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This establishes baseline performance of the algorithm using some resonable default settings. On my local machine, this yeilds the following bechmark results: goos: linux goarch: amd64 pkg: github.com/esimov/triangle cpu: Intel(R) Core(TM) i7-7500U CPU @ 2.70GHz BenchmarkDraw-4 21 3074890062 ns/op PASS ok github.com/esimov/triangle 67.892s Signed-off-by: Chris Waldon <christopher.waldon.dev@gmail.com>
Signed-off-by: Chris Waldon <christopher.waldon.dev@gmail.com>
This commit switches several types from taking 4-bytes-per-pixel to a single byte per pixel. The behavior (so far as I can tell) is unchanged, but the speedup is noticable: goos: linux goarch: amd64 pkg: github.com/esimov/triangle cpu: Intel(R) Core(TM) i7-7500U CPU @ 2.70GHz BenchmarkDraw-4 25 2865398063 ns/op PASS ok github.com/esimov/triangle 74.604s Signed-off-by: Chris Waldon <christopher.waldon.dev@gmail.com>
This brings another few percent of performance improvement: goos: linux goarch: amd64 pkg: github.com/esimov/triangle cpu: Intel(R) Core(TM) i7-7500U CPU @ 2.70GHz BenchmarkDraw-4 27 2498826294 ns/op PASS ok github.com/esimov/triangle 70.112s Signed-off-by: Chris Waldon <christopher.waldon.dev@gmail.com>
This tweak appears to have a minor performance improvemnt associated, as no dynamic allocation has to occur for the slice embedded within the type. goos: linux goarch: amd64 pkg: github.com/esimov/triangle cpu: Intel(R) Core(TM) i7-7500U CPU @ 2.70GHz BenchmarkDraw-4 28 2474394774 ns/op PASS ok github.com/esimov/triangle 71.881s Signed-off-by: Chris Waldon <christopher.waldon.dev@gmail.com>
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Hey @whereswaldon thanks a lot for your contribution, I really appreciate. I left a comment on the benchmark test, otherwise everything is just fine and the speed improvement is quite considerable. Please do that slight adjustment and I will merge it back your PR into the master branch.
This preserves support for older go versions. Signed-off-by: Chris Waldon <christopher.waldon.dev@gmail.com>
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This looks good for me. I have merged it back to the main branch. Thanks a lot.
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Hello! Thanks so much for this amazing library. It's been really fun to play with over the last day or so.
This PR is a series of tweaks I made to boost performance. These were guided by
pprofand the included benchmark, but only tested on a single x86_64 Linux machine. They may not be an improvement everywhere.That being said, they appear to represent a 24% speedup on my test hardware without compromising the output in any way.
I have never worked with these algorithms before, and it is definitely possible that my work contains mistakes that compromise the algorithms under some edge case that I failed to consider or did not understand.
I also don't know enough about the algorithms to know if the parameters being benchmarked represent the normal use-case well enough. Perhaps the benchmark should be using different values?
I did all of this because I have a toy program that transforms my webcam output using this library, and I'm trying to boost the realtime processing capability of this library. Even with all of these enhancements applied, I can only get 15-20FPS for very low-res images.
Regardless, I hope these are a useful reference point for optimization, even if they ultimately aren't merged.