Search for dissertations about: "Masoud Daneshtalab"

Showing result 1 - 5 of 7 swedish dissertations containing the words Masoud Daneshtalab.

  1. 1. Configuration and Timing Analysis of TSN-based Distributed Embedded Systems

    Author : Bahar Houtan; Saad Mubeen; Seyed Mohammad Hossein Ashjaei; Mikael Sjödin; Masoud Daneshtalab; Jean-Luc Scharbarg; Mälardalens universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Computer Science; datavetenskap;

    Abstract : The set of IEEE Time-Sensitive Networking (TSN) standards is an emerging candidate for backbone communication in modern applications of real-time distributed embedded systems. TSN provides various traffic shaping mechanisms that aim at managing the timing requirements of traffic. READ MORE

  2. 2. DeepMaker : Customizing the Architecture of Convolutional Neural Networks for Resource-Constrained Platforms

    Author : Mohammad Loni; Mikael Sjödin; Masoud Daneshtalab; Franz Pernkopf; Mälardalens högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Computer Science; datavetenskap;

    Abstract : Convolutional Neural Networks (CNNs) suffer from energy-hungry implementation due to requiring huge amounts of computations and significant memory consumption. This problem will be more highlighted by the proliferation of CNNs on resource-constrained platforms in, e.g., embedded systems. READ MORE

  3. 3. Efficient Design of Scalable Deep Neural Networks for Resource-Constrained Edge Devices

    Author : Mohammad Loni; Mikael Sjödin; Masoud Daneshtalab; Franz Pernkopf; Mälardalens universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Computer Science; datavetenskap;

    Abstract : Deep Neural Networks (DNNs) are increasingly being processed on resource-constrained edge nodes (computer nodes used in, e.g., cyber-physical systems or at the edge of computational clouds) due to efficiency, connectivity, and privacy concerns. READ MORE

  4. 4. DeepKit: a multistage exploration framework for hardware implementation of deep learning

    Author : Mohammad Riazati; Masoud Daneshtalab; Mikael Sjödin; Björn Lisper; Diana Goehringer; Mälardalens universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Computer Science; datavetenskap;

    Abstract : Deep Neural Networks (DNNs) are widely adopted to solve different problems ranging from speech recognition to image classification. DNNs demand a large amount of processing power, and their implementation on hardware, i.e., FPGA or ASIC, has received much attention. READ MORE

  5. 5. Reliability and Performance in Heterogeneous Systems Generated by High-Level Synthesis

    Author : Mohammad Riazati; Masoud Daneshtalab; Diana Goehringer; Mälardalens högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Computer Science; datavetenskap;

    Abstract : High-level synthesis (HLS) is now widely used to implement heterogeneous systems. It was invented to enable designers to use high-level languages such as C or C++. It makes it possible for the software developers to move their implementations to an FPGA or ASIC without having to know the hardware details. READ MORE