cblas

Bindings to a reference CBLAS implementation — OpenBLAS, Netlib, or MKL — the cross-platform CPU numerics path. Where accelerate is the Apple-only BLAS that ships in every macOS binary, cblas is the portable sibling: link it against whatever CBLAS your platform provides. For the full backend picture, see GPU & numerics.

The surface is standard CBLAS, with typed Order (RowMajor / ColMajor) and Transpose (NoTrans / Trans / ConjTrans) enums instead of char flags:

• Level 1 — sdot, saxpy, sscal, snrm2, sasum (vector dot, scaled add, scale, 2-norm, sum of magnitudes).
• Level 2 — sgemv (matrix-vector).
• Level 3 — sgemm (matrix-matrix).
• Each has its d-variant for f64.

import "cblas/cblas" as cblas;

let x: [f32; 3] = [1.0f32, 2.0f32, 3.0f32];
let y: [f32; 3] = [4.0f32, 5.0f32, 6.0f32];
let dot: f32 = cblas::sdot(
    3 as i32,
    unsafe { #addr_of(x) as *f32 }, 1 as i32,
    unsafe { #addr_of(y) as *f32 }, 1 as i32,
);   // 32.0

Linking

Point the manifest at your CBLAS install if it lives outside the default search path (a custom OpenBLAS prefix, an MKL directory):

[link]
search-paths = ["/opt/openblas/lib"]

The entry becomes both -L<dir> and -Wl,-rpath,<dir>, so the library resolves at link and run time without LD_LIBRARY_PATH.

For NVIDIA GPU acceleration of the same routines, see cuda.