The Megh Platform
Real-time analytics platform with AI+ acceleration
Megh solutions are built using The Megh Platform, a powerful, Open Analytics foundation for real-time analytics with AI+ acceleration. It’s powered by the Nimble Application Framework, which easily enables the implementation of analytics pipelines. The platform supports seamless acceleration of applications that process streams, with machine learning and deep learning algorithms to extract value from data as it moves. It’s designed to support any type of real-time stream, including audio, video, and a wide range of sensor data.
The Megh Platform has two main attributes:
- It’s highly customizable, using modular components that can be managed using a no-code interface
- Applications using the platform can run seamlessly across CPUs, GPUs, FPGAs, and SOCs
The platform has the following principal components:
The Application, developed in-house, or by Megh Computing or a 3rd party, provides support for one or more analytics uses cases.
Megh’s Nimble Application Framework supports flexible pipelines for implementing the application for deployment from edge to cloud.
Our Arka Libraries expose software- or hardware-accelerated functions to the application using standard APIs.
The Arka Runtime enables the application to build custom data pipelines spanning multiple devices and accelerators, including GPUs and FPGAs.
The Sira Shell provides platform-agnostic, scale-out hardware services for the FPGA accelerators.
Megh’s Deep Learning Engine (DLE) for FPGAs delivers best-in-class performance for accelerating inferencing for image detection and classification on FPGAs.
The Megh Platform can be deployed from edge to cloud and across platforms.
Megh's Deep Learning Engine
The platform includes our Deep Learning Engine (DLE), the best-in-class inference engine for implementing various deep learning models.
- Seamless multi-stage model support on single and across multiple FPGAs.
- Native mixed precision support on a layer-by-layer basis, giving fine-grained control of model accuracy and performance.
- Optimized for batch size = 1 data ingest and allows for both inline real-time and offload workloads.
- Easy end-user customization using DLE Compiler.
- Scalable architecture to meet end-user throughput and FPGA area requirements.
Learn more about DLE.
See blog posts about DLE.
Why FPGA acceleration?
FPGAs provide a reconfigurable sea of hardware gates. With FPGAs you can:
- Design a custom hardware accelerator with direct I/O connectivity and low latency
- Deploy for a single application to deliver increased performance efficiencies
- Quickly reconfigure the device as a new accelerator for a different application
Megh Computing’s DLE is optimized to take advantage of FPGA architecture, in some cases delivering 10x performance compared to GPUs.
Applications
The Open Analytics Blog
Read The Open Analytics Blog to learn more about real-time analytics.
White paper and briefs
