Once in a while on our forum, somebody asks why the CPU usage isn't at 100% when encoding. I recently took the time to provide a thorough answer, which I think would be beneficial posted here.So first, let's explore what's happening when encoding a media file using Expression Encoder. The encoding process involves 5 phases: Reading the source(s) from storage.
Demuxing and decoding the source(s) into uncompressed frames.
Pre-processing the frames (deinterlacing, resizing, cropping, etc).
Encoding and muxing the frames.
Writing the stream to storage.If any one of those operations is slower than the others, all the encoding pipeline will suffer in terms of performance because it will bottleneck the flow of frames into it. #1 and #5 are usually the bottleneck when source files are either not local (aka slow Network share) or are very high-bandwidth coupled with a slow storage. Possible solutions: making sure the source files are copied locally on your fastest storage available and outputting to a different local storage are good solutions to reduce the bottleneck in those two areas. #2 usually becomes a bottleneck because of the type of sources and the codecs used to decode them. Obviously, using complex HD sources will use significantly more resources than simple lower-resolution sources. Some 3rd party codecs are extremely slow, running only on one core. Trying to test other codecs available on the PC by disabling some of the codecs listed in the "Tools -> Options -> Compatibility" dialog may help reducing the bottleneck. It's also worth noting that because many codecs are single-thread, having faster cores can help enormeously here. This is the main reason why a 3.4MHz 4-core is faster than a 2.6MHz 8-core PC in many cases. Read more: Expression Encoder
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Demuxing and decoding the source(s) into uncompressed frames.
Pre-processing the frames (deinterlacing, resizing, cropping, etc).
Encoding and muxing the frames.
Writing the stream to storage.If any one of those operations is slower than the others, all the encoding pipeline will suffer in terms of performance because it will bottleneck the flow of frames into it. #1 and #5 are usually the bottleneck when source files are either not local (aka slow Network share) or are very high-bandwidth coupled with a slow storage. Possible solutions: making sure the source files are copied locally on your fastest storage available and outputting to a different local storage are good solutions to reduce the bottleneck in those two areas. #2 usually becomes a bottleneck because of the type of sources and the codecs used to decode them. Obviously, using complex HD sources will use significantly more resources than simple lower-resolution sources. Some 3rd party codecs are extremely slow, running only on one core. Trying to test other codecs available on the PC by disabling some of the codecs listed in the "Tools -> Options -> Compatibility" dialog may help reducing the bottleneck. It's also worth noting that because many codecs are single-thread, having faster cores can help enormeously here. This is the main reason why a 3.4MHz 4-core is faster than a 2.6MHz 8-core PC in many cases. Read more: Expression Encoder
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