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  1. Emby Learn
  2. Media hardware acceleration
  3. Hardware pipelines and their limits
  4. Why hardware acceleration can still use the CPU
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    Why hardware acceleration can still use the CPU

    CPU activity during accelerated media processing can come from unaccelerated stages, host coordination and concurrent work, so its meaning depends on the complete selected workload.

    Hardware acceleration assigns supported work to particular device paths. The application and other media stages still have work on the CPU.

    A high overall CPU number therefore needs a workload explanation before it becomes evidence that hardware decoding or encoding failed.

    Identify the CPU’s tasks

    Work Possible CPU contribution
    Container and packet handling Source reads, parsing and stream selection
    Audio processing Selected decode, channel processing or encoding
    Subtitle/picture work A selected CPU renderer or filter
    Device coordination Submission, queues, callbacks and resource handling
    Delivery Packaging, temporary output and request handling
    Other server activity Concurrent jobs and library/system work

    NVIDIA's decoder documentation, for example, separates its software parser from the dedicated reconstruction engine. An application can consequently perform CPU parsing while NVDEC is doing its selected decode work.

    An original CPU-work diagram relates host responsibilities to accelerated video stages without equating total utilization with one codec operation.

    Small per-picture work can accumulate

    Use an original model with eight milliseconds of CPU work per picture at thirty pictures per second:

    0.008 CPU seconds × 30 pictures = 0.24 CPU seconds per wall second
    

    If the modeled work uses one core at a time, it is about 24% of one core's time. Four equivalent independent jobs request 0.96 core-seconds per wall second.

    On an ideal eight-core total-time denominator, that is 12% aggregate CPU time. The actual reporting convention, scheduling and extra work determine a real utilization display.

    The numbers are invented. They show why a per-picture cost, a per-core percentage and a machine-total percentage should not be interchanged.

    Observation scope by stage

    Evidence What it establishes
    Hardware encoder successfully initialized Selected output encoder path
    Hardware decoder produces pictures Selected reconstruction progress
    CPU filter appears in the graph A picture-processing path needing its CPU contract
    Total CPU utilization is high Combined activity under that reporting interval
    Conversion falls below playback rate Deficit somewhere in the complete producer route

    A hardware encoder name does not prove every upstream operation used hardware. Conversely, total CPU utilization does not erase a successfully running hardware stage.

    Preserve the compared workload

    An Emby session with a newly selected burn-in subtitle can introduce CPU picture work while keeping the same hardware decoder and encoder.

    Changing simultaneous jobs or output dimensions also changes demand. Compare the same source, selected tracks, target and job count before assigning the difference to acceleration.

    Transcoding logs supply operation and progress evidence that can be related to the observation interval.

    See Also

    • Mixed hardware and software filtering
    • Copy-back video pipelines
    • Concurrent encoder sessions, policy and capacity
    • Hardware acceleration in Emby Server
    • Reading a transcoding log
    • Concurrent playback workloads

    References

    • Emby: Hardware acceleration overview
    • NVIDIA SDK 13.1: NVDEC programming guide
    • NVIDIA SDK 13.1: NVENC programming guide
    • FFmpeg: Hardware devices and processing
    • FFmpeg: Hardware and software filters
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