93
edits
Changes
→Assignment 1
</source>
<nowiki>************************</nowiki><pre style="color: green">
The hotspot seems to be the double for-loop based on m and n in the Jacobi iterations code of the dojacobi() function. I believe these matrix calculations could be parallelized for improved performance. Note that the for-loop that the double loop is inside of is based on a constant numbers, iters, so it doesn't grow with the problem size. It would be O(iters * n^2) which is still O(n^2) not O(n^3).
</pre>
==== Idea 2 - LZW Compression ====
=== Assignment 2 ===
We parallelized the original code by placing the jacobi calculations into a kernel. For this initial parallel version, we only used 1D threading and had each thread run a for loop for the other dimension.
The iters loop launches a kernel for each iteration and we use double buffering (where we choose to launch the kernel with either d_a, d_b or d_b, d_a) since we can't simply swap pointers like in the serial code.
<source>
