White Papers

7 Real Time Streaming Analytics with Megh Computing on Dell EMC PowerEdge Servers
Application Case Study
We consider fraud prevention in the retail supply chain as the application case study. Retail inventory
loss (or “shrinkage”) is a serious problem, totaling about $100 billion annually—almost 1.8% of sales—
worldwide. Not surprisingly, retailers are seeking solutions. While some are looking at a broad range of
possibilities—facial recognition, motion tracking, reading emotions and gestures, and AR—most want to
begin with solutions that are low cost and yield immediate returns. Fortunately, there are effective
technological solutions that satisfy these criteria.
Megh has developed the Video Analytics Solution (VAS) to solve this problem. The Solution is targeted
for various use cases including fraud prevention in the retail supply chain, inventory tracking in
manufacturing, and video surveillance for security.
Solution Description
The Solution maps the entire real time analytics pipeline consisting of the ingestion phase of streaming
data input, transformation phase of video decoding and image resizing and the inference phase of
object detection and classification into multiple networked FPGAs with integration into user's
application.
The Solution runs on Dell EMC PowerEdge Server with Intel Programmable Acceleration Cards. The
Solution consists of Sira Accelerator Function Units (AFUs) for inline processing of streaming data and
offload processing of compute intensive algorithms on multiple networked FPGAs. The AFUs used in this
solution include:
• PPE (Packet Processing Engine) for ingesting the data using a direct NIC and extracting the
payload