skip to main content
Close Icon

In order to deliver a personalized, responsive service and to improve the site, we remember and store information about how you use it. This is done using simple text files called cookies which sit on your computer. By continuing to use this site and access its features, you are consenting to our use of cookies. To find out more about the way Informa uses cookies please go to our Cookie Policy page.

Global Search Configuration

Ovum view


Graphcore, a Bristol, UK-based start-up, went live today, announcing a successful and oversubscribed series A venture funding round of more than $30m, a record in the UK. The names now backing the new venture have stellar backgrounds, with key funders linked to high-technology firms, such as Bosch and Samsung, and VC firms with a history in successful ventures (Apple and Google to name two). This means that Graphcore is able to call on first-class expertise and a deep network in the high-technology industry to help steer the company as it prepares to launch its flagship product in 2017, an artificial intelligence (AI) accelerator microprocessor to be known as Intelligent Processing Unit (IPU). The company location in Bristol is not by chance, CEO Nigel Toon and CTO Simon Knowles have a background in custom processors, and many of their team go back to the Inmos Transputer that was based in Bristol. The AI accelerator market, particularly for training and inference on deep neural networks, is forecast to grow from its current million-dollar bracket to become a billion-dollar industry in the next three to five years. The success of general-purpose processing GPUs for deep learning neural networks has made Nvidia the dominant player in AI acceleration, and it is now the turn of new hardware innovations dedicated to AI to up the game, something Graphcore promises to deliver. The competition in the accelerator market bodes well for the AI systems designers, and will lead to the next round of innovation.

The deep learning accelerator will be a competitive market in 2017

Graphcore’s key differentiator is that its technology will offer not only data parallelism but also instruction-level parallelism. This will boost the performance of massively parallel networks in the way in which they handle training and more efficient inference on data, and also in how the algorithms are processed at the neuron layers. The company name includes the word “graph” and the mathematical concept of a graph is a network of vertices linked by edges. Data parallelism boosts activity on the edges while instruction-level parallelism boosts activity at the vertices (neurons). This twin parallelism approach will differentiate Graphcore from Nvidia, the dominant player in the market with its GPU-based accelerator that mainly provides data parallelism.

With machine learning systems leaving the research laboratories and entering real-world enterprise applications, products, and services, the market for AI accelerators is predicted to grow rapidly. The three largest application areas to immediately benefit from AI migration will be the automotive and healthcare industries, and any vertical industry that requires intelligent automation to mine big data.

The end game is for inference accelerator processors to be inexpensive enough to be embedded in everyday products, creating a mass market for this type of product. AI accelerators will be used in a combination of modes, including running on the cloud with IOT connectivity and running training algorithms in real-time learning scenarios, as well as pure inference systems that can also be regularly updated over the air: when one robot learns to ride a bicycle all robots (by that manufacturer) can ride a bicycle.



Michael Azoff, Principal Analyst, IT Infrastructure Solutions

Recommended Articles

  • Enterprise Decision Maker, Enterprise IT Strategy and Select...

    2017 Trends to Watch: Big Data

    By Tony Baer 21 Nov 2016

    The breakout use case for big data will be fast data. The Internet of Things (IoT) is increasing the urgency for enterprises to embrace real-time streaming analytics, as use cases from mobile devices and sensors become compelling to a wide range of industry sectors.

    Topics Big data and analytics IoT

  • Consumer & Entertainment Services, World Cellular Informatio...

    Mapping the Future of Enterprise Messaging: SMS, RCS, and Chat Bots

    By Pamela Clark-Dickson

    In this paper, we analyze the results of the Enterprise Messaging Survey 2017, placing the findings in the context of the rapidly evolving business-to-consumer communications market.

  • Consumer & Entertainment Services, Service Provider Technolo...

    FAANG to sink its teeth deeper into TV in 2018

    By Rob Gallagher 14 Dec 2017

    Few trends will be bigger in 2018 than the transformation of TV and video by OTT technology and services. Here we present five Ovum predictions related to the most influential players: Facebook, Amazon, Apple, Google, and Netflix – or FAANG, for short.


Have any questions? Speak to a Specialist

Europe, Middle East & Africa team - +44 (0) 207 017 7700

Asia-Pacific team - +61 (0)3 960 16700

US team - +1 646 957 8878

+44 (0) 207 551 9047 - Operational from 09.00 - 17.00 UK time

You can also contact your named/allocated Client Services Executive using their direct dial.
PR enquiries - Call us at +44 7770704398 or email us at

Contact marketing -

Already an Ovum client? Login to the Knowledge Center now