Everything about the NETINT Product Line

Everything about the NETINT Product Line

by Jan Ozer at NETINT Technologies Inc.

This article will introduce you to the NETINT product line and Codensity ASIC generations. We?will focus primarily on the hardware differences since all products share a common software architecture and feature set, which are briefly described at the end of the article.

Codensity G4-Powered Video Transcoder Products

The?Codensity G4?was the first encoding ASIC developed by?NETINT. There are two G4-based transcoders, the?T408?(Figure 1), is available in a U.2 form factor and as an add-in card, and the?T432?(Figure 2), which is available as an add-in card. The?T408?contains a single?G4 ASIC?and draws 7 watts under full load, while the?T432?contains four?G4 ASICs?and draws 27 watts.

The?T408?costs $400 in low volumes, while the?T432?costs $1,500. The?T432?delivers 4x the raw performance of the?T408.

T408?and?T432?decode and encode H.264 and HEVC on the device but perform all scaling, overlay, and deinterlacing on the host CPU.

If you’re buying your own host, the selected CPU should reflect the extent of processing that it needs to perform and the overhead requirements of the media processing framework that is running the transcode function.?

When transcoding inputs without scaling, as in a cloud gaming or conferencing application, a modest CPU can suffice, if you are creating standard encoding ladders, deinterlacing multiple streams, or frequently scaling incoming videos, you’ll need a more capable CPU. For a turn-key solution, check out the?NETINT Video Transcoding Server?options.

The?T408?and?T432?run on multiple versions of Ubuntu and CentOS; see?here?for more detail about those versions and recommendations for configuring your server.

The NETINT Video Transcoding Server

The NETINT Video Transcoding Server?includes ten?T408?U.2 transcoders. It is targeted for high-volume transcoding applications as an affordable turn-key replacement for existing hardware transcoders or where a drop-in solution to a software-based transcoder is preferred.

The base model costs?$7,000?and is built on the Supermicro 1114S-WN10RT server platform powered by an AMD EPYC 7232P CPU Series Processor with eight CPU cores and 16 threads running Ubuntu 20.04.05 LTS. The server ships with 512 GB of DDR4-3200 RAM and a 400GB M.2 SSD drive with 3x PCIe slots and ten NVME slots that house the ten T408 transcoders. At full transcoding capacity, the server draws 220 watts while encoding or transcoding up to ten 4Kp60 streams or as many as 160 720p60 video streams.

The server?is also offered with two more powerful CPUs, the AMD EPYC 7543P Server Processor (32-cores/64-threads, $8,900) and the AMD EPYC 7713P Server Processor (64-cores/128-threads, $11,500). Other than the CPU, the hardware specifications are identical.

All Codensity?G4-based products support HDR10 and HDR10+ for H.264 and H.265 encode and decode, as well as EIA CEA-708 closed captions for H.264 and H.265 encode and decode. In low-latency mode, all products support sub-frame latency. Other features include region-of-interest encoding, a customizable GOP structure with eight presets, and forced IDR frame inserts at any location.

The?T408,?T432, and?NETINT Server?are targeted toward high-volume interactive applications that require inexpensive, low-power, and high-density transcoding using the H.264 and HEVC codecs.

Codensity G5-Powered Live Transcoder Products

In addition to roughly quadrupling the H.264 and HEVC throughput of the?Codensity G4,?the Codensity G5?is our second-generation ASIC that adds AV1 encode support, VP9 decode support, onboard scaling, cropping, padding, graphical overlay, and an 18 TOPS (Trillions of Operations Per Second) artificial intelligence engine that runs the most common frameworks all natively in silicon.

Codensity G5?also includes audio DSP engines for encoding and decoding audio codecs such as MP3, AAC-LC, and HE AAC. All this on-board activity minimizes the role of the CPU, allowing?Quadra?products to operate effectively in systems with modest CPUs.

Where the?G4 ASIC?is primarily a transcoding engine,?the G5?incorporates much more onboard processing for even greater video processing acceleration. For this reason, NETINT labels?Codensity G4-based products as Video Transcoders and?Codensity G5-based products as Video Processing Units or VPUs.

