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• W2912237310 abstract "Power-efficient architectures have become the most important feature required for future embedded systems. Modern designs, like those released on mobile devices, reveal that clusterisation is the way to improve energy efficiency. However, such architectures are still limited by the memory subsystem (i.e. memory latency problems). This work investigates an alternative approach that exploits on-chip data locality to a large extent, through distributed shared memory systems that permit efficient reuse of on-chip mapped data in clusterised many-core architectures. First, this work reviews the current literature on memory allocations and explores the limitations of cluster-based many-core architectures. Then, several memory allocations are introduced and benchmarked scalability, performance and energy-wise against the conventional centralised shared memory solution in order to reveal which memory allocation is the most appropriate for future mobile architectures. The results show that distributed shared memory allocations bring performance gains and opportunities to reduce energy consumption." @default.
• W2912237310 created "2019-02-21" @default.
• W2912237310 creator A5004806356 @default.
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• W2912237310 date "2019-04-24" @default.
• W2912237310 modified "2023-10-07" @default.
• W2912237310 title "Exploiting memory allocations in clusterised many‐core architectures" @default.
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• W2912237310 doi "https://doi.org/10.1049/iet-cdt.2018.5136" @default.
• W2912237310 hasPublicationYear "2019" @default.
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