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Please read the general instructions for this exercise first. Here are the additional instructions specific to this task:
Parallelize your solution to CP1 with the help of OpenMP and multithreading so that you are exploiting multiple CPU cores in parallel. Do not use any other form of parallelism yet in this exercise. Please do all arithmetic with double-precision floating point numbers.
For this technical exercise, we have disabled auto-vectorization.
I will first run all kinds of tests to see that your code works correctly. You can try it out locally by running ./grading test, but please note that your code has to compile and work correctly not only on your own computer but also on our machines.
If all is fine, I will run the benchmarks. You can try it out on your own computer by running ./grading benchmark, but of course the precise running time on your own computer might be different from the performance on our grading hardware.
| Name | Parameters |
|---|---|
| benchmarks/1 | nx = 1000, ny = 1000 |
| the input contains 1000 × 1000 pixels, and the output should contain 1000 × 1000 pixels | |
| benchmarks/2 | nx = 1000, ny = 4000 |
| the input contains 4000 × 1000 pixels, and the output should contain 4000 × 4000 pixels | |
In this task your submission will be graded using benchmarks/2: the input contains 4000 × 1000 pixels, and the output should contain 4000 × 4000 pixels.
The point thresholds are as follows. If you submit your solution no later than on Wednesday, 09 October 2024, at 23:59:59 (Helsinki), your score will be:
| Running time | Points |
|---|---|
| ≤ 4.000 sec | 1 |
| ≤ 1.000 sec | 2 |
| ≤ 0.700 sec | 3 |
If you submit your solution after the deadline, but before the course ends on Wednesday, 04 December 2024, at 23:59:59 (Helsinki), your score will be:
| Running time | Points |
|---|---|
| ≤ 2.000 sec | 1 |
| ≤ 0.700 sec | 2 |