Search for dissertations about: "Zain Ul-abdin"
Showing result 1 - 5 of 7 swedish dissertations containing the words Zain Ul-abdin.
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1. Programming of coarse-grained reconfigurable architectures
Abstract : Coarse-grained reconfigurable architectures, which offer massive parallelism coupled with the capability of undergoing run-time reconfiguration, are gaining attention in order to meet not only the increased computational demands of high-performance embedded systems, but also to fulfill the need of adaptability to functional requirements of the application. This thesis focuses on the programming aspects of such coarse-grained reconfigurable computing devices, including the relevant computation models that are capable of exposing different kinds of parallelism inherent in the application and the ability of these models to capture the adaptability requirements of the application. READ MORE
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2. Compiling Concurrent Programs for Manycores
Abstract : The arrival of manycore systems enforces new approaches for developing applications in order to exploit the available hardware resources. Developing applications for manycores requires programmers to partition the application into subtasks, consider the dependence between the subtasks, understand the underlying hardware and select an appropriate programming model. READ MORE
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3. Tools to Compile Dataflow Programs for Manycores
Abstract : The arrival of manycore systems enforces new approaches for developing applications in order to exploit the available hardware resources. Developing applications for manycores requires programmers to partition the application into subtasks, consider the dependence between the subtasks, understand the underlying hardware and select an appropriate programming model. READ MORE
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4. Pragma-Based Approach For Mapping DSP Functions On A Coarse Grained Reconfigurable Architecture
Abstract : .... READ MORE
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5. Exploring Efficient Implementations of Deep Learning Applications on Embedded Platforms
Abstract : The promising results of deep learning (deep neural network) models in many applications such as speech recognition and computer vision have aroused a need for their realization on embedded platforms. Augmenting DL (Deep Learning) in embedded platforms grants them the support to intelligent tasks in smart homes, mobile phones, and healthcare applications. READ MORE