Sold by: AMD Xilinx
Deployed on AWS
The AMD Xilinx Video SDK is a complete software stack allowing users to seamlessly leverage the hardware accelerated features of AMD Xilinx video codecs such as the ones available on Amazon EC2 VT1 instances and AWS Elastic Container Service.
Overview
The AMD Xilinx Video SDK is a complete software stack allowing users to seamlessly leverage the hardware accelerated features of AMD Xilinx video codecs and enable high-density real-time transcoding for live streaming video service providers, OEMs, and Content Delivery Network (CDNs). Included in the AMD Xilinx Video SDK is a pre-compiled version of FFmpeg and GStreamer which integrates key video transcoding plug-ins, enabling simple hardware offloading of compute-intensive workloads (such as video decoding, scaling, and encoding) using these popular tools.
The AMD Xilinx Video SDK also provides a C-based application programming interface (API) which facilitates the integration of AMD-Xilinx video codec transcoding capabilities in proprietary frameworks.
In addition to enhanced OS/kernel support and bug fixes, the 3.0.0 release brings with it ultra low latency (ULL) encoding, dynamic GOP, min/max frame quantization parameter (QP) bounding, and support for updates using package feeds. Visit What's New of its release notes (https://xilinx.github.io/video-sdk/v3.0/release_notes.html#what-s-new ) for the full list of enhancements.
The 3.0.0 release includes support for the popular GStreamer multimedia framework with the addition of several plugins to access the accelerated video transcoding capabilities.
Highlights
- Adaptive bitrate (ABR) transcoder * Real-time and faster than real-time transcoder * Supports H.264 and HEVC * Up to two channels of 4Kp60 video throughput per card * Subdivide total throughput for a maximum of 48 channels of lower resolution video
- FFmpeg, Gstreamer, and C-based API's * Supports HDR10 and HDR10+ * Dynamic update of encoder parameters
- Ultra low latency (ULL) encoding * Dynamic GOP * Min/max frame quantization parameter (QP) bounding * Updates using package feeds
Details
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64-bit (x86) Amazon Machine Image (AMI)
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Operating system
AmazonLinux 2
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Pricing
This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimensions summary
This software is free to use, so the AWS Marketplace charges no license fee. You only pay the underlying AWS costs for the VT1 instance you run. Pricing is billed by the hour and split across three VT1 instance sizes: vt1.24xlarge, vt1.6xlarge, and vt1.3xlarge. These are not feature tiers. They differ by hardware capacity, letting you match the instance size to your video transcoding workload. Larger sizes handle more concurrent streams. You choose one size per instance and pay for the hours it runs.
Top-of-mind questions for buyers
Each size maps to a different VT1 hardware capacity. The vt1.24xlarge has the most video codec resources, the vt1.6xlarge sits in the middle, and the vt1.3xlarge has the fewest. You choose one size per instance and pay for the hours it runs. More capacity handles more concurrent transcoding streams.
The software carries no license fee, so no software charge accrues at any time. Hourly charges reflect the underlying AWS instance cost and apply only while the instance runs. Stopped instances stop accruing compute charges, though AWS storage fees for attached volumes may still apply.
You get the Amazon Linux 2 AMI with the video transcoding software stack and ECS container support. It provides pre-compiled versions of common media processing tools with hardware acceleration plug-ins, plus a C-based API. This lets you run hardware-accelerated video decoding, scaling, and encoding on VT1 instances.
xilinx.github.io
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Additional details
Usage instructions
Refer to the GitHub repository for details: https://xilinx.github.io/video-sdk/#
Resources
Vendor resources
Support
Vendor support
Submit issues via the AMD Xilinx Video SDK Github repository for support.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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