using syrk for performing special cases of matrix multiplication

[vtavana]

In this PR, the syrk routines from oneMKL is used to perform a rank-k update which is used for a specialized matrix multiplication where the result is a symmetric matrix.

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[github-actions]

View rendered docs @ https://intelpython.github.io/dpnp/pull/2509/index.html

[github-actions]

Array API standard conformance tests for dpnp=0.19.0dev0=py313h509198e_45 ran successfully.
Passed: 1227
Failed: 0
Skipped: 9

[antonwolfy]

As an option we can test with the work-groups:

    static constexpr std::size_t tile_sz = 16; // Tile size
    sycl::range<2> global_range(Align(n, tile_sz), Align(n, tile_sz));
    sycl::range<2> local_range(tile_sz, tile_sz);

    // kernel to copy upper triangle to lower triangle
    sycl::event copy_event = exec_q.submit([&](sycl::handler &h) {
        h.depends_on(syrk_event);

        h.parallel_for(sycl::nd_range<2>(global_range, local_range), [=](sycl::nd_item<2> item) {
            int i = item.get_global_id(0);
            int j = item.get_global_id(1);

            if (i < n && j < n && i > j) {
#if defined(USE_ONEMATH_CUBLAS)
                res[i * ldc + j] = res[j * ldc + i];
#else
                if (is_row_major) {
                    res[i * ldc + j] = res[j * ldc + i];
                } else {
                    res[j * ldc + i] = res[i * ldc + j];
                }
#endif // USE_ONEMATH_CUBLAS
            }
        });
    });

but we need to discover a proper tile_sz, based on device

[coveralls]

coverage: 72.027% (-0.03%) from 72.052%
when pulling 8592575 on syrk
into eb4e73c on master.