Enterprises, system integrators (SIs), OEMs, and developers can take control with Megh’s Open Analytics VAS SDK: A simplified and supported platform for custom, high-performance intelligent video analytics solutions.
VAS SDK allows developers to optimize video (and data) analytics pipelines and integrate highly customizable AI into applications and products.
With AI+ acceleration using GPUs, FPGAs, and SOCs, VAS SDK offers the highest performance, most scalability, greatest flexibility, and best vendor choice for system integrators and independent software vendors.
VAS SDK is a platform optimized for real-world complexity and performance.
Fully customizable pipeline
Open vendor choice
Intelligent video analytics
VAS SDK enables development of end-to-end intelligent video analytics solutions with the following Megh products:
VAS Suite— Deploy market-ready solutions that create actionable insights to reduce risks and improve operational efficiencies.
Specifications and implementation
- Languages supported: Python
- AI model frameworks: Pytorch and TensorFlow (TF-Lite)
- Platforms: CPU, GPU, FPGA, SOC
- Vendors: Intel, AMD, ARM, Xilinx, NVIDIA, Qualcomm
- Cloud infrastructure supported: AWS, Microsoft Azure, Google Cloud
For more technical details, learn about The Megh Platform.
Enhance VAS SDK with our SDK extensions:
- DLE SDK: Train, build, and deploy custom models with Pytorch, TF-Lite, and other frameworks on FPGAs for AI deep learning inferencing
- AFU SDK (coming soon): Develop custom FPGA accelerator function units (AFUs) for analytics using RTL/HLS for deployment on scale-out FPGA platforms
Why VAS SDK?
VAS SDK is an Open Analytics solution, designed to enable flexible, scalable, high-performance, end-to-end integration into your business operations, applications, and products.
- Customize the AI/video analytics pipeline for any camera/sensor stream
- Optimize for accuracy, TCO, or performance based on use case
- Edge-to-cloud deployment options for performance, cost, and regulatory adherence
- Start with CPU and scale to GPU/FPGA as needed
- Change compute platform and/or deployment type on the fly
- Stability for business users while scaling (no need to recode app layer)
Easy AI adoption
- Utilities provided to help report data and optimize analytics
- Concierge Support for custom integration or model development
- Right-size hardware for simple-to-complex use cases, based on pre-tested specs
- Lowest TCO for any performance target
Enables operational reliability
- Intelligent video analytics that actually deliver in complex environments and use cases
This 11-page Dell-EMC technical white paper evaluates a video analytics pipeline with deep learning inference using Megh’s VAS and Intel Programmable Acceleration Card (PAC) FPGAs on Dell EMC PowerEdge R740/R740xd servers.
This 3-page HPE technical white paper discusses how customers can achieve dramatically increased performance and reduced TCO by running the Megh Computing real-time streaming video analytics platform on the HPE ProLiant DL380 Gen10 server with Intel Arria 10 GX FPGAs compared to a configuration without FPGAs.
In the following video, see how Intel and Megh have partnered in developing low-latency analytics using AI with Intel FPGAs.