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CSCE 689-600 HW 2: Parallel Programming with OpenMP

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CSCE 689-600
HW 2: Parallel Programming with OpenMP

The inverse of an upper triangular matrix R with a block 2×2 structure can be represented as shown
below.
?
−1 = [
?11 ?12
0 ?22
]
−1
= [
?11
−1 −?11
−1?12?22
−1
0 ?22
−1
]
Thus, the inverse of R can be computed recursively by computing the inverse of the two diagonal
blocks R11 and R22 followed by the off-diagonal block.
A Matlab code of the implementation is given below. The code should be saved to a file called
Rinverse.m. The routine Rinverse() creates a well-conditioned random R and calls
compute_inverse() to compute the inverse of the upper triangular matrix recursively.
1. (40 points) You are required to develop a parallel C/C++ implementation of the above
algorithm that uses OpenMP directives to parallelize the compute_inverse routine. You
should use the task directive for the recursive tasks.
2. (5 points) Describe your strategy to parallelize the algorithm. Discuss any design choices you
made to improve the parallel performance of the code.
3. (5 points) Determine the speedup and efficiency obtained by your routine on 1, 2, 4, 10, and 20
processors. You may choose appropriate values for the matrix size to illustrate the features of
your implementation.
function [R, Ri] = Rinverse(n)
A = rand(n);
A = A + diag(sum(abs(A)));
R = triu(A);
Ri = compute_inverse(R);
fprintf(‘Error in computing inverse: %e\n’, …
norm(Ri*R-eye(size(R))));
return
function Ri = compute_inverse(R)
n = size(R,1);
if (n < 16)
Ri = inv(R);
else
n1 = round(n/2);
Ri = R;
Ri(1:n1,1:n1) = compute_inverse(Ri(1:n1,1:n1));
Ri(n1+1:n,n1+1:n) = compute_inverse(Ri(n1+1:n,n1+1:n));
Ri(1:n1,n1+1:n) = – Ri(1:n1,1:n1) * Ri(1:n1,n1+1:n) …
* Ri(n1+1:n,n1+1:n);
end
return
Submission: You need to upload the following to eCampus:
1. Submit the code you developed.
2. Submit a single PDF or MSWord document that includes the following.
• Responses to Problem 1, 2, and 3. Response to 1 should consist of a brief description of
how to compile and execute the code on the parallel computer
Helpful Information:
1. Source file(s) are available on ecampus.
2. Load the Intel software stack prior to compiling and executing the code. Use:
module load intel/2017A
3. The run time of a code should be measured when it is executed in dedicated mode. Create a
batch file as described on hprc.tamu.edu and use the following command to submit it to the
batch system:
bsub < batch_file

PlaceholderCSCE 689-600 HW 2: Parallel Programming with OpenMP
$30.00
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