Easy & Safe Codec Modernization with Beamr using Nvidia GPUs
Following a decade where AVC/H.264 was the clear ruler of the video encoding world, the last years have seen many video coding options battling to conquer the video arena. For some insights on the race between modern coding standards you can check out our corresponding blog post.
Today we want to share how easy it can be to upgrade your content to a new and improved codec in a fast, fully automatic process which guarantees the visual quality of the content will not be harmed. This makes the switchover to newer encoders a smooth, easy and low cost process which can help accelerate the adoption of new standards such as HEVC and AV1. When this transformation is done using a combination of Beamr’s technology with the Nvidia NVENC encoder, using their recently released APIs, it becomes a particularly cutting-edge solution, enjoying the benefits of the leading solution in hardware AV1 encoding.
The benefit of switching to more modern codecs lies of course in the higher compression efficiency that they offer. While the extent of improvement is very dependent on the actual content, bitrates and encoders used, HEVC is considered to offer gains of 30%-50% over AVC, meaning that for the same quality you can spend up to 50% fewer bits. For AV1 this increase is generally a bit higher.. As more and more on-device support is added for these newer codecs, the advantage of utilizing them to reduce both storage and bandwidth is clear.
Generally speaking, performing such codec modernization involves some non-trivial steps.
First, you need to get access to the modern encoder you want to use, and know enough about it in order to configure the encoder correctly for your needs. Then you can proceed to encoding using one of the following approaches.
The first approach is to perform bit-rate driven encoding. One possibility is to use conservative bitrates, in which case the potential reduction in size will not be achieved. Another possibility is to set target bitrates that reflect the expected savings, in which case there is a risk of losing quality. For example, In an experimental test of files which were converted from their AVC source to HEVC, we found that on average, a bitrate reduction of 50% could be obtained when using the Beamr CABR codec modernization approach. However, when the same files were all brute-force encoded to HEVC at 50% reduced bitrate, using the same encoder and configuration, the quality took a hit for some of the files.
This example shows the full AVC source frame on top, with the transcodes to HEVC below it. Note the distortion in the blind HEVC encode, shown on the left, compared to the true-to-source video transformed with CABR on the right.
The second approach is to perform the transcode using a quality driven encode, for instance using the constant QP (Quantization Parameter) or CRF (Constant Rate Factor) encoding modes with conservative values, which will in all likelihood preserve the quality. However, in this case you are likely to unnecessarily “blow up” some of your files to much higher bitrates. For example, for the UGC content shown below, transcoding to HEVC using a software encoder and CRF set to 21 almost doubled the file size.
Yet another approach is to use a trial and error encode process for each file or even each scene, manually verifying that a good target encoding setup was selected which minimizes the bitrate while preserving the quality. This is of course an expensive and cumbersome process, and entirely unscalable.
By using Beamr CABR this is all done for you under the hood, in a fully automatic process, which makes optimized choices for each and every frame in your video, selecting the lowest bitrate that will still perfectly preserve the source visual quality. When performed using the Nvidia NVENC SDK with interfaces to Beamr’s CABR technology, this transformation is significantly accelerated and becomes even more cost effective.
The codec modernization flow is demonstrated for AVC to HEVC conversion in the above high-level block diagram. As shown here, the CABR controller interacts with NVENC, Nvidia’s hardware video encoder, using the new APIs Nvidia has created for this purpose. At the heart of the CABR controller lies Beamr’s Quality Measure, BQM, a unique, patented, Emmy award winning perceptual video quality measure. BQM has now been adapted and ported to the Nvidia GPU platform, resulting in significant acceleration of the optimization process .
The Beamr optimization technology can be used not only for codec modernization, but also to reduce bitrate of an input video, or of a target encode, while guaranteeing the perceptual quality is preserved, thus creating encodes with the same perceptual quality at lower bitrates or file sizes. In any and every usage of the Beamr CABR solution, size or bitrate are reduced as much as possible while each frame of the optimized encode is guaranteed to be perceptually identical to the reference. The codec modernization use case is particularly exciting as it puts the ability to migrate to more efficient and sophisticated codecs, previously used primarily by video experts, into the hands of any user with video content.
For more information please contact us at info@beamr.com
The proliferation of AI-generated visual content is creating a new market for media optimization services, with companies like Beamr well positioned to help businesses optimize their video content for reduced storage, faster delivery, and better user experiences.
We are living in a brave new world, where any image and video content we can imagine is at our fingertips, merely a prompt and AI based content generation engine away. Platforms like Wochit, Synthesia, Wibbitz, and D-ID are using AI technology to automate the video creation process. Using these tools makes it almost trivial for businesses to create engaging video content at scale. These platforms allow users to create tailored content quickly and efficiently, with minimal time and cost.
Wochit, for example, offers a library of pre-made templates that users can customize with their own branding and messaging. The platform’s AI technology can also automatically generate videos from text, images, and video clips, making it easier for businesses to create engaging video content without needing specialized video production skills.
However, as businesses increasingly rely on AI-generated content to reach their audiences, and can create a multitude of ‘perfect fit’ videos, the struggle with storage and bit rates becomes a significant factor in their operations. When dealing with bandwidth gobbling video, companies need to ensure that their videos are optimized for fast delivery, high quality, and optimal user experiences. That’s where Beamr comes in.
Beamr’s technology uses advanced compression algorithms to automatically optimize image and video content for fast delivery over any network or device, without compromising quality. This means that you will get to keep the full look and feel of the content, and maintain standard compatibility, but reduce the file sizes or bitrates – without having to do anything manually. The underlying, patented and Emmy Award winning technology will guarantee that the perceptual quality is preserved while any unnecessary bits and bytes are removed. This allows businesses to deliver high-quality content that engages their audience and drives results, while also minimizing the impact on network resources and reducing storage and delivery costs.
To demonstrate the synergy between AI based video content generation and Beamr’s optimization technology we went to Wochit and created a magnificent video showcasing Ferrari above. We then applied the Beamr optimization technology, and received the reduced size perceptually identical optimized video, with file size down from the original 8.8MB to 5.4MB, offering saving of almost 38%.
For our next experiment we took the title of this blog, went to D-ID, and turned the text into a promotional video, using all the default settings. This resulted in the source video shared below.
With an easy drag & drop into the Beamr optimization utility, a completely equivalent video file – using the same codec, resolution and perceptual quality was obtained, except its size was reduced by 48%.
Image synthesis using AI is also becoming more and more common. Along with the already commonplace AI based image generators such as DALL-E (2), many additional platforms are becoming available including Midjourney, DreamStudio and Images.ai.
Feeling the tug of the Land-Down-Under we headed to https://images.ai/prompt/ and requested an image showing ‘a koala eating ice-cream’. The adorable result is shown below on the left. Then we put it through Beamr optimization software and obtained an image with the exact same quality, but reduced from the original 212 KB JPEG, to a mere 49 KB perceptually identical fully standard compliant JPEG image.
