RISC-V Processor Core of Fraunhofer IPMS now ready for Edge AI
The Fraunhofer Institute for Photonic Microsystems IPMS offers ready-made,
platform-independent IP core modules. With IP modules, developers can quickly
adopt complete functional areas in standard products such as SoCs,
microcontrollers, FPGAs and ASICs. This allows a significant reduction of
development times and costs. With EMSA5, Fraunhofer IPMS offers a processor
core based on the open RISC-V instruction set architecture. In the latest release,
the institute has ported Tensorflow lite to the EMSA5 RISC-V. Thus, the EMSA5
RISC-V processor core is now ready for use in Edge AI applications, for example
sensor data evaluation, gesture control or vibration analysis
"Edge AI means that AI algorithms are executed either directly on the device or on a
server close to the device. This is done using the data collected directly from the device
- without the need to connect to the Internet or a cloud service. Only the results of the
processing are then fed into the cloud. In this way, the devices can make autonomous
decisions within milliseconds using AI," explains Dr. Andreas Weder, group manager
Module Integration at Fraunhofer IPMS. To be able to process the data, so-called
machine learning models are used. Such a model is trained on the basis of data sets to
recognize patterns - first on the training data set and later with real data, for example
from sensors. In this way, it can derive new facts from already existing data and apply
them to a specific context to make predictions.
"Applications with low-latency requirements can benefit from this type of processing,
as there are no delays caused by transmitting data to the cloud. The system is able to
work even with unstable internet connections and does not rely on processing data in
the cloud - a big advantage for mobile or stand-alone applications and for locations
with unstable data connections," Weder said. As the number of IoT devices increases
enormously worldwide and more and more data is sent to the cloud, the scalability of
the system also plays a major role. Furthermore, data security is of course of high
interest nowadays. The more data that has to be sent wirelessly to the cloud, the more
points of attack an IoT system provides. The use of an edge system makes it more
difficult to attack from the outside because the data is processed locally in a closed
network.
"We have ported Tensorflow lite to the EMSA5 RISC-V. Our users can now easily
implement edge AI applications such as sensor data analysis, gesture recognition or
vibration analysis," explains Weder. The Fraunhofer IPMS EMSA5 processor core can be
made available for any FPGA platform. Integration into customer-specific ASICs for any
foundry technologies is also possible.
Developers using the EMSA5 processor core can use open-source RISC-V development
environments (IDE), test tools, and libraries, including the GNU toolchain and the
comprehensive Eclipse IDE with OpenOCD debug support. Fraunhofer IPMS also works
with commercial third-party compilers and software tools such as IAR Embedded
Workbench to enable software development in the Functional Safety context.
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About Fraunhofer IPMS
The Fraunhofer Institute for Photonic Microsystems IPMS stands for applied research
and development in the fields of industrial manufacturing, medical technology and
improved quality of life. Our research focuses on miniaturized sensors and actuators,
integrated circuits, wireless and wired data communication, and customized MEMS
systems.
Fraunhofer IPMS has years of experience in designing and engineering IP cores for
automotive communication and has a family of TSN IP cores. Many users worldwide
use Fraunhofer IPMS IP cores in the automotive, aerospace, and automation industries,
among others. The multidisciplinary IP design team of Fraunhofer IPMS with expertise
in computer architectures, network structures, RTL design and implementation of
electronic systems is also available as a competent development partner for applicationspecific adaptations of the IP cores as well as their integration into complex network architectures.
Wissenschaftlicher Ansprechpartner:
Andreas Weder - andreas.weder@ipms.fraunhofer.de