Deep learning system-on-chip

06 September 2017

Credit: Intel Corporation

The Movidius Myriad X vision processing unit advances Intel’s portfolio of artificial intelligence solutions to deliver more autonomous capabilities across a wide range of product categories – including drones, robotics, smart cameras and virtual reality.

Myriad X is the world’s first system-on-chip (SOC) shipping with a dedicated Neural Compute Engine for accelerating deep learning inferences at the edge. The Neural Compute Engine is an on-chip hardware block specifically designed to run deep neural networks at high speed and low power without compromising accuracy, enabling devices to see, understand and respond to their environments in real time. With the introduction of the Neural Compute Engine, the Myriad X architecture is capable of 1 TOPS of compute performance on deep neural network inferences.

“We’re on the cusp of computer vision and deep learning becoming standard requirements for the billions of devices surrounding us every day,” said Remi El-Ouazzane, vice president and general manager of Movidius, Intel New Technology Group. “Enabling devices with human-like visual intelligence represents the next leap forward in computing. With Myriad X, we are redefining what a VPU [or vision processing unit] means when it comes to delivering as much AI and vision compute power possible – all within the unique energy and thermal constraints of modern untethered devices.”

Capable of delivering more than 4 TOPS of total performance, its tiny form factor and on-board processing are ideal for autonomous device solutions. In addition to its Neural Compute Engine, Myriad X uniquely combines imaging, visual processing and deep learning inference in real time.

Myriad X is the newest generation in a lineage of Movidius VPUs, which are purpose-built for embedded visual intelligence and inference. Movidius VPUs achieve significant performance at low power with the merging of three architectural elements to provide sustained high-performance on deep learning and computer vision workloads: an array of programmable VLIW vector processors with an instruction set tuned to computer vision and deep learning workloads; a collection of hardware accelerators supporting image signal processing, computer vision, and deep learning inferences; and commonly accessible intelligent memory fabric that minimizes data movement on chip.

For more information, visit link 1 and link 2 on the Movidius Myriad X vision processing unit from Intel.


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