Sökning: "Hardware Software Co-Design"

Visar resultat 1 - 5 av 17 uppsatser innehållade orden Hardware Software Co-Design.

  1. 1. Validation of theoretical cost model for Power and Reliability : Case study of a reliable Central Direct Memory Access system

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Sonal Shrivastava; [2021]
    Nyckelord :Single event upsets; Extra-functional properties; System on Chip; Mean Time Between Failure; Power consumption; Enstaka händelse störs; Extra funktionella egenskaper; System på chip; Medeltid mellan misslyckande; Energiförbrukning;

    Sammanfattning : Safety-critical applications employed in automotive, avionics and aerospace domains are placed under strict demands for performance, power efficiency and fault tolerance. Development of system hardware and software satisfying all criteria is challenging and time-consuming. LÄS MER

  2. 2. An Investigative Study of Testing Strategy and Test Case Creation in a Hardware-Software Co-design Environment Using Software Product Line Theory

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Stina Långström; [2021]
    Nyckelord :Variability analysis; Software product line; Testing; Test case categorization; Testing strategy; Feature modeling; Variationsanalys; Software product line; Testning; Testfallskategorisering; Funktionsmodellering;

    Sammanfattning : The requirements for software products have increased in recent years. This is both due to more complex technology as well as more requirements from the customers. An approach to solve this issue is by using a software product line (SPL) where reusable assets are developed to produce more tailor-made products with reduced time to market. LÄS MER

  3. 3. Implementation of a Deep Learning Inference Accelerator on the FPGA.

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Shenbagaraman Ramakrishnan; [2020]
    Nyckelord :Artificial Intelligence; Machine Learning; Deep Learning; Neural Networks; Deep Learning Accelerators; NVDLA; FPGA; Technology and Engineering;

    Sammanfattning : Today, Artificial Intelligence is one of the most important technologies, ubiquitous in our daily lives. Deep Neural Networks (DNN's) have come up as state of art for various machine intelligence applications such as object detection, image classification, face recognition and performs myriad of activities with exceptional prediction accuracy. LÄS MER

  4. 4. Programmable Address Generation Unit for Deep Neural Network Accelerators

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Muhammad Jazib Khan; [2020]
    Nyckelord :Address Generation Unit; Deep Neural Network Accelerators; Very Long Instruction Word; Application Specific Instruction Processor; Hardware-Software Co-design; Adressgenereringsenhet; Deep Neural Network Accelerators; Mycket långt instruktionsord; Applikationsspecifik instruktionsprocessor; Hårdvaruprogramvara Samdesign;

    Sammanfattning : The Convolutional Neural Networks are getting more and more popular due to their applications in revolutionary technologies like Autonomous Driving, Biomedical Imaging, and Natural Language Processing. With this increase in adoption, the complexity of underlying algorithms is also increasing. LÄS MER

  5. 5. A Data Sorting Hardware Accelerator on FPGA

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Boyan Liu; [2020]
    Nyckelord :Data Sorting; Hardware Accelerator Algorithm; Block Circuit; FPGA;

    Sammanfattning : In recent years, with the rise of the application of big data, efficiency has become more important for data processing, and simple sorting methods require higher stability and efficiency in large-scale scenarios. This thesis explores topics related to hardware acceleration for data sorting networks of massive input resource or data stream, which leads to our three different design approaches: running the whole data processing fully on the software side (sorting and merging on PC), a combination of PC side and field- programmable gate arrays (FPGA) platform (hardware sorting with software merging), and fully hardware side (sorting and merging on FPGA). LÄS MER