Files
rocm-systems/projects/rocdecode/docs/rocDecodeUserGuide.md
T
Lakshmi Kumar e9ae320fc3 WIP: Docs - User Guide (#177)
* user guide intial

* clean up

* review comments

* clean up

* clean up

* review comments + new smaples section

[ROCm/rocdecode commit: 2e2f1e3f21]
2024-01-16 13:28:55 -08:00

5.2 KiB

rocDecode User Guide

Contents

Chapter 1 Overview

1.1 Supported Codecs

Chapter 2 Decoder Capabalities

Chapter 3 Decoder Pipeline

Chapter 4 Using rocDecode API

4.1 Video Parser
4.2 Querying decode capabilities
4.3 Creating a Decoder
4.4 Decoding the frame
4.5 Preparing the decoded frame for further processing
4.6 Getting data buffer
4.7 Querying the decoding status
4.8 Reconfiguring the decoder
4.9 Destroying the decoder

Chapter 5 Samples

5.1 Video Decode
5.2 Video Decode Performance
5.3 Video Decode Fork
5.4 Video Decode Memory
5.5 Video Decode Multiple Files
5.6 Video Decode RGB

Chapter 1 Overview

AMD GPUs contain one or more hardware decoders as separate engines (VCNs) that provide fully accelerated hardware based video decoding. Hardware decoders consume lower power than CPU based decoders. Dedicated hardware decoders offload decoding tasks from CPU, boosting overall decoding throughput. And with proper power management, decoding on hardware decoders can lower the overall system power consumption.

This document describes AMDs rocDecode SDK which provides APIs, allowing the developers to access the video decoding features of VCNs and allows interoperability with other compute engines on the GPU. rocDecode API facilitates decoding of the compressed video streams and keeps the resulting YUV frames in video memory. With decoded frames in video memory, video post processing can be done using ROCm HIP, thereby avoiding unnecessary data copies via PCIe bus. The video frames can further be post-processed using scaling/color-conversion and augmentation kernels (on GPU or host) and be in a format for GPU/CPU accelerated inferencing/training.

In addition, rocDecode API can be used to create multiple instances of video decoder based on the number of available VCN engines in a GPU. By configuring the decoder for a device, all the available engines can be used seamlessly for decoding a batch of video streams in parallel.

1.1 Supported Codecs

The codecs currently supported by rocDecode are:

  • HEVC/H.265 (8 bit and 10 bit)

Future versions of the SDK will support:

  • H.264/AVC (8 bit)
  • AV1

Chapter 2 rocDecode Hardware Capabilities

Table 1 shows the codec support and capabilities of the VCN for each GPU architecture supported by rocDecode.

GPU Architecture VCN Generation Number of VCNs H.265/HEVC Max width, Max height - H.265 H.264/AVC Max width, Max height - H.264
gfx908 - MI1xx VCN 2.5.0 2 Yes 4096, 2176 No 4096, 2160
gfx90a - MI2xx VCN 2.6.0 2 Yes 4096, 2176 No 4096, 2160
gfx940, gfx942 - MI3xx VCN 3.0 3 Yes 7680, 4320 No 4096, 2176
gfx941 - MI3xx VCN 3.0 4 Yes 7680, 4320 No 4096, 2176
gfx1030, gfx1031, gfx1032 - Navi2x VCN 3.x 2 Yes 7680, 4320 No 4096, 2176
gfx1100, gfx1102 - Navi3x VCN 4.0 2 Yes 7680, 4320 No 4096, 2176
gfx1101 - Navi3x VCN 4.0 1 Yes 7680, 4320 No 4096, 2176

Table 1: Hardware video decoder capabilities

Chapter 3 Decoder Pipeline

There are three main components Fig. 1 in the rocDecode: Demuxer, Video Parser APIs, and Video Decode APIs. The Demuxer is based on FFMPEG. The demuxer extracts a segment of video data and sends it to the Video Parser. The parser then extracts crucial information such as picture and slice parameters, which is then sent to the Decoder APIs. These APIs submit the information to the hardware for the decoding of a frame. This process repeats in a loop until all frames have been decoded.

Steps in decoding video content for applications (available in rocDecode Toolkit)

  1. Demultiplex the content into elementary stream packets (FFmpeg)
  2. Parse the demultiplexed packets into video frames for the decoder provided by rocDecode API.
  3. Decode compressed video frames into YUV frames using rocDecode API.
  4. Wait for the decoding to finish.
  5. Map the decoded YUV frame from amd-gpu context to HIP (using VAAPI-HIP under ROCm)
  6. Execute HIP kernels in the mapped YUV frame (e.g., format conversion, scaling, object detection, classification etc.)
  7. Un-map decoded HIP YUV frame.

The above steps are demonstrated in the sample applications included in the repository.

Chapter 4 Using rocDecode API

All rocDecode APIs are exposed in the two header files: rocdecode.h and rocparser.h. These headers can be found under api folder in this repository. \ The samples use the RocVideoDecoder user class provided in roc_video_dec.h under the utils folder in this repository.