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Future low-end embedded systems will make an increased use of heterogeneous MPSoCs. To utilize these systems efficiently, methods and tools are required that support the extraction and implementation of parallelism typically found in embedded applications. Ideally, large amounts of existing legacy code should be reused and ported to these new systems. Existing parallelization infrastructures, however,...
Heterogeneous multi-core platforms are increasingly attractive for embedded applications due to their adaptability and efficiency. This proliferation of heterogeneity demands new approaches for extracting thread level parallelism from sequential applications which have to be efficient at runtime. We present, to the best of our knowledge, the first Integer Linear Programming (ILP)-based parallelization...
Heterogeneous MPSoCs are used in a large fraction of current embedded systems. In order to efficiently exploit the available processing power, advanced parallelization techniques are required. In addition to consider performance variances between heterogeneous cores, these methods have to be multi-objective aware to be useful for resource restricted embedded systems. This multi-objective optimization...
Automatic parallelization of sequential applications is the key for efficient use and optimization of current and future embedded multi-core systems. However, existing approaches often fail to achieve efficient balancing of tasks running on heterogeneous cores of an MPSoC. A reason for this is often insufficient knowledge of the underlying architecture's performance. In this paper, we present a novel...
The MADNESS project aims at the definition of innovative system-level design methodologies for embedded MP-SoCs, extending the classic concept of design space exploration in multi-application domains to cope with high heterogeneity, technology scaling and system reliability. The main goal of the project is to provide a framework able to guide designers and researchers to the optimal composition of...
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