Beginner speed woes
 
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2026-10-09 APP 2.0.0-beta48 has been released !

This is mainly a bug fix release for the reported bugs in beta47. In addition it has a significant User Interface performance improvement noticable when you need to process 1000s of images in APP.

2026-10-03 APP 2.0.0-beta47 has been released !

This is a very big release... many code optimizations/rewrites, many parts of APP are much faster and more precise, especially star analysis and registration are much faster ! Big mosaics will go much faster 🙂

And we introduce a new preview filter, which includes the new Adaptive Deep Sky Stretch and a General Levels Stretch, this has been long over due. The old preview filter (the panel on the right side to stretch and preview your data) has not been updated for a couple of years and it is a critical part of any APP session.

Adaptive Deep Sky Stretch or ADSS is a much more intuitive stretch algorithm. It is also color preserving (which is a great new addition in itself ! ) which means that the highlights are no longer bleached, color is maintained from the linear data while stretching. You can simply stretch your data using the sky background level and signal width sliders which work much easier and more intuitive. You no longer need to fiddle with the old complicated sliders with zoom buttons. All the zoom buttons for the sliders are made redundant. And you can enter slider values in the slider value fields yourself. I will make a youtube video in the coming days to explain and fully introduce ADSS. Once the video is ready, it will be highlighted on the forum.

RGB Combine upgrade !. The RGB Combine Tool has been rewritten mostly. The tool is faster and easier to use and most importantly, the Luminance slider to inject a luminance channel or channels into the RGB composite is now working correctly. It no longer bleaches the RGB colors. Combined with the new ADSS preview, you will get much better and easier great composites with great color! I will also explain this in a new youtube video.

Beginner speed woes

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(@milesy303)
White Dwarf
Joined: 7 years ago
Posts: 10
Topic starter  

It’s been a long time since I used a message board, all the ones I used were taken over by Facebook haha. 

So I’ve installed fine trial into my laptop which is about 10 years old, 1Gb ram and maybe 1. Something amd processor. It was a windows 7 laptop so you can probably figure out the sort of spec it has.

are things supposed to take this long? I managed to stack my latest images in deep sky stacker in about several hours. Approx 197 lights totalling about 5 hours of exposure.

so far every single step I do in APP is taking that amount of time.

Today I started the saving registered frames and after about 6 hours I was playing in a terminal (I’m using Ubuntu on the machine now) and managed to accidentally cancel the save.

I was gutted at this so I had to start it again as there was no obvious way to restart it again and I left it and went out the house. I came back several hours later to find a message saying - do you want to overwrite - yes or no, and nothing had completed, and now I have no option to answer for all 197 lights - it would be handy to be able to say yes for all or no fall or all - in this particular instance - skip all - meaning I wouldn’t have to wait on every single light being processed again...

anyway I digress a little bit - the current saving process here is taking 3 minutes per image so I estimate that’ll take 9 hours to save the registered files, so I’m off to my bed to let it run again.

im scared how long the integration step will take - if I ever manage to get that far before my trial runs out.

so far excluding my accidental cancel - there’s been about 48 hours of processing time here - on 5 hours of andromeda - not 20 hours - 5 measly hours. 

Its not a 486 I’m running surely I can get better performance than this? Haha 

chris 

 

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(@Anonymous 174)
Joined: 9 years ago
Posts: 5702
 

So APP is using a very different and way more advanced calibration engine compared to DSS. But it requires quite a lot of calculating. Mabula is working on getting this faster by supporting GPU's in the near future, however it's not recommended to use very old computers. 1 GB of ram is very limited and many use at least 8, 16 being even better. A SSD instead of a regular harddrive will speed things up quite a bit as well. So unfortunately, the real issue in this case is the age of the computer I'm afraid. DSS might be able to still process it, but there's also a reason why results in APP are generally much better.



   
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(@milesy303)
White Dwarf
Joined: 7 years ago
Posts: 10
Topic starter  

Thanks. I’ll see what the results look like. I’ll be getting a new computer next year but hopefully once my guiding stuff arrives I’ll be able to get longer subs and reduce this processing time. 

Looking at the way the tasks are performed this looks like something that could perhaps be done using a clustered system?

ive got a cluster of 6 raspberry pi’s sitting there idle. It would be fantastic if there was a way the software could be written to support executing commands in parallel where they could be farmed out. 

Chris 



   
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(@Anonymous 174)
Joined: 9 years ago
Posts: 5702
 

Well, now there's an interesting idea. I don't think Mabula is targeting for running it on pi's (I love them, but they're not processing champs and APP does benefit from multicore CPU's, the new Threadripper cpu's are great for it), but I like the clustering idea, I'll ask him if that would be possible, sharing loads between fast computers.



   
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(@milesy303)
White Dwarf
Joined: 7 years ago
Posts: 10
Topic starter  

Each of mine are probably as fast as this laptop it seems haha. 

I have some background in neural networks and my post grad was basically about sharing computation across a cluster where processing was something that could be done as discrete jobs on their own. So say normalise one image with the inputs it requires. 

Assuming the time to transfer the data is quicker than the time it takes to process it then there would be a net gain. 

Chris 



   
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