Scale Game of Life to huge matrices

You are given starter code for computing one step of a **Game of Life–style** cellular automaton on a binary grid, but the naive implementation loads the entire matrix into memory. The input grid can be as large as **1,000,000 × 1,000,000**, so it cannot fit in RAM. ## Automaton rule - Each cell is either 0 (dead) or 1 (alive). - For each cell, count the 8 neighbors (up, down, left, right, diagonals). - Apply standard Game of Life rules: - Alive cell survives if it has 2 or 3 alive neighbors; otherwise it dies. - Dead cell becomes alive if it has exactly 3 alive neighbors. ## I/O model Assume the grid is stored on disk (e.g., one row at a time). You are provided helper functions similar to: - `readRow(i) -> array<int>` returns row `i` (0/1 values) - `writeRow(i, row)` writes the computed next-state row `i` ## Task Modify/implement the update so that it can process the full grid without OOM, using limited memory (e.g., O(W) or O(3W) where W is the number of columns). Be careful about: - Boundary rows/columns (treat missing neighbors as 0) - Ensuring correctness while streaming rows Return/produce the next grid on disk.