Sold by: AMD Xilinx
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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 Kubernetes 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 release includes support for the popular GStreamer multimedia framework with the addition of several plugins to access the accelerated video transcoding capabilities.
For Kubernetes deployments, please upgrade the plugin to version 1.1.0 before deploying this 3.0.0 EKS AMI. Refer to https://xilinx.github.io/video-sdk/v3.0/deploying_with_kubernetes.html#deploying-with-kubernetes for more detail.
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
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64-bit (x86) Amazon Machine Image (AMI)
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AmazonLinux 2
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Dimensions summary
This software is free to use, so you pay only for the underlying EC2 VT1 instances. The three dimensions map to VT1 instance sizes: vt1.3xlarge, vt1.6xlarge, and vt1.24xlarge. Each is billed hourly. The sizes differ in compute capacity, letting you match instance size to your video transcoding workload. Pricing scales with the instance size you select and the number of hours you run it. There are no tiers or add-ons — you simply choose one instance size and pay by the hour.
Top-of-mind questions for buyers
Each dimension maps to a VT1 instance size with different compute capacity. The vt1.24xlarge holds the most transcoding resources, followed by vt1.6xlarge, then vt1.3xlarge. You pick one size to match your video transcoding workload. Larger sizes handle more concurrent streams. You pay the hourly rate for whichever size you run.
The software itself is free, so no software charges apply. The hourly rate you see reflects the underlying EC2 VT1 instance. Charges accrue while the instance runs. Stopped instances stop accruing compute charges, though attached storage may still incur separate AWS fees. Metering follows running time.
You get a software stack for hardware-accelerated video transcoding on VT1 instances. It includes pre-compiled versions of common media processing tools with transcoding plug-ins, plus a C-based API for integration into your own frameworks. It supports hardware-accelerated video decoding, scaling, and encoding for live streaming workloads.
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
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Support
Vendor support
Submit issues via the AMD Xilinx Video SDK Github repository for support. https://github.com/Xilinx/video-sdk/issues
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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