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Efficient runtime resource allocation is critical to the overall performance and energy consumption of many-core systems. A region of free cores is allocated for each newly launched application. The cores are deallocated when the corresponding applications finish execution. The frequent allocations and deallocations of the cores might leave free cores scattered (not forming a contiguous region). This...
The conventional approaches to reduce the energy consumption of high performance computing (HPC) data centers focus on consolidation and dynamic voltage and frequency scaling (DVFS). Most of these approaches consider independent tasks (or jobs) and do not jointly optimize for energy and value. In this paper, we propose DVFS-aware profiling and non-profiling based approaches that use design-time profiling...
Nelder-Mead algorithm (NMA) is the best-known algorithm for multidimensional optimization without involving derivative computations. Due to the simplicity in implementation and the fast convergent property of NMA, it is widely used in the fields of statistics, engineering, physics and medical sciences. In practice, when objective function is complicated, the optimization procedure requires a lot of...
The advancement in process technology has enabled integration of different types of processing cores into a single chip towards creating heterogeneous Multiprocessor Systems-on-Chip (MPSoCs). While providing high level of computation power to support complex applications, these modern systems also introduce novel challenges for system designers, like managing a huge number of mappings (application...
The reliance on multi/many-core systems to satisfy the high performance requirement of complex embedded software applications is increasing. This necessitates the need to realize efficient mapping methodologies for such complex computing platforms. This paper provides an extensive survey and categorization of state-of-the-art mapping methodologies and highlights the emerging trends for multi/many-core...
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