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An Adaptive Framework for Managing Heterogeneous Many-Core - ece uprm

An Adaptive Framework for Managing Heterogeneous Many-Core - ece uprm 2025

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The dissertation presents an adaptive framework for managing heterogeneous many-core clusters, focusing on high-performance computing (HPC) systems that utilize specialized accelerators like IBM Cell and GPUs. It addresses challenges in programmability, resource management, and scheduling in asymmetric architectures. The proposed framework includes an extended MapReduce programming model, efficient data prefetching techniques, and energy-aware resource scheduling mechanisms. The research demonstrates significant performance improvements and reduced time-to-solution for data-intensive applications while enabling easier deployment of software components across varying hardware configurations.

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