Real-time Video Encoding on FPGAs¶
High quality and efficient video encoding is critical for modern video streaming services. Bodo and Xilinx are collaborating on a video encoding solution called Efficient Elastic Ensemble (E3) that provides high quality encoding in real-time at a fraction of total cost of ownership (TCO) of existing solutions. E3 combines the simplicity of Python and efficiency of FPGA encoding using Bodo’s automatic parallelization, workload distribution, and accelerator management.
The figure below demonstrates the components of this solution:
The video application is written in standard Python code without any API changes.
The Bodo compiler recognizes the operations that can be offloaded to FPGAs and generates optimized FPGA-enabled parallel code.
The Bodo runtime manages data and computation across the FPGAs in the compute cluster.
The compute cluster can have any number of FPGAs which are fully managed by Bodo elastically.
A simple E3 program has the following structure:
Load input video file
Process and encode the video
Write output video to file
Here is an example using Numpy to load an uncompressed video:
@bodo.jit def process_video(raw_input_filename, encoded_output_filename): # load data data = np.fromfile(raw_input_filename, np.uint8) # reshape to array of frames data = data.reshape(len(data) // FRAME_SIZE, FRAME_SIZE) # compute output video result = ... # write output video result.tofile(encoded_output_filename)
This program is written as regular sequential Python and is parallelized automatically by the JIT compiler. This enables fully elastic and scalable execution due to Bodo’s transformations:
Bodo splits the input file read (
np.fromfile) across processors to provide scalable I/O.
The reshape operation (
data.reshape) is performed in parallel while handling the frame boundaries properly.
Computation is parallelized and offloaded to FPGA devices automatically.
The output is written to a file in parallel (
result.tofile), which essentially “stitches” the data chunks together.
To execute a E3 program all you need to do is execute your normal Python program in MPI and indicate the number of processes you want.
For example to use 8 processes, you would execute the command:
mpiexec -n 8 python -u E3.py video_args
The components of this command are:
mpiexec -n 8- Create 8 MPI processes.
python -u E3.py video_args- Execute your python program using the MPI processes.
This page will include more details of supported APIs and operations as incorporated in future versions of Bodo.