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Home/ Questions/Q 6740593
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Editorial Team
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Editorial Team
Asked: May 26, 20262026-05-26T11:37:27+00:00 2026-05-26T11:37:27+00:00

I’ve written an app which is handling videos. As we know, video processing takes

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I’ve written an app which is handling videos. As we know, video processing takes a huge amount of memory while dealing with HD resolution. My App always seemed to crash. But actually I am 100% sure, that there is no memory leak in my code. Instruments is showing no leak.

At the beginning I am startin up one OpenGLES view and the video engine. For a very short time the memory consumption is high, but falling down to normal level after the initializations are done. I am always getting memory warnings during this period. Normally this is no problem. But if I have a lot of apps in suspended mode running, the App seems to be crashing. Watching into the crash log and using the debugger shows up, that I am only running out of memory.

My customers are flooding my support mail with “app is crashing” mails. But I do know, that they have too much Apps running in the background, so there is no memory left to go. I think it’s bad style programing saying the customer that he has to close Background tasks before running the app.

According to this post this is a common problem.

My question is: Is it possible to tell the OS that one needs a lot of memory so the OS should terminate some suspended Apps? This memory stuff makes me crazy, because it’s no bug I could fix.

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  1. Editorial Team
    Editorial Team
    2026-05-26T11:37:28+00:00Added an answer on May 26, 2026 at 11:37 am

    No. It is not possible to affect anything outside of your sandbox without API calls. None exist for affecting other processes in the public API.

    Have you tried to minimize your memory usage? In my experience once a memory warning it thrown apps can be more likely to have problems once they are in the background, even when memory usages drops.

    If you are using OpenGLES and textures, if you haven’t already compress your textures. What is the specific cause of your memory allocation spike?

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