mdarray_demo.va

`include "disciplines.vams"

// Enhancement-15 demonstration: multi-dimensional arrays.
//
// A 2x2 weighted-gain buffer whose gain is the sum of a 2-D weight matrix. It
// exercises every Enhancement-15 capability at once:
//
//   * multi-dimensional array PARAMETER `parameter real [0:1][0:1] w = '{...}`
//     with a nested-literal default -- each element (`w[0][0]`, `w[0][1]`, ...)
//     carries its own default and is individually overridable from SPICE;
//   * multi-dimensional array VARIABLES `real [0:1][0:1] acc, tr;`
//   * NESTED-literal aggregate assignment `acc = '{'{..},'{..}}`;
//   * DYNAMIC (runtime) multi-index read/write `tr[j][i] = acc[i][j]` in nested
//     `for` loops -- a runtime select over the flattened element variables.
//
// The gain g = sum of all w[i][j]. With the defaults (0.1+0.2+0.3+0.4 = 1.0)
// V(out) tracks V(in); overriding any weight element rescales it.
module mdarray_demo(in, out);
    input in;
    output out;
    electrical in, out;

    // 2-D array parameter: nested-literal default, per-element SPICE override
    parameter real [0:1][0:1] w = '{'{0.1, 0.2}, '{0.3, 0.4}};

    real [0:1][0:1] acc;   // working matrix
    real [0:1][0:1] tr;    // transpose
    integer i, j;
    real g;

    analog begin
        // nested-literal aggregate assignment, built from the parameter's elements
        acc = '{'{w[0][0], w[0][1]}, '{w[1][0], w[1][1]}};

        // dynamic multi-index write + read: transpose acc into tr
        for (i = 0; i < 2; i = i + 1)
            for (j = 0; j < 2; j = j + 1)
                tr[j][i] = acc[i][j];

        // dynamic multi-index read: sum the transpose (= sum of all weights)
        g = 0.0;
        for (i = 0; i < 2; i = i + 1)
            for (j = 0; j < 2; j = j + 1)
                g = g + tr[i][j];

        V(out) <+ g * V(in);
    end
endmodule