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Netint technologies

ASIC vs. CPU-Based Transcoding: A Comparison
of Capital and Operating Expenses

Jan Ozer

Jan Ozer

is Senior Director of Video Marketing at NETINT.

Jan is also a contributing editor to Streaming Media Magazine , writing about codecs and encoding tools. He has written multiple authoritative books on video encoding, including ‘Video Encoding by the Numbers: Eliminate the Guesswork from your Streaming Video’ and ‘ Learn to Produce Video with FFmpeg: In Thirty Minutes or Less’ and has produced multiple training courses relating to streaming media production.

As the title suggests, this post compares CAPEX and OPEX costs for live streaming using ASIC- based transcoding and CPU-based transcoding. The bottom line?

NETINT Transcoding Server with 10 T408 Video Transcoders
Figure 1. The 1 RU Deep Edge Appliance with ten NETINT T408 U.2 transcoders.

Jet-Stream is a global provider of live-streaming services, platforms, and products. One such product is Jet-Stream’s Deep Edge OTT server, an ultra-dense scalable OTT streaming transcoder, transmuxer, and edge cache that incorporates ten NETINT T408 transcoders. In this article, we’ll briefly review how Deep Edge compared financially to a competitive product that provided similar functionality but used CPU-based transcoding.

About Deep Edge

Jet-Stream Deep Edge is an OTT edge transcoder and cache server solution for telcos, cloud operators, compounds, and enterprises. Each Deep Edge appliance converts up to 80 1080p30 television channels to OTT HLS and DASH video streams, with a built-in cache enabling delivery to thousands of viewers without additional caches or CDNs.

Each Deep Edge appliance can run individually, or you can group multiple systems into a cluster, automatically load-balancing input channels and viewers per site without the need for human operation. You can operate and monitor Edge appliances and clusters from a cloud interface for easy centralized control and maintenance. In the case of a backlink outage, the edge will autonomously keep working.

Figure 2. Deep Edge operating schematic.

Optionally, producers can stream access logs in real-time to the Jet-Stream cloud service. The Jet-Stream Cloud presents the resulting analytics in a user-friendly dashboard so producers can track data points like the most popular channels, average viewing time, devices, and geographies in real-time, per day, week, month, and year, per site, and for all the sites.

Deep Edge appliances can also act as a local edge for both the internal OTT channels and Jet-Stream Cloud’s live streaming and VOD streaming Cloud and CDN services. Each Deep Edge appliance or cluster can be linked to an IP-address, IP-range, AS-number, country, or continent, so local requests from a cell tower, mobile network, compound, football stadium, ISP, city, or country to Jet-Stream Cloud are directed to the local edge cache. Each Deep Edge site can be added to a dynamic mix of multiple backup global CDNs, to tune scale, availability, and performance and manage costs.

Under the Hood

Each Deep Edge appliance incorporates ten NETINT T408 transcoders into a 1RU form factor driven by a 32-core CPU with 128 GB of RAM. This ASIC-based acceleration is over 20x more efficient than encoding software on CPUs, decreasing operational cost and CO2 footprint by order of magnitude. For example, at full load, the Deep Edge appliance draws under 240 watts.

The software stack on each appliance incorporates a Kubernetes-based container architecture designed for production workloads in unattended, resource-constrained, remote locations. The architecture enables automated deployment, scaling, recovery, and orchestration to provide autonomous operation and reduced operational load and costs.

The integrated Jet-Stream Maelstrom transcoding software provides complete flexibility in encoding tuning, enabling multi-bit-rate transcoding in various profiles per individual channel.

Each channel is transcoded and transmuxed in an isolated container, and in the event of a crash, affected processes are restarted instantly and automatically.

Play Video about NETINT- HQHT - Jan Ozer - CPU encoding vs ASIC encoding
HARD QUESTIONS ON HOT TOPICS
 ASIC vs. CPU-Based Transcoding: A Comparison of Capital and Operating Expenses
Watch the full conversation on YouTube: https://youtu.be/pXcBXDE6Xnk

Deep Edge Proposal

Recently, Jet-Stream submitted a bid to a company with a contract to provide local streaming services to multiple compounds in the Middle East. The prospective customer was fully transparent and shared the costs associated with a CPU-based solution against which Deep Edge competed.

In producing these projections, Jet-Stream incorporated a cost per kilowatt of € 0.20 Euros and assumed that the software-based server would run at 400 Watts/hour while Deep Edge would run at 220 Watts per hour.  These numbers are consistent with lab testing we’ve performed at NETINT; each T408 draws only 7 watts of power, and because they transcode the incoming signal onboard, host CPU utilization is typically at a minimum.

Jet-Stream produced three sets of comparisons; a single appliance, a two-appliance cluster, and ten sites with two-appliance clusters. Here are the comparisons. Note that the Deep Edge cost includes all software necessary to deliver the functionality detailed above for standard features. In contrast, the CPU-based server cost is hardware-only and doesn’t include the licensing cost of software needed to match this functionality.    

Single Appliance

A single Deep Edge appliance can produce 80 streams, which would require five separate servers for CPU-based transcoding. Considering both CAPEX and OPEX, the five-year savings was €166,800.

Table 1. CAPEX/OPEX savings for a single
Deep Edge appliance over CPU-based transcoding.

A Two-Appliance Cluster

Two Deep Edge appliances can produce 160 streams, which would require nine CPU-based encoding servers to produce. Considering both CAPEX and OPEX, the five-year savings for this scenario was €293,071.

ASIC vs. CPU-Based Transcoding - table 2
Table 2 CAPEX/OPEX savings for a dual-appliance
Deep Edge cluster over CPU-based transcoding.
.

Ten Sites with Two-Appliance Clusters

Supporting ten sites with 180 channels would require 20 Deep Edge appliances and 90 servers for CPU-based encoding. Over five years, the CPU-based option would cost over € 2.9 million Euros more than Deep Edge.

Table 3. CAPEX/OPEX savings for ten dual-appliance
Deep Edge clusters over CPU-based transcoding.

While these numbers border on unbelievable, they are actually quite similar to what we computed in this comparison, How to Slash CAPEX, OPEX, and Carbon Emissions with T408 Video Transcoder, which compared T408-based servers to CPU-only on-premises and AWS instances.

The bottom line is that if you’re transcoding with CPU-based software, you’re paying way too much for both CAPEX and OPEX, and your carbon footprint is unnecessarily high. If you’d like to explore how many T408s you would need to assume your current transcoding workload, and how long it would take to recoup your costs via lower energy costs, check out our calculators here.

Play Video about Voices of VIdeo - Stef van der Ziel from Jet Stream - Building Localized OTT Networks
Voices of Video: Building Localized OTT Networks
Watch the full conversation on YouTube: https://youtu.be/xP1U2DGzKRo

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