I'm porting cobalt release_11 (11.119147) to my STB .
I want to reduce the cobalt memory usage when play 4K Video to the 180M .
Cobalt will add about 140M of memory(all 250M memory) when playing 4K video from the youtube homepage, most are used as media buffer to cache demuxer media data.
I find the base.gypi have a parameter config: cobalt_media_buffer_storage_type as follows:
# This can be set to "memory" or "file". When it is set to "memory", the
# media buffers will be stored in main memory allocated by SbMemory
# functions. When it is set to "file", the media buffers will be stored in
# a temporary file in the system cache folder acquired by calling
# SbSystemGetPath() with "kSbSystemPathCacheDirectory". Note that when its
# value is "file" the media stack will still allocate memory to cache the
# the buffers in use.
'cobalt_media_buffer_storage_type%': 'memory',
when it set to "file", it will add define "COBALT_MEDIA_BUFFER_STORAGE_TYPE_FILE=1" ,
But I did not find any source code about COBALT_MEDIA_BUFFER_STORAGE_TYPE_FILE , Whether this configuration is still valid?
Is there a better way to reduce memory, except as described in memory_tuning.md
Sorry, Cobalt currently doesn't support caching media buffers in file system.
Is it possible for you to tell us the purpose of the optimization? Are you trying to make Cobalt support 4k playback on a system with limited memory, or are you trying to optimize the memory footprint of Cobalt just to see if it can take less resource on your target system?
Related
We are using Web Audio API to play and manipulate audio in a web app.
When trying to decode large mp3 files (around 5MB) the memory usage spikes upwards in Safari on iPad, and if we load another similar size file it will simply crash.
It seems like Web Audio API is not really usable when running on the iPad unless we use small files.
Note that the same code works well on Chrome Desktop version - Safari version does complain on high memory usage.
Does anybody knows how to get around this issue? or what's the memory limit for playing audio files using Web Audio on an iPad?
Thanks!
Decoded audio files weight a lot more in RAM than on disk. A single sample uses 4 bytes (32-bit float). This translates to 230 MB of RAM for 10 minutes of audio at 48 000 Hz sample rate and in stereo. One hour of audio at the same sample rate and with stereo will take ~1,3 GB of RAM!
So, if you decode a lot of files, you can consume big amounts of RAM. My suggestion is to "undecode" files that you don't need (just "forget" unneeded audio buffers, so garbage collector can free memory).
You can also use mono audio files instead of stereo, that should reduce memory usage by half.
Note, that decoded audio files are always resampled to device's sample rate. This means that using audio with low sample rates won't help with memory usage.
I have a MTLBuffer that is using memory that is allocated by the cpu and thus shared by both the cpu and the GPU.
Per Apple's suggestion I am using triple buffering to remove latency that might be caused by one processor waiting on the other to finish.
My vertex data changes every frame so every frame I am writing to one section of the array with the CPU and reading a different section with the GPU.
What I would like to do is read some of the values that the GPU is currently also reading as they save me some time doing calculations for the section of the buffer the CPU is writing to.
Essentially this is because the current frame's data is dependent on the previous frames data.
Is this valid? Can the CPU and the GPU be reading from the same portion of memory at once since memory is shared on iOS?
I think that's valid and safe, for two reasons. First, CPUs actually often have to read in order to write. Things like caches and memory buses don't allow for access to RAM at the granularity we usually think of (byte or even register size). In order to write, it usually has to read a larger chunk from memory, modify just the part written, and then (eventually) write the larger chunk back to memory. So, even the approach where you don't explicitly read from parts of the buffer that the GPU is reading and you only write to parts that the GPU isn't accessing can, in theory, still be implicitly reading from parts of the buffer that the GPU is reading. Since we're not given the info we'd need to reliably avoid that, I'd say it isn't considered a problem.
Second, no warning is given about what you describe in Apple's docs. There's the "Maintaining Coherency Between CPU and GPU Memory" section in the article about resource objects. That only discussed the case where either the CPU or GPU are modifying shared data, not where both are just reading.
Then there's the "Resource Storage Modes and Device Memory Models" section describing the new storage modes introduced with iOS 9 and macOS 10.11. And the docs for MTLResourceStorageModeShared itself. Again, there's mention of reading vs. writing, but none about reading vs. reading.
If there were a problem with simultaneous reading, I think Apple would have discussed it.
By pressing F12 and then Esc on Chrome, you can see a few options to tick. One of them is show FPS meter, which allows us to see GPU memory usage in real time.
