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2. Deep Learning on Low Power Embedded Devices Using RISC-V Cores with an Extended Instruction Set : master's thesisJure Vreča, 2020, master's thesis Abstract: This thesis explores the possibility of running neural networks on microcontrollers and how
to optimize their performance using instruction set extensions. Microcontrollers are seen as
too weak to run neural networks. We challenge this view and show that stripped-down neural
networks can run and be useful for some applications. We used an open-source microcontroller
called PULPino to run our neural network. The benefit of various instructions and optimizations
for minimizing energy consumption to run deep learning algorithms was evaluated. Hardware
loops, loop unrolling, and the dot-product unit were implemented and tested.
We developed an FPGA-based testing system to evaluate our hardware. We also developed a
deep learning library and a test neural network for our hardware. We wrote two versions of
the deep learning library. One version is the reference code, and the other is the optimized
code that uses the dot product unit. Using the testing system, we tested the performance of
the two versions. The synthesis was run to determine the power and energy consumption. We
also tried out various optimizations to see if the performance could be improved.
Using instruction set extensions and algorithmic optimizations we reduced the clock cycle count by 72% for the convolutional layers and by 78% for fully-connected layers. This reduced
power consumption by 73%. We compare our results with related research.
Keywords: deep learning, embedded system, instruction set, RISC-V
Published in DKUM: 03.11.2020; Views: 1556; Downloads: 166
 Full text (2,69 MB) |
3. Design of an Embedded Position Sensor with Sub-mm Accuracy : magistrsko deloMatej Nogić, 2019, master's thesis Abstract: This master’s thesis presents the development of a machine-vision based localization unit developed at Robert Bosch GmbH, Corporate Sector Research and Advance Engineering in Renningen, Germany. The localization unit was developed primarily for position detection purposes with three degrees of freedom in highly versatile manufacturing systems but has an immense potential to be used anywhere where a precise, low-cost localization method on a two-dimensional surface is required. The complete product development cycle was carried out, from the components selection, schematic and optical system design, to the development of machine vision algorithms, four-layer Printed Circuit Board design and evaluation using an industrial robot. Thanks to the use of a patented two-dimensional code pattern, the localization unit can cover a surface area of 49 km2. The size and speed optimized, self-developed machine-vision algorithms running on a Cortex-M7 microcontroller allow achieving an accuracy of 100 µm and 60 Hz refresh rate.
Keywords: localization, machine-vision, code pattern, image sensor, embedded system
Published in DKUM: 14.01.2020; Views: 1340; Downloads: 60
Full text (18,20 MB) |
4. Development of RFID/NFC based access control systemDarko Topić, 2018, master's thesis Abstract: The master thesis describes the development of NFC/RFID access control system based on the ARM platform. The access control system is widely used in different applications. The goal of this thesis is to develop a smart NFC access control system used for accessing an elevator, where users could use only NFC tags to access a specific floor. The design of the proposed NFC access control system is based on the ARM platform, while the developed NFC antenna guarantees wide scanning range. At the end of the thesis the results are presented.
Keywords: access control system, RFID, NFC, MIFARE, ARM processor, embedded system, short-range communication, contactless communication, ISO/IEC 14443
Published in DKUM: 23.05.2018; Views: 5441; Downloads: 639
Full text (7,51 MB) |
5. The Internet of Things Communication Protocol for Devices with Low Memory FootprintSašo Vinkovič, Milan Ojsteršek, original scientific article Abstract: This paper describes a new communication protocol named XMC which is designed for the transmission of messages between an embedded device and a remote system. A new markup language called XMDD has also been developed and is used to describe the functional profile of the embedded device. The main advantage of the XMC communication protocol is its flexibility and independence from the device type. It is suitable for communication with devices that have a curtailed amount of working memory (a few kB) and limited computing power, i.e. 8-bit or 16-bit microcontrollers. Messaging between the embedded device and the remote systems is done without any interference with the basic source code of the embedded device, thus allowing access to all functionalities and features of the connectable embedded device and is based on the functionality dictionary and built-in features of an embedded device. It also maintains a low production price for the embedded device and from the programming point of view provides a transparent and flexible upgrade of the hardware and software without any redundancy input.
Keywords: communication protocol, internet of things, home automation, functional profile, smart appliance, code generation, embedded system, framework
Published in DKUM: 21.12.2014; Views: 2653; Downloads: 117
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