Original versionOptimized version
Beamr is also preparing to launch a new SaaS platform that leverages Nvidia’s accelerated video encoding technology, to further speed up the video optimization process. This will allow businesses to optimize their video content even faster than traditional video encoding services, giving them a competitive edge in the rapidly evolving market for AI-generated video content.
For businesses that use Wochit to create their videos, Beamr’s technology can be integrated into the delivery process, ensuring that the videos are optimized for fast delivery and high quality. This allows businesses to stay ahead of the curve in this rapidly evolving market, and keeps their audiences coming back for more. As the demand for AI-generated video content continues to grow, media optimization services like Beamr will become increasingly important for businesses that want to deliver high-quality image and video content that engages their audience and drives results ensuring that they stay ahead of the curve in this rapidly evolving market.
It has been two years since we published a comparison of the two leading HEVC software encoder SDKs; Beamr 5, and x265. In this article you will learn how Beamr’s AVC and HEVC software codec SDKs have widened the computing performance gap further over x264 and x265 for live broadcast quality streaming.
Why Performance Matters
With the performance of our AVC (Beamr 4) and HEVC (Beamr 5) software encoders improving several orders of magnitude over the 2017 results, it felt like the right time to refresh our benchmarks, this time with real-time operational data.
It’s no secret that x264 and x265 have benefited greatly, as open-source projects, from having thousands of developers working on the code. This is what makes x264 and x265 a very high bar to beat. Yet even with so many bright and talented engineers donating tens of thousands of development hours to the code base, the architectural constraints of how these encoders were built limit the performance on multicore processors as you will see in the data below.
Creative solutions have been developed which enable live encoding workflows to be built using open-source. But it’s no secret that they come with inherent flaws that include being overly compute intensive and encumbered with quality issues as a result of not being able to encode a full ABR stack, or even a single 4K profile, on a single machine.
The reason this matters is because the resolutions that video services deliver continues to increase. And as a result of exploding consumer demand for video, data consumption is consuming network bandwidth to the point that Cisco reports in 2022, 82% of Internet traffic will be video.
Cisco says in their Visual Networking Index that by 2022 SD resolution video will comprise just 23.4% of Internet video traffic, compared to the 60.2% of Internet video traffic that SD video consumed in 2017. What use to represent the middle-quality tier, 480p (SD), has now become the lowest rung of the ABR ladder for many video distributors.
1080p (HD) will makeup 56.2% of Internet video traffic by 2022, an increase from 36.1% in 2017. And if you thought the resolution expansion was going to end with HD, Cisco is claiming in 2022, 4K (UHD) will comprise 20.3% of all Internet-delivered video.
Live video services are projected to expand 15x between 2017 and 2022, meaning within the next three years, 17.1% of all Internet video traffic will be comprised of live streams.
These trends demonstrate the industry’s need to prepare for this shift to higher resolution video and real-time delivery with software encoding solutions that can meet the requirement for live broadcast quality 4K.
Blazing Software Performance on Multicore Processors
The Beamr 5 software encoder utilizes an advanced thread management architecture. This represents a key aspect of how we can achieve such fantastic speed over x265 at the same quality level.
x265 works by creating software threads and adding them to a thread pool where each task must wait its turn. In contrast, Beamr 5 tracks all the serial dependencies involved with the video coding tasks it must perform, and it creates small micro-tasks which are efficiently distributed across all of the CPU cores in the system. This allows the Beamr codec to utilize each available core at almost 100% capacity.
All tasks added to the Beamr codec thread pool may be executed immediately so that no hardware thread is wasted on tasks where the data is not yet available. Interestingly, under certain conditions, x265 can appear to have higher CPU utilization. But, this utilization includes software threads which are not doing any useful work. This means they are “active” but not processing data that is required for the encoding process.
Adding to Beamr encoders thread efficiency, we have implemented patented algorithms for more effective and efficient video encoding, including a fast motion estimation process and a heuristic early-termination algorithm which enables the encoder to reach a targeted quality using fewer compute resources (cycles). Furthermore, Beamr encoders utilize the latest AVX-512 SIMD instruction set for squeezing even more performance out of advanced CPUs.
The end result of the numerous optimizations found in the Beamr 4 (AVC) and Beamr 5 (HEVC) software encoders is that they are able to operate nearly twice as fast as x264 and x265 at the same quality, and with similar settings and tools utilization.
Video streaming services can benefit from this performance advantage in many ways, such as higher density (more channels per server) which reduces operational costs. To illustrate what this performance advantage can do for you- consider that at the top-end, Beamr 5 is able to encode 4K, 10-bit video at 60 FPS in real-time using just 9 Intel Xeon Scalable cores where x265 is unable to achieve this level of performance with any number of computing cores (at least on a single machine). And, as a result of being twice as efficient, Beamr 4 and Beamr 5 can deliver higher quality at the same computing envelope as x264 and x265.
The Test Results
For our test to be as real-world as possible, we devised two methodologies. In the first, we measured the compute performance of an HEVC ABR stack operating both Beamr 5 and x265 at live speed. And for the second test, our team measured the number of simultaneous live streams at 1080p, comparing Beamr 4 with x264, and Beamr 5 with x265; and for 4K comparing Beamr 5 with x265. All tests were run on a single machine.
Live HEVC ABR Stack: Number of ABR Profiles (Channels)
This test was designed to find the maximum number of full ABR channels which can be encoded live by Beamr 5 and x265 on an AWS EC2 c5.24xlarge instance.
Each AVC channel comprises 4 layers of 8-bit 60 FPS video starting from 1080p, and the HEVC channel comprises either 4 layers of 10-bit 60 FPS video (starting from 1080p), or 5 layers of 10-bit 60 FPS video (starting from 4K).
Live HEVC ABR Stack Test – CONFIGURATION
Platform:
AWS EC2 c5.24xlarge instance
Intel Xeon Scaleable Cascade Lake @ 3.6 GHz
48 cores, 96 threads
Presets:
Beamr 5: INSANELY_FAST
x265: ultrafast
Content: Netflix 10-bit 4Kp60 sample clips (DinnerScene and PierSeaside)
Encoded Frame Rate (all layers): 60 FPS
Encoded Bit Depth (all layers): 10-bit
Encoded Resolutions and Bitrates:
4Kp60@18000 Kbps (only in 4K ABR stack)
1080p60@3750 Kbps
720p60@2500 Kbps
576p60@1250 Kbps
360p@625 Kbps
Live HEVC ABR Stack Test – RESULTS
NOTES:
(1) When encoding 2 full ABR stacks with Beamr 5, 25% of the CPU is unused and available for other tasks.
(2) x265 cannot encode even a single 4K ABR stack channel at 60 FPS. The maximum FPS for the 4K layer of a single 4K ABR stack channel using x265 is 35 FPS.
