Getting Started

Multi-threaded matrix multiplication: matmul! and matmul

Octavian exports the functions matmul! and matmul, which provide multithreaded matrix multiplication in pure Julia.

Remember to start Julia with multiple threads with e.g. one of the following:

  • julia -t auto
  • julia -t 4
  • Set the JULIA_NUM_THREADS environment variable to 4 before starting Julia
julia> using Octavian
julia> A = [1 2 3; 4 5 6]2×3 Matrix{Int64}:
 1  2  3
 4  5  6
julia> B = [7 8 9 10; 11 12 13 14; 15 16 17 18]3×4 Matrix{Int64}:
  7   8   9  10
 11  12  13  14
 15  16  17  18
julia> C = Matrix{Int}(undef, 2, 4)2×4 Matrix{Int64}:
 139695872798832  139695872798960  139695872799024  139695872799152
 139695872798896  139695872798728  139695872799088  139695872799216
julia> matmul!(C, A, B) # (multi-threaded) multiply A×B and store the result in C (overwriting the contents of C)2×4 Matrix{Int64}:
  74   80   86   92
 173  188  203  218
julia> C2×4 Matrix{Int64}:
  74   80   86   92
 173  188  203  218
julia> C == A * Btrue
julia> using Octavian
julia> A = [1 2 3; 4 5 6]2×3 Matrix{Int64}:
 1  2  3
 4  5  6
julia> B = [7 8 9 10; 11 12 13 14; 15 16 17 18]3×4 Matrix{Int64}:
  7   8   9  10
 11  12  13  14
 15  16  17  18
julia> C = matmul(A, B) # (multi-threaded) multiply A×B and return the result2×4 Matrix{Int64}:
  74   80   86   92
 173  188  203  218
julia> C2×4 Matrix{Int64}:
  74   80   86   92
 173  188  203  218
julia> C == A * Btrue