$4.(5$ points$)$ Matrix multiplication plays an important role in a number of applications.$$ Two matrices can only be multiplied if the number of columns of the first matrix is equal to the number of rows in the second.$$ Let us assume we have an m$$n matrix A and we want to multiply it by an n$$p matrix B$.$ We can express their product as an m$$p matrix denoted by C$=$ AB where$$ ci$,$j$$ denotes the entry in C at position$($i$,$ j$)$ for each element i and j with $1$i$$m and $1$j$$p$.$ Now we want to see if we can parallelize the computation of C$.$ Assume that matrices are laid out in memory sequentially as follows:$$ a$1,1,$ a$2,1,$ a$3,1,$ a$4,1,...$ etc.$$ Assume that we are going to compute$$ C on both a single core shared memory machine and a $4-$core shared$-$memory machine. Discuss the speedup we would expect to obtain on the $4-$core machine, ignoring any memory issues.