Live AVC & HEVC Single-Resolution: Number of Channels (1080p & 4K)
In this test, we are trying to discover the maximum number of single-resolution 4K and HD channels that can be encoded live by Beamr 4 and Beamr 5 as compared with x264 and x265, on a c5.24xlarge instance. As with the Live ABR Channels test, the quality between the two encoders as measured by PSNR, SSIM and VMAF was always found to be equal, and in some cases better with Beamr 4 and Beamr 5 (see the “Quality Results” section below).
Live AVC Beamr 4 vs. x264 Channels Test – CONFIGURATION
Platform:
AWS EC2 c5.24xlarge instance
Intel Xeon Scaleable Cascade Lake @ 3.6 GHz
48 cores, 96 threads
Speeds / Presets:
Beamr 4: speed 3
x264: preset medium
Content: Netflix 10-bit 4Kp60 sample clips (DinnerScene and PierSeaside)
Encoded Frame Rate (all channels): 60 FPS
Encoded Bit Depth (all channels): 8-bit
Channel Resolutions and Bitrates:
1080p60@5000 Kbps
Live AVC Beamr 4 vs. x264 Channels Test – RESULTS
Live HEVC Beamr 5 vs. x265 Channels Test – CONFIGURATION
Platform:
AWS EC2 c5.24xlarge instance
Intel Xeon Scaleable Cascade Lake @ 3.6 GHz
48 cores, 96 threads
Speeds / Presets:
Beamr 5: INSANELY_FAST
x265: ultrafast
Content: Netflix 10-bit 4Kp60 sample clips (DinnerScene and PierSeaside)
Encoded Frame Rate (all channels): 60 FPS
Encoded Bit Depth (all channels): 10-bit
Channel Resolutions and Bitrates:
4K@18000 Kbps
1080p60@3750 Kbps
Live HEVC Beamr 5 vs. x265 Channels Test – RESULTS
NOTES:
(1) x265 was unable to reach 60 FPS for a single 4K channel, achieving just 35 FPS at comparable quality.
Quality Comparisons (PSNR, SSIM, VMAF)
Beamr 5 vs. x265
NOTES:
As previously referenced, x265 was unable to reach 4Kp60 and thus PSNR, SSIM, and VMAF scores could not be calculated, hence the ‘N/A’ designation in the 3840×2160 cells.
Video engineers are universally focused on the video encoding pillars of computing efficiency (performance), bitrate efficiency, and quality. Even as technology has enabled each of these pillars to advance with new tool sets, it’s well known that there is still a tradeoff between each that is required.
On one hand, bitrate efficiency requires tools that sap performance, and on the other hand, to reach a performance (speed) target, tools which could positively affect quality cannot be used without harming the performance characteristics of the encoding pipeline. As a result, many video encoding practitioners have adapted to the reality of these tradeoffs and simply accept them for what they are. Now, there is a solution…
The impact of adopting Beamr 4 for AVC and Beamr 5 for HEVC transcends a TCO calculation. With Beamr’s high-performance software encoders, services can achieve bitrate efficiency and performance, all without sacrificing video quality.
The use of Beamr 4 and Beamr 5 opens up improved UX with an increase in resolution or frame-rate which means it is now possible for everyone to stream higher quality video. As the competitive landscape for video delivery services continues to evolve, never has the need been greater for an AVC and HEVC codec implementation that can deliver the best of all three pillars: performance, bitrate efficiency, and quality. With the performance data presented above, it should be clear that Beamr 4 and Beamr 5 continue to be the codec implementations to beat.
Going Inside Beamr’s Frame-Level Content-Adaptive Rate Control for Video Coding
When it comes to video, the tradeoff between quality and bitrate is an ongoing dance. Content producers want to maximize quality for viewers, while storage and delivery costs drive the need to reduce bitrate as much as possible. Content-adaptive encoding addresses this challenge, by striving to reach the “optimal” bitrate for each unique piece of content, be it a full clip or a single scene. Our CABR technology takes it a step further by adapting the encoding at the frame level. CABR is a closed-loop content-adaptive rate control mechanism enabling video encoders to lower the bitrate of their encode, while simultaneously preserving the perceptual quality of the higher bitrate encode. As a low-complexity solution, CABR also works for live or real-time encoding.
All Eyes are on Video
According to Grand View Research, the global video streaming market is expected to grow at a CAGR of 19.6% from 2019 to 2025. This shift, fueled by the increasing popularity of direct-to-consumer streaming services such as Netflix, Amazon and Hulu, the growth of video on social media networks and user-generated video platforms such as Facebook and YouTube, and other applications like online education & video surveillance, has all eyes on video workflows. Therefore, efficient video encoding, in terms of encoding and delivery costs, and meeting the viewer’s rising quality expectations, are at the forefront of video service provider’s minds. Beamr’s CABR solution can reduce bitrates without compromising quality while keeping a low computational overhead to enhance video services.
Comparing Content-Adaptive Encoding Solutions
Instead of using fixed encoding parameters, content-adaptive encoding configures the video encoder according to the content of the video clip to reach the optimal tradeoff between bitrate and quality. Various content-adaptive encoding techniques have been used in the past to provide a better user experience with reduced delivery costs. Some of them have been entirely manual, where encoding parameters are hand-tuned for each content category and sometimes, like in the case of high-volume Blu-ray titles, at the scene level. Manual content-adaptive techniques are restricted in the sense that they can’t be scaled, and they don’t provide granularity lower than the scene level.
Other techniques, such as those used by YouTube and Netflix, use “brute force” encoding of each title by applying a wide range of encoding parameters, and then by employing rate-distortion models or machine learning techniques, try to select the best parameters for each title or scene. This approach requires a lot of CPU resources since many full encodes are performed on each title, at different resolutions and bitrates. Such techniques are suitable for diverse content libraries that are limited in size, such as premium content including TV series and movies. These methods do not apply well to vast repositories of videos such as user-generated content, and are not applicable to live encoding.
Beamr’s CABR solution is different from the techniques described above in that it works in a closed-loop and adapts the encoding per frame. The video encoder first encodes a frame using a configuration based on its regular rate control mechanism, resulting in an initial encode. Then, Beamr’s CABR rate control instructs the encoder to encode the same frame again with various values of encoding parameters, creating candidate encodes. Using a patented perceptual quality measure, each candidate encode is compared with the initial encode, and then the best candidate is selected and placed in the output stream. The best candidate is the one that has the lowest bitrate but still has the same perceptual quality as the initial encode.
Taking Advantage of Beamr’s CABR Rate Control
In order for Beamr’s CABR technology to encode video to the minimal bitrate and still retain the perceptual quality of a higher bitrate encode, it compresses each video frame to the maximum extent that provides the same visual quality when the video is viewed in motion. Figure 1 shows a block diagram of an encoding solution which incorporates CABR technology.
