Browsing by Subject "Systems on a chip."
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Item Open Access Adaptive thread and memory access schelduling in chip multiprocessors(Bilkent University, 2013) Aktürk, İsmailThe full potential of chip multiprocessors remains unexploited due to architecture oblivious thread schedulers used in operating systems, and thread-oblivious memory access schedulers used in off-chip main memory controllers. For the thread scheduling, we introduce an adaptive cache-hierarchy-aware scheduler that tries to schedule threads in a way that inter-thread contention is minimized. A novel multi-metric scoring scheme is used that specifies the L1 cache access characteristics of a thread. The scheduling decisions are made based on multi-metric scores of threads. For the memory access scheduling, we introduce an adaptive compute-phase prediction and thread prioritization scheme that efficiently categorize threads based on execution characteristics and provides fine-grained prioritization that allows to differentiate threads and prioritize their memory access requests accordingly.Item Open Access Application-specific heterogeneous network-on-chip design(Bilkent University, 2011) Demirbaş, DilekWith increasing communication demands of processors and memory cores in Systems-on-Chips (SoCs), application-specific and scalable Network-on-Chips (NoCs) are emerged to interconnect processing cores and subsystems in Multiprocessor System-on-Chips (MPSoCs). The challenge of application-specific NoC design is to find the right balance among different trade-offs such as communication latency, power consumption, and chip area. This thesis introduces a novel heterogeneous NoC design approach where biologically inspired evolutionary algorithm and 2-dimensional rectangle packing algorithm are used to place the processing elements with various properties into a constrained NoC area according to the tasks generated by Task Graph for Free (TGFF). TGFF is one of the pseudo-random task graph generators used for scheduling and allocation. Based on a given task graph, we minimize the maximum execution time in a Heterogeneous Chip-Multiprocessor. We specifi- cally emphasize on the communication cost as it is a big overhead in a multi-core architecture. Experimental results show that our approach improves total communication latency up to 27% with modest power consumption.