This representation of jagged array is literally the "Compressed Sparse Row" (CSR) format for sparse matrices [1]:

- a single array of floats with all the nonzero matrix entries, ordered row-by-row:

  double values[nnz];

- a single array of ints with the corresponding column index:

  int columns[nnz];

- a single array of ints, of length (m+1), with the start of each row in the two other arrays (the (m+1)th element stores nnz, which will be useful later):

  int start[m + 1];

So to print a whole matrix, you do this:

  for (int i = 0; i < m; i++) {
    index = start[i]; // where
    count = start[i + 1] - start[i]; // number of nonzeros in row i
    
    for (int t = 0; t < count; t++) {
       j = columns[index + t];
       v = values[index + t];
       printf("element (%d, %d) has value %g\n", i, j, v);
    }

To a modern programmer, this may look very old-fashioned (Fortran-ish), but I have tried many alternatives (like grouping columns and values together in a struct, or using pointers), and in my numerical codes, nothing gets even close in terms of performance. It must be said that CSR and CSC (its transpose) are very compact in memory, which is often a bottleneck. Also, since so many sparse numerical codes in benchmarks have used this representation for decades, it could be that CPU designers make sure that it works well.

[1] https://en.wikipedia.org/wiki/Sparse_matrix#Compressed_spars...