Figure 1 – A block diagram of the CABR encoding solution
An integrated CABR encoding solution consists of a video encoder and the CABR rate control engine. The CABR engine is comprised of the CABR control module responsible for managing the optimization process and a module which evaluates video quality.
As seen in Figure 2, the CABR encoding process consists of multiple steps. Some of these steps are performed once for each encoding session, some are performed once for each frame, and some are performed for each iteration of candidate frame encoding. When starting a content-adaptive encoding session, the CABR engine and the encoder are initialized. At this stage, we set system-level parameters such as the maximum number of iterations per frame. Then, for each frame, the encoder rate control module selects the frame types by applying its internal logic.
Figure 2. A block diagram of a video encoder incorporating Content Adaptive Bit-Rate encoding.
The encoder provides the CABR engine with each original input frame for pre-analysis within the quality measure calculator. The encoder performs an initial encode of the frame, using its own logic for bit allocation, motion estimation, mode selections, Quantization Parameters (QPs), etc. After encoding the frame, the encoder provides the CABR engine with the reconstructed frame corresponding to this initially encoded frame, along with some side information – such as the frame size in bits and the QP selected for each MacroBlock or Coding Tree Unit (CTU).
In each iteration, the CABR control module first decides if the frame should be re-encoded at all. This is done, for example, according to the frame type, the bit consumption of the frame, the quality of previous frames or iterations, and according to the maximum number of iterations set for the frame. In some cases, the CABR control module may decide not to re-encode a frame at all – in that case, the initial encoded frame becomes the output frame, and the encoder continues to the next frame. When the CABR control module decides to re-encode, the CABR engine provides the encoder with modified encoding parameters, for example, a proposed average QP for the frame, or the difference from the QP used for the initial encode. Note that the QP or delta QP values are an average value, and QP modulation for each encoding block can still be performed by the encoder. In more sophisticated implementations a QP map of value per encoding block may be provided, as well as additional encoder configuration parameters.
The encoder performs a re-encode of the frame with the modified parameters. Note that this re-encode is not a full encode, since it can utilize many encoding decisions from the initial encode. In fact, the encoder may perform only re-quantization of the frame, reusing all previous motion vectors and mode decisions. Then, the encoder provides the CABR engine with the reconstructed re-encoded frame, which becomes one of the candidate frames. The quality measure module then calculates the quality of the candidate re-encoded frame relative to the initially encoded frame, and this quality score, along with the bit consumption reported by the encoder is provided to the CABR control module, which again determines if the frame should be re-encoded. When that is the case, the CABR control module sets the encoding parameters for the next iteration, and the above process is repeated. If the control module decides that the search for the optimal frame parameters is complete, it indicates which frame, among all previously encoded versions of this frame, should be used in the output video stream. Note that the encoder rate control module receives its feedback from the initial encode of the current frame, and in this way the initial encode of the next frames (which determines the target quality of the bitstream) is not affected.
The CABR engine can operate in either a serial iterative approach or a parallel approach. In the serial approach, the results from previous iterations can be used to select the QP value for the next iteration. In the parallel approach, all candidate QP values are provided simultaneously and encodes are done in parallel – which reduces latency.
Integrating the CABR Engine with Software & Hardware Encoders
Beamr has integrated the CABR engine into its AVC software encoder, Beamr 4, and into its HEVC software encoder, Beamr 5. However, the CABR engine can be integrated with any software or hardware video encoder, supporting any block-based video standard such as MPEG-2, AVC, HEVC, EVC, VVC, VP9, and AV1.
To integrate the CABR engine with a video encoder, the encoder should support several requirements. First and foremost, the encoder should be able to re-encode an input frame (that has already been encoded) with several different encoding parameters (such as QP values), and save the “state” of each of these encodes, including the initial encode. The reason for saving the state is that when the CABR control module selects one of the candidate frame encodes (or the initial encode) as the one to use in the output stream, the encoder’s state should correspond to the state it was right after encoding that candidate frame. Encoders that support multi-threaded operation and hardware encoders typically have this capability, since each frame encode is performed by a stateless unit.
Second, the encoder should support an interface to provide the reconstructed frame and the per block QP and bit consumption information for the encoded frame. To improve compute performance, we also recommend that the encoder supports a partial re-encode mode, where information related to motion estimation, partitioning and mode decisions found in the initial encode can be re-used for re-encoding without being computed again, and only the quantization and entropy coding stages are repeated for each candidate encode. This results in a minimal encoding efficiency drop for the optimized encoding result, with significant speed-up compared to full re-encode. As described above, we recommend that the encoder will use the initial encoded data (QPs, compressed size, etc.) for its Rate Control state update. However, the selected frame and accompanying data must be used for reference frames and other reference data, such as temporal MV predictors, as it is the only data available in the bitstream for decoding.
When integrating with hardware encoders that support parallel encoding with no increase in latency, we recommend using the parallel search approach where multiple QP values per frame are evaluated simultaneously. If the hardware encoder can perform parallel partial encodes (for example, re-quantization and entropy coding only), while all parallel encodes use the analysis stage of the initial encode, such as motion estimation and mode decisions, better CPU performance will be achieved.
Sample Results
Below, we provide two sample results of the CABR engine, when integrated with Beamr 5, Beamr’s HEVC software encoder, each illustrating different aspects of CABR.
For the first example, we encoded various 4K 24 FPS source clips to a target bitrate of 10 Mbps. Sample frames from each of the clips can be seen in Figure 3. The clips vary in their content complexity: “Crowd Run” has very high complexity since it has great detail and very significant motion of the runners. “StEM” has medium complexity, with some video compression challenges such as different lighting conditions and reasonably high film grain. Finally, a promotional clip of JPEGmini by Beamr has low complexity due to relatively low motion and simple scenes.
Figure 3. Sample frames from the test clips. top: crowd-run, bottom left: StEM bottom right: JPEGmini.
We encoded 500 frames from each clip to a target bitrate of 10 Mbps, using the VBR mode of the Beamr 5 HEVC encoder, which performs regular encoding, and using the CABR mode, which creates a lower bit-rate, perceptually identical stream. For the high complexity clip “Crowd Run,” where providing excellent quality at such an aggressive bitrate is very challenging, CABR reduced the bitrate by only 3%. For the intermediate complexity clip “StEM,” bitrate savings were higher and reached 17%. For the lowest complexity clip “JPEGmini,” CABR reduced the bitrate by a staggering 45%, while still obtaining excellent quality which matches the quality of the 10 Mbps VBR encode. This extensive range of bitrate reduction percentage demonstrates the fully automatic content-adaptive nature of CABR-enhanced encoder, which reaches a different final bitrate, according to the content complexity.
