Basic multi-thread rev implementation.

the rev() Operation

Given a matrix $$( A )$$ of size $$( m \times n )$$, rev() produces a matrix $$( B )$$ of the same dimensions such that:

$$B_{i,j} = A_{m-1-i, j}$$

for all $$( 0 \leq i < m )$$ and $$( 0 \leq j < n )$$.

In words:

• Each row of the output is the corresponding row from the bottom of the input matrix.
• The last row of the input becomes the first row of the output, the second last becomes the second, ... the first row becomes the last.

Example

Suppose:

$$A = \begin{bmatrix} 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \\ \end{bmatrix}$$

Then after rev(A), you get:

$$B = \begin{bmatrix} 7 & 8 & 9 \\ 4 & 5 & 6 \\ 1 & 2 & 3 \\ \end{bmatrix}$$

Multi-threaded Implementation

• Split the matrix into chunks of rows.
• Each thread copied its assigned chunk of output rows, each time taking from the appropriate (reversed) input row:
  • If a thread was responsible for output row $$( i )$$, it took input row $$( m-1-i )$$.
• All threads worked in parallel.

Summary Table

test

for every cell $$( (i, j) )$$, output[i][j] == input[rows - 1 - i][j]