The?Codensity G5?is available in three products (Figure 4), the U.2-based?Quadra T1?and PCIe-based?Quadra T1A, which include one?Codensity G5 ASIC, and the PCIe-based , which includes two?Codensity G5 ASICs.?Pricing for the T1 starts at $1,500.?

In terms of power consumption, the?T1?draws 17 Watts, the?T1A?20 Watts, and the?T2?draws 40 Watts.

FIGURE 4.?THE QUADRA LINE OF CODENSITY G5-BASED PRODUCTS.

All?Codensity G5-based products provide the same HDR and close caption support as the?Codensity G4-based products. They have also been tested on Windows, MacOS, Linux and Android OS with support for virtual machine and container virtualization, including Single Root I/O Virtualization [SRIOV].

From a quality perspective, the?Codensity G4-based transcoder products offer no configuration options to optimize quality vs. throughput. Quadra?Codensity G5-powered VPUs offer features like lookahead and rate-distortion optimization that allow users to customize quality and throughput for their particular applications.

HARD QUESTIONS ON HOT TOPICS – WHAT DO YOU NEED TO UNDERSTAND ABOUT NETINT PRODUCTS LINE.

AI-Based Video Processing

Beyond VP9 ingest and AV1 output, and superior on-board processing, the?Codensity G5 AI?engine is a game changer for many current and future video processing applications. Each?Codensity G5 ASIC?includes two onboard?Neural Processing Units (NPUs).?Combined with Quadra’s integrated decoding, scaling, and transcoding hardware, this creates an integrated AI and video processing architecture that requires minimal interaction from the host CPU.

Today, in early 2023, the AI-enabled processing market is nascent, but Quadra already supports several applications like?AI-based region of interest filter, background removal (see Quadra App Note APPS553), and others. Additional features under development include an automatic facial ID for video conferencing, license plate detection and OCR for security, object detection for a range of applications, and voice-to-text.

Quadra?includes an AI Toolchain workflow that enables importing models from AI tools like Caffe, TensorFLow, Keras, and Darknet for deployment on?Quadra. So, in addition to the basic models that?NETINT?provides, developers can design their own applications and easily implement them on?Quadra.?

Like NETINT’s?Codensity G4?based products, Quadra VPUs are ideal for interactive applications that require?low CAPEX and OPEX. Quadra VPUs offer increased onboard processing that enables lower-cost host systems and the ability to customize throughput and quality, deliver AV1 output, and deploy AI video applications.

Media Processing Frameworks - Driving NETINT Hardware

In addition to SDKs for both hardware generations,?NETINT?offers highly efficient?FFmpeg?and GStreamer SDKs that allow operators to apply an FFmpeg/libavcodec or GStreamer patch to complete the integration.

In the?FFmpeg implementation, the libavcodec patch on the host server functions between the?NETINT?hardware and?FFmpeg software layer, allowing existing FFmpeg-based video transcoding applications to control hardware operation with minimal changes.

The?NETINT?hardware device driver software includes a resource management module that tracks hardware capacity and usage load to present inventory and status on available resources and enable resource distribution. User applications can build their own resource management schemes on top of this resource pool or let the?NETINT server?automatically distribute the decoding and encoding tasks.

In automatic mode, users simply launch multiple transcoding jobs, and the device driver automatically distributed the decode/encode/processing tasks among the available resources. Or, users can assign different hardware tasks to different?NETINT?devices, and even control which streams are decoded by the host CPU or?NETINT?hardware. With these and similar controls, users can most efficiently balance the overall transcoding load between the?NETINT?hardware and host CPU and maximize throughput.

In all interfaces, the syntax and command structure is similar for?T408s and?Quadra?units which simplifies migrating from G4-based products to Quadra hardware. It is also possible to operate?T408?and?Quadra?hardware together in the same system.

That’s the overview. For more information on any product, please check the following?product pages?(click the image below to see the product page).?

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