The second example uses a 500 frame 1080p 24 FPS clip from the well-known “Tears Of Steel” movie by the Blender open movie project. The same clip was encoded using the VBR and CABR modes of the Beamr 5 HEVC software encoder, with three target bitrates: 1.5, 3 and 5 Mbps. Savings, in this case, were 13% for the lowest bitrate resulting in a 1.4 Mbps encode, 44% for the intermediate bitrate resulting in an encode of 1.8 Mbps, and 62% for the highest bitrate, resulting in a 2 Mbps encode. Figures 4 and 5 show sample frames from the encoded clips with VBR encoding on the left vs. CABR encoding on the right. The top two images are from encodes to a bitrate of 5 Mbps, while the bottom two were taken from the 1.5 Mbps encodes. As can be seen here, both 5 Mbps target encodes preserve the details, such as the texture of the bottom lip or the two hairs on the forehead above the right eye, while in the lower bitrate encodes these details are somewhat blurred. This is the reason that when starting from different target bitrates, CABR does not converge to the same bitrate. We also see, however, that the more generous the initial encoding, generally the more savings can be obtained. This example shows that CABR adapts not only to the content complexity, but also to the quality of the target encode, and preserves perceptual quality in motion while offering significant savings.
Figure 4. A sample from the “Tears of Steel” 1080p 24 FPS encode to 5 Mbps (top) and 1.5 Mbps (bottom), encoded in VBR mode (left) and CABR mode (right)
Figure 5. Closer view of the face in Figure 4, showing detail of lips and forehead from the encode to 5 Mbps (top) and 1.5 Mbps (bottom), encoded in VBR mode (left) and CABR mode (right).
At the 2018 Consumer Electronics Show, video hardware manufacturers came out swinging on the innovation front—including 8K TVs and a host of whiz-bang UX improvements—leading to key discussions around the business and economic models around content and delivery.
On the hardware side, TV has dominated at CES, with LG and Samsung battling it out over premium living room gear. LG, in addition to debuting a 65-inch rollable OLED screen, made headlines with its announcement of an 88-inch 8K prototype television. It’s backed by the new Alpha 9 intelligent processor, which provides seven times the color reproduction over existing models, and can handle up to 120 frames per second for improved gaming and sports viewing.
Not to be outdone, Samsung has debuted its Q9S 8K offering (commercially available in the second half of the year), featuring an 85-inch screen with built-in artificial intelligence that uses a proprietary algorithm to continuously learn from itself to intelligently upscale the resolution of the content it displays — no matter the source of that content.
The Korean giant also took the wraps off of what it is calling “the Wall,” which, true to its name, is an enormous 146-inch display. It’s not 8K, but it’s made up of micro LEDs that it says will let consumers “customize their television sizes and shapes to suit their needs.” It also said that its newest TVs will incorporate its artificial digital assistant Bixby and a universal programming guide with AI that learns your viewing preferences.
It’s clear that manufacturers are committed to upping their games when it comes to offering better consumer experiences. And it’s not just TVs that are leading this bleeding edge of hardware development: CES has seen announcements around 4K VR headsets (HTC), video-enabled drones, cars that can utilize a brain-hardware connection to tee up video-laden interactive apps, and a host of connected home gadgets—all of which will be driving the need for a combination of reliable hardware platforms, content availability and, perhaps above all, a positive economic model for content delivery.
This year CES provided a view into the next generation of video entertainment possibilities that are in active development. But it will all be for naught if content producers and distributors don’t have reliable and scalable delivery networks for compatible video, where costs don’t spiral out of control as the network becomes more content-intensive. For instance, driving down the bitrate requirements for delivering, say, 8K, whether it’s in a pay-TV traditional operator model or on an OTT basis, will be one linchpin for this vision of the future.
We’re committed to making sure we are in the strongest position to bring our extensive codec development resources to bear on this ecosystem. HEVC, for instance, is recognized to be 40 to 50 percent more efficient for delivering video than legacy format, AVC H.264. With Beamr’s advanced encoding offerings, content owners can optimize their encoding for reduced buffering, faster start times, and increased bandwidth savings.
We’re also keeping an eye on the progression of the Alliance for Open Media (AOMedia)’s AV1 codec standard, which recently added both Apple and Facebook to its list of supporters. It hopes to be up to 30 percent more efficient than HEVC, though it’s very much in the development stages.
We’re excited about the announcements coming out of CES this year, and the real proof that the industry is well on its way to delivering an exponential improvement on the consumer video experience. We also look forward to helping that ecosystem mature and doing our part to make sure that innovation succeeds, for 8K in the living room and very much beyond.
It’s no secret that Intel-based hardware is ubiquitous in many video encoding data centers, which explains the high level of interest in the new Intel® Xeon® Scalable Platinum processor family. This article examines the live HEVC 4Kp60 10-bit encoding performance from the perspective of speed with Beamr 5 running on the scalable Platinum 8180 where the results are nothing short of amazing.
Intel is known for pushing the state of art with ever faster and more capable processors, which enable software encoding vendors like Beamr to achieve performance benchmarks some thought impossible. Since Intel’s announcement of their new processor series, Beamr has been excited to see what is possible with the version 5 Xeon® processor.
The result?
Mind-blowing.
Video services needing to encode live 4Kp60 10-bit HDR video can achieve 6 simultaneous streams on a dual-socket Intel® Xeon® Scalable Platinum 8180 processor using Beamr 5 v4.1. This performance represents a 6x speed advantage over x265 and establishes an entirely new benchmark for HEVC software encoders.
CLICK HERE for a speed comparison of the Beamr 5 HEVC software encoder and x265 running on Amazon EC2.
Executive Introduction
As over-the-top (OTT) and IP overtake traditional linear delivery systems, the ability to encode video on software, in real time, is now a requirement.
According to Cisco, consumer Video-on-Demand (VoD) traffic will almostdouble by 2021. This trend is driven largely by new video services and entertainment formats such as Cloud DVR, UHD (4K), High Dynamic Range (HDR) and 360 degree AR/VR immersive video. These advanced video formats carry with them much greater encoding complexity which places high operational demands on the computing environment. This means more efficient software requires less server time which translates to fewer machines and lower capex and opex.
With content and operational costs rising, and end user pricing under pressure, it is essential for operators to invest in video encoding technology that can provide advanced services in the most efficient way possible. As NFV and virtualized container based architectures advance in the data center, encoding density and speed is becoming a critical vector within the encoder selection process. Also, the ability to operate across a wide range of general purpose platforms is essential. Many GPU bound solutions are inextricably linked to a single processor or limited series. Beamr’s HEVC encoder scales across the entire Intel® Xeon® family.
Apple is playing a pivotal role in enabling the HEVC ecosystem starting with iOS 11 and High Sierra. It is estimated that up to 1 billion devices in the Apple ecosystem can now play HEVC without any special update or third-party apps needed. With HEVC files now supported from big screens to mobile devices, video services can transition their entire library with all resolutions to HEVC, and benefit from the reduced bitrate and improved quality that HEVC is able to deliver. This represents hundreds of thousands if not millions of hours of content needing to be encoded by each video distributor.
