Reexen SIGNED
Ultra-low cost & ultra-high efficiency AI processor for enabling fast and cost-effective deployment of edge-computing applications
Total Cost €
0EC-Contrib. €
0Partnership
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0Reexen project word cloud
Explore the words cloud of the Reexen project. It provides you a very rough idea of what is the project "Reexen" about.
Project "Reexen" data sheet
The following table provides information about the project.
| Coordinator |
CYBERTRON TECH GMBH
Organization address contact info |
| Coordinator Country | Switzerland [CH] |
| Total cost | 71˙429 € |
| EC max contribution | 50˙000 € (70%) |
| Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
| Code Call | H2020-SMEInst-2018-2020-1 |
| Funding Scheme | SME-1 |
| Starting year | 2020 |
| Duration (year-month-day) | from 2020-01-01 to 2020-04-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | CYBERTRON TECH GMBH | CH (ZURICH) | coordinator | 50˙000.00 |
Map
Project objective
'Since the breakthrough application of Deep Neural Networks algorithms (DNNs) to speech and image recognition, the number of applications that use DNNs has exploded, achieving the highest accuracy in a myriad of contexts (health, robotics, finance, gaming, etc.). However, their superior accuracy comes at the cost of high computational complexity. Current approaches to solve this challenge are cloud-based, incurring in high power consumption and high latency, given their communication needs. Although cloud approaches are suitable for some context, they are suboptimal for real-time applications running on embedded or mobile devices (with limited battery capacity and requiring fast responses). REEXEN appears to bring a solution to this challenge: an extremely efficient AI processor (a semiconductor chip) specifically designed for supporting DNN-based edge applications. By exploiting state-of-the-art semiconductor technologies in mixed-signal circuits and in-memory processing, REEXEN obtains the best power-efficiency when executing DNN algorithms, in terms of maximum throughput per energy unit consumption (30 TOPs/W). By reducing the 'distance' between data generation (sensors), data storage (memory) and data processing (core processor or nucleus), and by eliminating A/D conversions, REEXEN also achieves minimum latency (<10ms) and fabrication area, thus also reducing the overall cost of production. REEXEN completely aligns with the EU approach to AI, as an enabling technology that will allow the development of current industry-transversal smart services and the implementation of future new ones. Our company is 100% focused on developing next generation of ultra-low power neural network processors. From the successful results of our early prototyping for audio applications, REEXEN project will attract the best talent and additional financing to build the business around our technology and increase our company size, international presence and job generation.'
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The information about "REEXEN" are provided by the European Opendata Portal: CORDIS opendata.