The work deals with the design of a USB floppy drive driver. It describes the theory needed to design your own floppy drive driver and the output of individual components. The following is a schematic of the floppy drive driver design. The functions for controlling the floppy drive are described, as well as the pitfalls of the ATSAMD21J18A-AU processor used.

Increasingly, soft processors are being considered for use within FPGA-based reliable computing systems. In an environment in which radiation is a concern, such as space, the logic and routing (configuration memory) of soft processors are sensitive to radiation effects, including single event upsets (SEUs). Thus, effective tools are needed to evaluate and estimate how sensitive the configuration memories of soft processors are in high-radiation environments. A high-speed FPGA fault injection system and methodology were created using the Xilinx Radiation Test Consortium's (XRTC's) Virtex-5 radiation test hardware to conduct exhaustive tests of the SEU sensitivity of a design within an FPGA's configuration memory. This tool was used to show that the sensitivity of the configuration memory of a soft processor depends on several variables, including its microarchitecture, its customizations and features, and the software instructions that are executed. The fault injection experiments described in this thesis were performed on five different soft processors, i.e., MicroBlaze, LEON3, Arm Cortex-M0 DesignStart, OpenRISC 1200, and PicoBlaze. Emphasis was placed on characterizing the sensitivity of the MicroBlaze soft processor and the dependence of the sensitivity on various modifications. Seven benchmarks were executed through the various experiments and used to determine the SEU sensitivity of the soft processor's configuration memory to the instructions that were executed. In this thesis, a wide variety of soft processor fault injection results are presented to show the differences in sensitivity between multiple soft processors and the software they run.

Uttrycket Internet of Things växer sig större och större och världen är på väg att ha 50miljarder uppkopplade enheter till 2020. IoT-enheter är beroende av att ha en låg effektförbrukningoch därför är en processor med låg effektförbrukning viktigt att ha. Denna studieutför tester på två strömsnåla processorer för att komma fram till vilken processor somär mest lämplig till vilken IoT-produkt. Testningen utgick från tre applikationer som i sintur baseras på verkliga IoT-situationer. De tre applikationerna har olika intesitetsnivåer. Iden första applikationen arbetar processorerna inte särskilt hårt, I den andra applikationenfår processorena arbeta mer och i den tredje applikationen får processorerna jobba somhårdast. Effektförbrukningen mäts med hjälp av Atmel Power debugger. Resultatet visaratt IoT-enheter som inte är särskilt aktiva har en lägre effektförbrukning med en 8-bitarsprocessor men en IoT-enhet som är mer aktiv har lägre effektförbrukning med Cortex-M0+baserad 32-bitars processor. / The term Internet of Things grows bigger and bigger and the world is about to have 50 billionconnected devices. IoT devices are dependent on low power consumption and thereforea low power processor is important to have. This study performs tests on two power-savingprocessors to determine which processor is most suitable for an IoT product. The test wasbased on three applications, which in turn are based on actual IoT situations. The threeapplications have different levels of intency. In the first application, the processors do notwork very hard. In the second application, the processors get more work and in the thirdapplication, the processors get the hardest work. Power consumption is measured usingAtmel Power debugger The result shows that low-active IoT devices have a lower powerconsumption with an 8-bit processor, but an IoT device that is more active has lower powerconsumption with a Cortex-M0 + based 32-bit processor.