With Beamr 5 running on an Intel® Xeon® Scalable processor, video encoding engineers can perform up to 6 times more live video encoding, which leads to a reduction in:
The new Beamr 5 HEVC software encoder exploits multiple features of the Intel® Xeon® Scalable platform, making it possible to deliver the performance of hardware with the scale and flexibility that only software allows. Beamr 5 is able to utilize the entire range of Intel® Xeon® processors from the entry-level Intel® Xeon® Processor E3 v5 family to the best in class Intel® Xeon® Platinum Scalable 8180 processor. For real-time live video encoding operations that require resolutions up to 4K and frame rates as high as 60 FPS, higher performance means less computing resources required.
Solutions like Beamr 5 running on Intel® Xeon® Scalable Platinum processors contribute to decidedly lower operational and capital investment costs.
In addition to the live workflow benefits, offline VoD applications can also benefit from greater performance as the shorter turnaround time to complete VoD encodes and transcodes means the content will be available for distribution more quickly.
Beamr 5 opens up compelling options for MSOs, CDNs, and broadcasters to build video workflows that exceed their service expansion plans and technical goals while also enabling service operators to deploy media processing workflows across public clouds and on-premise data centers.
With Beamr 5 running on Intel® Xeon® processors, new video encoding workflows can be imagined as edge encoding services running Intel® Xeon® E3 processor-based points of presence (PoPs) for JIT transcoding are now possible. The high performance of Beamr 5 directly enables workflows to be split and re-deployed without a need to redesign workflows.
Beamr’s Next-Generation Video Encoding Technology on Intel
At the foundation of Beamr’s HEVC software encoder is technology that stems from more than a dozen years of codec development by our codec engineering team. Though we’ve developed our solution and technical advantages entirely in-house, working closely with Intel gives us a significant technical and business advantage.
Of the many points related to how we achieved our massive speed advantage, the two we will highlight are motion estimation advantage and micro-level parallelization.
Incoming frames are extensively analyzed by Beamr 5. It is this step which determines the complexity of the scene as rough motion vectors are calculated, and estimates for the bit demand of the encoded frame are made. These estimates guide the second stage of the encoder and allow those activities to focus on visually meaningful aspects of the frame. By partitioning the encoding process, unproductive calculations can be avoided, thus improving the speed of the encoder and the quality it produces.
Second, Beamr 5 features micro-level parallelization which is the result of the codec engineering team leveraging software engineering lessons learned from earlier generations of Beamr real-time software encoders. This experience led the team to design a micro-level parallelization approach that stages portions of the encoding tasks in a controlled manner, staggering their execution so each micro-task begins when the data is available (and still in the cache). This results in wasteful power and CPU cycles spent writing and fetching data being eliminated. Careful design of these micro-tasks assures that they are executed efficiently across the whole frame and in an even manner so that all cores are kept uniformly busy, and none are left waiting for their next task.
Uniquely, the Beamr encoder does not rely on the operating system to manage these critical execution threads but instead is under full control of the pooling and process allocation between the available cores and threads. Beamr’s advanced encoder controls the execution priority based on the availability of pipelined data.
Test Methodology
As in part 1 of ourx265 vs. Beamr 5 performance test, we encourage you to experience our speed claims first hand. For qualified video distributors, services and platforms, we are happy to offer a FREE evaluation agreement. To take advantage of this, please contact sales@beamr.com.
The purpose of this test was to measure the speed of Beamr 5 for live encoding applications running on Intel® Xeon® Scalable Platinum processors. In our first comparison of codec performance based on CPU, we decided to run a few comparisons with x265. For this comparison, x265 was benchmarked in its fastest speed setting ‘ultrafast’ – while for Beamr 5 we operated the encoder at its highest speed setting “15” with the performance boost modifier ‘TURBO1’ which activated our latest algorithmic improvements that are available in version 4.1. (All files were 4Kp60.)
For this second test, we wanted to dig deeper using Beamr 5 version 4.1 running on the same 2S Intel® Xeon® Platinum 8180 processor-based machine that we tested with in September, to see what gains were possible. What we found was nothing short of stunning.
In Graphic 1, HTOP shows Beamr 5 loaded 108 threads (from 112 available) at an impressive 90% utilization rate. This demonstrates the high degree of effectiveness with our Intel specific optimization.
Graphic 1: HTOP Intel 8180 dual socket 108 thread utilization at 90% across each thread.
More speed and performance benchmarks from Intel: CLICK HERE.
Conclusion
The drive to increase density with software-based video encoding and transcoding infrastructure is key to securing a competitive advantage for multi-service operators, OTT video distributors, and content distribution networks. At the same time, video architects must enable encoding and delivery of advanced entertainment content, by embracing new technologies, capabilities, and codecs such as HEVC, HDR, and 4K.
With a Beamr + Intel® Xeon® optimized video encoding solution, density – efficiency – quality – and flexibility of video encoding operations for on-premises, cloud, and hybrid data centers can be realized. Beamr 5 running on Intel® Xeon® Scalable processors offers TCO benefits and provides a meaningful improvement to the video processing capabilities of any video distribution solution.
If you missed part 1 of this post, be sure to check it out since additional technical details about Beamr 5 and its operational and performance advantages against x265 were specifically discussed. Find the x265 vs. Beamr 5 Speed Test here.
In late July, I reported on the “news” that Verizon was throttling video traffic for some users. As usual, the facts around this seemingly punitive act were not fully understood, which triggered this blog post.
At IBC last month (September 2017), I was interviewed by RapidTV where much of the conversation was around the Apple news of their support for HEVC across the device ecosystem running iOS 11 and High Sierra. As I was reviewing this interview, it seemed natural to publish it as a follow up to the original post.
There is no doubt that mobile operators are under pressure as a result of the network crushing video traffic they are being forced to deliver. But the good news is that for those operators who adopt HEVC, they are going to enjoy significant bitrate efficiencies, possibly as high as 50%. And for many services, though they will chose to take some savings, this means they’ll be able to upgrade their resolutions to full 1080p while simultaneously improving the video quality they are delivering.
I hope you find this video insightful. Our team has a very simple evaluation offer to discuss with all qualified video services and video distributors. Just send an email to sales@beamr.com and we’ll get in touch with the details.
There should be no debate over which standard will be the next generation winner with Apple’s adoption of HEVC (H.265). As the leading HEVC commercial software encoder implementer, we see video distributors who were waiting on the sideline prior to Apple’s announcement jumping into evaluations now that Apple has released the public versions of iOS 11 and macOS High Sierra.
The criteria for determining the best HEVC implementation will vary across application and service type and the business model of the video service will influence the decision of which solution to use. Yet, there is one factor that should be at the top of the decision tree for software based video encoders, and that is the performance (speed) of the encoder.