I have a few questions regarding this GPU memory usage:
This GPU memory means the memory the webpage needs to store its code: variables, methods, images, cached videos, etc. Is this right to affirm?
Is there a reason as to why it has an upper bound of 512 Mb? Is there a way to reduce or increase it?
How much GPU memory usage is enough to see considerable slowdown on browser navigation?
If I have an array with millions of elements (just hypothetically), and I splice all the elements in the array, will it free the memory that was in use? Or will it not "really" free the memory, requiring an additional step to actually wipe it out?
1. What is stored in GPU memory
Although there are no hard-set rules on the type of data that can be stored in GPU-memory, the bulk of GPU memory generally contains single-frame resources like textures, multi-frame resources like vertex buffers and index buffer data, and programmable-shader compiled code fragments. So while in theory it is possible to store video's in GPU memory, as well as all kinds of other bulk data, in practice, for every streamed video only a bunch of frames will ever be in GPU-ram.
The main reason for this soft-selection of texture-like data sets is that a GPU is a parallel hardware architecture, and it expects the data to be compatible with that philosophy, which means that there are no inter-dependencies between sets of data (i.e. pixels). Decoding images from a video stream is more or less the same as resolving interdependence between data-blocks.
2. Is 512MB enough for everyone?
No. It's probably based on your hardware.
3. When does GPU memory become slow?
You have to know that some parts of the GPU memory are so fast you can't even start to appreciate the speed. There is nothing wrong with the speed of a GPU card. What matters is the time it takes to get the data IN that memory in the first place. That is called bandwidth, and the operations usually need to be synchronized. In that case, the driver will lock the Northbridge bus so that data can flow from main memory into GPU memory, and this locking + transfer takes quite some time.
So to answer the question, once it is uploaded, the GUI will remain fast, no matter how much more memory is used on the GPU card. The only thing that can slow it down, are changes to the GUI, and other GPU processes taking time to complete that may interfere with rendering operations.
4. Splicing ram memory frees it up?
I'm not quite sure what you mean by splicing. GPU memory is freed by applications that release that memory by using the API calls to do that. If you want to render you GPU memory blank, you'd have to grab the GPU handles of the resources first, upload 'clear' data into them, and then release the handles again, but (for normal single-threaded GPU applications) you can only do that in your own process context.
Is it possible to store the display list data on the video card memory?
I want to use only video memory like Video Buffer Object(VBO) to store DisplayList.
But when I try it, it always uses main memory instead of video memory.
I tested on nVidia geForce 8600GTS, and GTX260.
Display lists are a very old feature, that dates back to OpenGL-1.0. They have been depreceated a long time ago. Anyhow you can still use them for compatibility reasons.
The way OpenGL works, prevents display lists from being held in GPU memory only. The graphics server (as OpenGL calls it) is a purely abstract thing, and the specification warrants, that what you put in a display lists is always available. However in modern GPUs there's only a limited amount of memory, so payload data may be swapped in and out as needed.
Effectively GPU memory is a cache for data in system RAM (the same way system RAM should be treaded as cache for storage).
Even moreso, modern GPUs may crash, and the drivers will perform a full reset giving the user the impression everything works normal. But after the reset all the data on GPU memory must be reinitialized.
So it is necessary for OpenGL to keep copies of every payload data in memory to support smooth operation.
Hence it is perfectly normal for your data to show up as consuming system RAM as well. It is though very likely, that the display lists are also cached in GPU memory.
Display Lists are deprecated. You can use VBO with vertex indices to use graphics memory, and draw it with glDrawElements.
I'm just researching at the moment the possibility of writing an app to record an hours worth of video/audio for a specific use case.
As the video will be an hour long I would want to encode on-the-fly and not after the recording has finished to keep disk usage to a minimum.
Do the video capture APIs write a large uncompressed file to disk that has to be encoded after or can they encode on-the-fly resulting in a optimised file written to disk?
It's important that the video is recorded at a lower resolution than the iPhone's advertised 720/1080p as I need to keep the file sizes down due to length of video (which will need to be uploaded).
Any information you have would be appreciated or even just a pointer in the right direction.
No they do not record uncompressed to disk (unless this is what you want). You can specify to record to a MOV/MP4 and have the video encoded in H264. Additionally you can control the average bit rate of the encoding. You can also specify the capture size, and output encoding size along with scaling options if needed. For demo code check out AVCamDemo in the WWDC 2010 sample code. This demo code may now be available in the docs.