Mythic Introduces Compact Quad-AMP PCIe Card for High-Performance Edge AI Applications

By Tiera Oliver

Associate Editor

Embedded Computing Design

November 17, 2021


Mythic Introduces Compact Quad-AMP PCIe Card for High-Performance Edge AI Applications
(Image Courtesy of Mythic)

Mythic unveiled its new MP10304 PCIe card which features four M1076 Mythic Analog Matrix Processors (AMPs), delivering up to 100 TOPs of AI performance and supporting up to 320 million weights for complex AI workloads at less than 25W of power.

The combination of high-performance and power-efficiency in a compact form factor makes the MP10304 PCIe card ideal for edge AI applications in video security, commercial drones, and product inspection in manufacturing.

The MP10304 PCIe card can be configured to run large DNN models utilizing the combined AI compute of all four AMPs for high-definition camera applications that need to detect smaller objects with minimal or no downscaling, for example in commercial drones and physical security. The MP10304 can also run a set of smaller DNN models for applications that process and analyze independent video streams concurrently from multiple cameras, such as network video recorders (NVRs).

Integrating four M1076 AMPs, the MP10304 PCIe card offers 4X the performance of each M1076, packaged in a compact half-height, half-length PCIe card, offering a combination of performance and power-efficiency for embedded edge AI applications. With the MP10304, complex AI networks can be deployed in edge appliance and network video recorders (NVRs) to ingest video data from many cameras in the field, and complex networks can be deployed at high resolution for applications requiring high accuracy. Mythic currently supports object detection, classification, and low-latency human body pose estimation. Other models such as depth estimation and image segmentation will be available soon.

Mythic’s Founder and CEO, Mike Henry, will be discussing the Mythic AMP platform at the 2021 Edge AI Summit. His presentation, “Solving the Edge AI Challenge with Analog Compute,” will take place on Tuesday, Nov. 16, 2021 at 11:45 a.m. PST.  

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Tiera Oliver, Associate Editor for Embedded Computing Design, is responsible for web content edits, product news, and constructing stories. She also assists with newsletter updates as well as contributing and editing content for ECD podcasts and the ECD YouTube channel. Before working at ECD, Tiera graduated from Northern Arizona University where she received her B.S. in journalism and political science and worked as a news reporter for the university’s student led newspaper, The Lumberjack.

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