If you operate the encoding function for a live streaming service, then the performance and speed of your encoder is already top of mind, and the benefits of a solution which is 2 times faster is understood. But for those who operate SVOD and VOD services, the need to measure performance may not be as obvious. Read on to discover the benefits of operating a software encoder that is 2x faster.
Why a speed “face off”?
There is an inherent tradeoff between speed and quality with video encoder’s. With unlimited computing resources, one simply needs to apply the appropriate CPU power to meet the quality objective being targeted. In the case that an encoder is slow and inefficient, provided it can deliver the desirable quality, one can always reach the quality target if sufficient computing power is available. But, in the real world, there are constraints that cannot be ignored- whether budget, power, or space in the rack, few services have the luxury of operating as if they have unlimited computing resources. Which is why CPU performance is as critical an evaluation vector as absolute quality.
With Beamr 5 you will experience the following operational benefits as a result of the encoding operation being up to two times faster than x265 (based on the settings applied).
Up to half the server resources compared with x265
50% of the power utility draw compared with x265
50% less cooling and connectivity cost
Half the rack space
Evaluating Software Video Encoders
First, let’s examine the correlation between speed and quality by taking a look at the world’s best HEVC software video encoder, Beamr 5, as compared to the free open source alternative, x265.
The complexity of video encoder evaluations is such that you must understand not only what video files were used for the input, but also the precise settings (configuration) used. For this speed and quality evaluation you will note that x265 offers ten (10) performance presets that do a reasonable job of balancing the encoder’s speed and efficiency. Beamr 5 has a similar parameter named ‘enc_speed’ where there are a total of sixteen (16) levels available.
Out of the box Beamr 5 offers more granularity in its speed selection than x265, allowing for easier and more precise tuning across a wider range of computing platforms and architectures. However, to ensure an “apples to apples” comparison, other than matching the speed preset of each encoder, all other default parameters were left unchanged.
We want you to experience Beamr 5’s speed and quality first hand which is why we’ve provided the x265 settings that were used for each test. Readers are encouraged to duplicate the same tests, and we have provided download links for all files so that you can run your own independent analysis. Don’t believe our results? You can check them yourself.
As a commercial vendor working with the largest OTT and broadcast customers in the world, we design our products to be maximally usable by any video encoding engineer operating a video service. For the analysis we used x265 ‘veryslow’, ‘medium’, and ‘ultrafast’ settings since this test was designed to mirror real world use cases and not theoretical targets of either extreme speed or quality.
At Beamr we are all about the numbers, but as all video encoding engineers say, the eyes never lie. After you review the data in the charts below, please download the corresponding files so you can see for yourself Beamr 5’s superior quality.
We start with comparing the highest video quality modes of both encoders, akin to what an SVOD service may use, and move to slightly reduced video quality, but with faster performance needed for real-time (live) applications. Here we can demonstrate that Beamr 5 ‘enc_speed 0’ is much faster than the ‘veryslow’ x265 preset, while at the same time Beamr 5 produces better overall video quality.
The original source files can be downloaded from https://media.xiph.org/video/derf/, and converted from .y4m to yuv using the following FFmpeg command:
All Beamr 5 and x265 encoded files may be download from the links in the following tables or by click here. (all files were encoded in 4K resolution)
To aid in your subjective visual evaluation we suggest that you use a video comparison tool that is capable of rendering two videos in sync on the same screen. If you do not have a copy of Beamr View (formerly VCT), you may request a copy here. Beamr provides a limited license to our PC and Mac HEVC and H.264 software viewing tool FREE of charge to qualified video distribution services, content owners, and video platforms.
Test machine spec used for all clips: Amazon EC2 c3.4xlarge instance, Intel Xeon E5-2680 v2 @ 2.8GHz (16 threads), 30GB RAM, 160GB SSD.
The following chart provides a comparison of CPU performance at the maximum encoding quality with x265 configured at the ‘veryslow’ setting and Beamr 5 working at speed 0. The following chart shows the ability of Beamr 5 to produce higher video quality with much greater speed than x265. All other configuration settings were unchanged, except those required to align both codecs in keyframe interval, rate control limitations, and appropriate multithreading settings.
Table 1: Highest quality (VOD) configuration.
These are the settings used to test the highest quality presets (Beamr 5 enc_speed 0, x265 preset ‘veryslow’)
Command line example for x265 Highest Quality VOD setting:
4K resolution video ‘Ritual Dance’ frame 166, left side is Beamr 5, right side is x265. Beamr 5 is 71% faster than x265 with noticeably better quality.
4K resolution video ‘Driving POV’ frame 234, left side is Beamr 5, right side is x265. Beamr 5 is almost twice as fast as x265 at 98% with demonstrably better video quality.
With x265 set to the ‘medium’ preset and Beamr 5 ‘enc_speed’ set to 3, we observed that Beamr 5 maintained a 15% to 50% speed advantage over x265 while Beamr 5 consistently produced better quality. As with all other tests, configuration settings were unchanged, except those required to align both codecs in keyframe interval, rate control limitations, and appropriate multithreading settings.
Table 3: High quality preset configuration.
Command line example for x265 High Quality setting:
Table 4: High quality preset performance Beamr 5 vs. x265.
Screen capture 4: High quality settings Beamr 5 vs. x265.
4K resolution video ‘Wind and Nature’ frame 518, left side is Beamr 5, right side is x265. Beamr 5 is 50% faster with a slight edge on video quality over x265.
Screen capture 5: High quality settings Beamr 5 vs. x265.
4K resolution video ‘Ritual Dance’ frame 565, left side is Beamr 5, right side is x265. Beamr 5 is 50% faster than x265 and Beamr 5 has a definite edge on video quality.
Screen capture 6: High quality settings Beamr 5 vs. x265.
4K resolution video ‘Pier Seaside’ frame 18, left side is Beamr 5, right side is x265. Beamr 5 is 43% faster than x265 and Beamr 5 has noticeably better video quality.
Let’s examine how x265 and Beamr 5 fair when used for live encoding of 4K resolution video. When we set Beamr 5 to an equal speed configuration of x265 ‘ultrafast’, Beamr 5 was found to be faster while producing the same or better video quality.
Table 5: Live preset configuration.
Command line example for x265 live (real-time) configuration:
Table 6: Live configuration performance of Beamr 5 vs. x265.
Screen capture 7: Live settings Beamr 5 vs. x265.
4K resolution video ‘Bar Scene’ frame 595, left side is Beamr 5, right side is x265. Beamr 5 is 15% faster and produced better video quality than x265.
4K resolution video ‘Dinner Scene’ frame 528, left side is Beamr 5, right side is x265. Beamr 5 is 15% faster than x265, while both exhibited comparable quality.
Beamr has 30 granted and 23 pending patents, including a fast motion estimation process which is useful when speed and quality are at competing priority. Beamr 5’s fast motion estimation process is a significant factor in our performance advantage.
