compile and
runtime logic to do the best with expression templates.
