If your code consists mainly of small arrays, you may want to have a look at the FixedSizeArrays <https://github.com/SimonDanisch/FixedSizeArrays.jl> or StaticArrays <https://github.com/JuliaArrays/StaticArrays.jl> package. These provide fast and convenient stack allocated arrays.
On Sunday, September 25, 2016 at 5:19:39 PM UTC+2, vav...@uwaterloo.ca wrote: > > My code has many operations on small matrices and vectors. In Julia 0.4, > carrying these out with subvector operations causes a needless heap > allocation, so I've done them all with loops. In other words, instead of > nr = norm(x[p:p+2]) > > I write > > nr = 0.0 > for j = p : p + 2 > nr += x[j]^2 > end > nr = sqrt(nr) > > I've also used the Einsum.jl macro package, which implicitly writes the > loops. > > My question is: do the new broadcast and generator-comprehension > operations available in 0.5 or 0.6 make it possible to accomplish these > small operations using one-line solutions that don't allocate heap memory? > > Here are some other examples of operations for which I would like > efficient one-liners: > > t = dot(v[p:p+3], w[p:p+3]) > c += A[p:p+2, q:q+2] * v[q:q+2] # "gaxpy"; c is a length-3 vector > > Thanks, > Steve Vavasis > >