Beamr 5 uses a heuristic early-termination process which enables it to reach a targeted quality using less computational resources.
Beamr 5 allows for more possible frame hierarchies (levels) than what is provided by the H.265 standard. When encoding hierarchical B-frames, x265 uses a 2-level B-frame hierarchy. Beamr 5 on the other hand, encodes with a 3-level B-frame hierarchy when encoding seven B frames between P-frames.
x265 begins encoding frames before all reference frames are finished, which limits motion estimation to only the parts of reference frames that are available. When high performance (speed) is needed, x265 encoding quality can be degraded. This provides a serious advantage to Beamr 5 which supports full codec multithreading while x265 uses slices and tiles for parallelism (when WPP is disabled for maximum efficiency).
Beamr 5 achieves better parallelism without the limitations noted above because it is based on utilizing all possible independent encoding tasks inside a single frame. This is called wave-front and it is active even when entropy wave-front is not used. Multithreading in de-blocking and SAO filtering provides additional quality benefits.
Evaluating an encoder is one of the most important jobs for a video encoding engineer and we are proud of the advanced HEVC codec implementation we’ve developed. All information presented may be tested and verified and we invite you to take advantage of the video files using Beamr View to subjectively analyze the results above.
Beamr just returned from the Internet & Television Expo, or INTX, previously known as the Cable Show, where we identified three technology trends that are advancing rapidly and for some, are even here now. They are HDR, Network Function Virtualization, and IP Video.
HDR (High Dynamic Range) is probably the most exciting innovation in display technology in recent years.
There is a raging debate about resolution, “are more pixels really better?” But there is no debating the visual impact of HDR. Which is why it’s great to see TVs in the market that can display HDR reaching lower and lower price points, with better and better performance. However being able to display HDR is not enough. Without content there is no impact.
For this reason, Comcast EVP and CTO Tony Werner’s announcement at INTX that on July 4th, Comcast will be shipping their Xi5 STB to meet NBC Universal’s schedule of transmitting select Olympic events in HDR, is a huge deal. Though there will be limited broadcast content available in HDR, once Comcast has a sufficiently high number of HDR set top boxes in the field, and as consumers buy more HDR enabled TVs, the HDR bit will flip from zero to one and we’ll wonder how we ever watched TV without it.
Virtualization is coming and already here for some cable companies.
Though on the surface NFV (Network Function Virtualization) may be thought of as nothing more than the cable industry moving their data centers to the cloud, it’s actually much more than that. NFV offers an alternative to design, deploy and manage networking services by allowing network functions to run in software rather than traditional, “purpose-built” hardware appliances. In turn, this helps alleviate the limitations of designing networks using these “fixed” hardware appliances, giving network architects a lot more flexibility.
There are two places in the network where the efficiencies of virtualization can be leveraged, Access and Video. By digitizing access, the Virtual CCAP removes the physical CCAP and CMTS completely, allowing the control plane of the DOCSIS to be virtualized. Distributing PHY and the MAC is a critical step, but separating their functions is ground zero for virtualization.
Access virtualization is exciting, but what’s of great interest to those involved in video is virtualizing the video workflow from ingest to play out. This includes the encoding, transcoding, ad insertion, and packaging steps and is mainly tailored for IP video, though one cable operator took this approach to the legacy QAM delivery by leveraging converged services for IP and QAM. In doing this, the operator is able to simplify their video ingest workflow.
By utilizing a virtualized approach, operators are able to build more agile and flexible video workflows using “best of bread” components. Meaning they can hand pick the best transcoder, packager, etc. from separate vendors if needed. It also allows operators to select the best codec and video optimizer solutions, processes that are considered to be the most crucial parts of the video ingestion workflow, as the biggest IP (intellectual property) is within the video processing, not packaging, DRM etc. With content adaptive encoding and optimization solutions being introduced in the last few years, if an operator has a virtualized video workflow, they can be free to add innovations as they are introduced to the market. Gone are the days where service providers are forced to buy an entire solution from one vendor using proprietary customized hardware.
Having the IT industry (CPU, networking, storage) make tremendous progress in running video processing, packagers, streamer as software-only solutions on standard COTS hardware, this virtualization concept helps vendors focus on their core expertise, whether it is video processing, workflow, streamer, ad etc.
Virtualization can lower TCO, but it can also introduce operational and management challenges. Today service providers buy “N” transcoders, “N” streamers etc. to accommodate peak usage requirements. With virtualization the main advantage is to share hardware, so that overall less hardware is needed, which can lower TCO as file based transcoders could be run during off peak times (middle of the night) while more streamers are needed during peak times to accommodate a higher volume of unicast stream sessions (concurrency). This will require new methods of pay per usage, as well as sophisticated management and workflow solutions to initiate and kill instances when demand is high or when it drops.
For this reason we are seeing some vendors align with this strategy. Imagine Communications is entering the market with solutions for providing workflow management tools that are agnostic to the video processing blocks. Meanwhile, Cisco and Ericsson provide open workflows capable of interoperating with their transcoders, packagers, etc. while being open to third party integration. This opens the door for vendors like Beamr to provide video processing applications for encoding and perceptual quality optimization.
It is an IP Video world and that is a good thing.
Once the network is virtual, it flattens the distribution architecture so no longer does an operator need to maintain separate topologies for service delivery to the home, outside the home, fixed wire, wireless, etc. The old days of having RF, on net, and off net (OTT) systems, are quickly moving behind us.
IP video is the enabler that frees up new distribution and business models, but most importantly meets the expectation of end-users to access their content anywhere, on any device and at anytime. Of course there is that little thing called content licensing that can hold back the promise of anytime, anywhere, anyplace, especially for sports – but in time, as content owners adapt to the reality that by opening up availability they will spur not hamper consumption, it may not be long before the user is able to enjoy entertainment content on the terms they are willing to pay for.
Could we be entering the golden age of cable? I guess we’ll have to wait and see. One thing is certain. Vendors should ask themselves whether they are able to be the best in every critical path of the workflow. Because what is obvious, is that service providers will be deciding for them, as there is no solution from a single vendor that can be best of breed in todays modern network and video architectures. Vendors who adapt to changes in the market, due to virtualization, will be the leaders of the future.
At Beamr we have a 60 person engineering team focused solely on the video processing block of the virtualized network, specifically HEVC and H.264 encoding and content adaptive optimization solutions. Our team comes into the office every day with the single objective of pushing the boundary for delivering the highest quality video at the lowest bitrates possible. The innovations we are developing translate to improved customer experience and video quality whether that is 4k HDR with Dolby Vision, or reliable 1080p on a tablet.
IP Video is here, and in tandem with virtualized networks and the transition of video from QAM to the DOCSIS network, we are reaching a technology inflection point that is enabling better quality video than previous technological generations were able to deliver. We think it’s an exciting time to be in cable!
