Is there anything particular we should be aware of when trying to get the highest performance out of hardware decoding with low-latency streaming media? We're trying to run quite a few such decoding sessions in parallel (>10), and I seem to be noticing peculiar differences in the ability of the decoding to keep up depending on the management of the input MfxBitstream.
I had thought that circular buffer-style management of the bitstream read offset pointer (along with similar added write logic) would be an improvement over the method used in the example code, which involves a bitstream whose offset data is copied back to the starting offset as often as possible. It seems like only moving pointers would be much more efficient than constantly memcpying encoded video data -- but instead the best-performing solution we've found is a double-buffered approach, similar to the one used in the example except with a second input bitstream.
Any idea why this is the case? Is there some reason decoding operations perform better when they tend to start from the beginning of the MfxBitstream buffer, rather than at some offset along it?
And why does the guide recommend decoding all remaining frames from the input buffer before adding more? Shouldn't write operations appending to the end of a section of memory be transparent to the decoder, who is simply reading along it's own (earlier) section of memory? It's not as though there's any sort of inherent lock implemented in the bitstream data, since it's randomly accessible.
Again, this is all in a low-latency setup, with AsyncDepth set to 1 and the bitstream flag set to indicate a complete frame is available every time DecodeFrameAsync is called. Though increasing the AsyncDepth and clearing that flag don't seem to improve throughput at the expense of latency, as I would have expected. Maybe it's because of the large number of simultaneous decoding sessions, such that the hardware can't work on any one in parallel, anyway?
Any advice, insights, or assistance are appreciated!