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XMOS launches $1 processor for the AIoT market


Bristol-based fabless semiconductor company XMOS launched a new crossover processor for Artificial Intelligence of Things (AIoT) applications. Called, for the first time, AI, DSP, control and IO have come together in a single $1 device. says it wants to put intelligence at the core of smart products.

“ delivers the world’s highest processing power for a dollar,” said Mark Lippett, XMOS CEO. “Coupled with its flexibility means electronics manufacturers can embed multi-modal processing in smart devices to make life simpler and safer.”
A crossover processor is one that combines the merits of an applications processor, which are high-performance and optimised features, with the those of an MCU, which are low price and accessibility. The is developed to deliver real-time inferencing and decision-making at the edge, as well as signal processing, control and communications.

AIoT is the combination of artificial intelligence (AI) technologies with the Internet of Things (IoT) infrastructure to achieve more efficient IoT operations, improve human-machine interactions and enhance data management and analytics. Today’s smart devices typically require energy-hungry and costly connectivity to the cloud. This comes marred with challenges around latency, connectivity, privacy and energy consumption. By providing efficient, high-performance compute at the edge, delivers solutions to each of these challenges while keeping cost low and design potential high.
“ heralds an entirely new generation of embedded platform. It’s the most versatile, scaleable, cost-effective and easy-to-use processor on the market today. With its fast processing and neural network capabilities, enables data to be processed locally and actions taken on device — within nanoseconds. In the rapidly-evolving AIoT ecosystem, this enables manufacturers to build smarter sensing technology that fits seamlessly into our lives,” added Lippett.

The core offers the following features:


  • Fully programmable in ‘C’, with specific features such as DSP and machine learning accessible through optimised c-libraries;
  • Supports the FreeRTOS real-time operating system, enabling developers to use a broad range of familiar open-source library components;
  • TensorFlow Lite to converter, allows easy prototyping and deployment of neural network models.


  • Up to 128 pins of flexible IO (programmable in software) give access to a wide variety of interfaces and peripherals, which can be tailored to the precise needs of the application;
  • Integrated hardware USB 2.0 PHY and MIPI interface for collection and processing of data from a wide range of sensors.

Binarised neural networks

  • Employs deep neural networks using binary values for activations and weights instead of full precision values, dramatically reducing execution time;
  • By using binary neural networks, delivers 2.6x to 4x more efficiency than its 8-bit counterpart.

Performance compared to the nearest comparable ARM Cortex product

  • 32x improvement in AI performance;
  • 16x faster I/O processing;
  • 15x digital signal processing performance;
  • 21x 16-bit MACs.

  • incorporates DSP and machine learning capability together with scalar, floating and fixed point and vector instructions to deliver efficient control;
  • 16 real-time logical cores, with support for scalar/float/vector instructions, enabling flexibility and scale depending on application;
  • Flexible IO ports with nanosecond latency, ensuring time-critical response across applications;
  • Support for 8-bit and binarised neural network inferences (and 16-bit/32-bit), delivering on-device intelligence;
  • Complex multi-modal data capture and processing, enabling concurrent, on-device application across classification, audio interfaces, presence detection, voice interfaces, comms and control, actuation;
  • High-performance instruction set for digital signal processing, machine learning and cryptographic functions;
  • On-device inference of TensorFlow Lite for microcontroller models, offering a familiar development environment.

Product demos will be available from June 2020.

This project received funding from the European Union Horizon 2020 research and innovation programme under Grant Agreement No 849469.

About XMOS

In 2005, a small team from the University of Bristol assembled. They saw that a fast, flexible and cost-effective microcontroller was needed that would enable designers to respond quickly to diversifying market demand. That first-generation microcontroller put unprecedented IO capability – available through software for the first time – alongside significant DSP and control processing. This established XMOS as a name in the USB audio sector: if you wanted to compete in a rapidly changing market, you needed to create something special – and you needed XMOS to do it.

The team’s initial vision quickly shifted towards developing a powerful AI processor. This led to a fork in the road in 2016. Caught between two very different technical and commercial models for the future, XMOS split into two entities: Graphcore was created to focus on server-side AI (huge Cloud-based intelligence engines), and XMOS continued the quest towards low-cost, efficient embedded intelligence (or edge-AI).

The early vision has become reality. Voice is the most significant AI application in the market, and in 2019, XMOS moved to make it mainstream, bringing out the highest performing far-field 2-mic voice-interface for just under a dollar.

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