Aspire Faculty ID #19085 · Topic: UGC NET Computer Science Dec 2019 (Paper II) · Just now
UGC NET Computer Science Dec 2019 (Paper II)

The following multithreaded algorithm computes transpose of a matrix in parallel:

$p\ Trans(X,Y,N)$

if $N=1$

then $Y[1,1]\leftarrow X[1,1]$

else partition $X$ into four $(N/2)\times(N/2)$ submatrices $X_{11},X_{12},X_{21},X_{22}$

partition $Y$ into four $(N/2)\times(N/2)$ submatrices $Y_{11},Y_{12},Y_{21},Y_{22}$

spawn $p\ Trans(X_{11},Y_{11},N/2)$

spawn $p\ Trans(X_{12},Y_{12},N/2)$

spawn $p\ Trans(X_{21},Y_{21},N/2)$

spawn $p\ Trans(X_{22},Y_{22},N/2)$

What is the asymptotic parallelism of the algorithm?

Solution

Parallelism is given by:

$\dfrac{T_1}{T_\infty}$

Here, $T_1$ is total work.

The algorithm recursively divides the matrix into $4$ subproblems of size $N/2$.

So,

$T_1(N)=4T_1(N/2)+\theta(1)$

Hence,

$T_1(N)=\theta(N^2)$

Now, span or critical path time is:

$T_\infty(N)=T_\infty(N/2)+\theta(1)$

because recursive calls run in parallel.

So,

$T_\infty(N)=\theta(\lg N)$

Therefore,

$\dfrac{T_1}{T_\infty}=\dfrac{\theta(N^2)}{\theta(\lg N)}$

$=\theta(N^2/\lg N)$

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