Beamr’s Content Adaptive Bit Rate solution enables significantly decreasing video file size or bitrates without changing the video resolution or compromising perceptual quality. Since the optimized file is fully standard compliant, it can be used in your workflow seamlessly, whatever your use case, be it video streaming, playback or even part of an AI workflow.
Beamr first launched Beamr cloud earlier this year, and we are now super excited to announce that our valued partnership with Oracle Cloud Infrastructure (OCI) is enabling us to offer to OCI customers more features and better performance.
The performance improvements are due in part to the availability of the powerful NVIDIA L40S GPUs on OCI. In preliminary testing we found that running our video encoding workflows can be up to 30% faster when using these cards, than when running on the cards we currently use in the Beamr Cloud solution.
This was derived from testing AVC and HEVC NVENC driven encodes for a set of nine 1080p classic test clips with eight different configurations, and comparing encoding wall times on an A10G vs. a L40S GPU. Speedup factors of up to 55% were observed, with an average just above 30%. The full test data is available here.
Another exciting feature about these cards is that they support AV1 encoding, which means Beamr Cloud will now offer to turn your videos into optimized AV1 encodes, offering even higher bitrate/file size savings.
What’s the fuss about AV1?
In order to store and transmit video, substantial compression is needed. From the very earliest efforts to standardize video compression in the 90s, there has been a constant effort to create video compression standards offering increasing efficiency – meaning that the same video quality can be achieved with smaller files or lower bitrates.
As shown in the schematic illustration below, AV1 has come a long way in improving over H.264/AVC, the most widely adopted standard today, despite being 20 years old. However, the increased compression efficiency is not free – the computational complexity of newer codecs is also significantly higher, motivating the adoption of hardware accelerated encoding options.
With the demand and need for Video AI workflows continuing to rise, the ability to perform fully automatic, fast, efficient, optimized video encoding is an important enabler.
The Beamr GPU powered video compression and optimization occur within the GPU on OCI, right at the heart of these AI workflows, making them extremely well placed to offer benefits to such workflows. We have previously shown in a number of case studies that there is no negative impact on inference or training results when using the optimized files – making the integration of this optimization process into AI workflows a natural choice for cost savvy developers.
