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Cloud Computing is a promising approach to handle the growing needs for computation and storage in an efficient and cost-effective manner. Towards this end, characterizing workloads in the cloud infrastructure (e.g., a data center) is essential for performing cloud optimizations such as resource provisioning and energy minimization. However, there is a huge(More)
Protein folding is critical for many biological processes. In this work, we propose an NoC-based multi-core platform for protein folding computation. We first identify the speedup bottleneck for applying conventional genetic algorithm on a mesh-based multi-core platform. Then, we address this computation- and communication- intensive problem while taking(More)
The astonishing rate of sensing modalities and data generation poses a tremendous impact on computing platforms for providing real-time mining and prediction capabilities. We are capable of monitoring thousands of genes and their interactions, but we lack efficient computing platforms for large-scale (exa-scale) data processing. Towards this end, we propose(More)
Capturing the mathematical features of physical and cyber processes is essential for endowing the CPS with built-in intelligence. In this paper, we develop a compact yet accurate mathematical model able to capture the spatio-temporal fractal cross-dependencies between coupled processes and illustrate its benefits within the context of brain-machine-body(More)
The continuous increase in integration densities contributed to a shift from Dennard's scaling to a parallelization era of multi-/many-core chips. However, for multicores to rapidly percolate the application domain from consumer multimedia to high-end functionality (e.g., security, healthcare, big data), power/energy and thermal efficiency challenges must(More)
The impact of dark silicon phenomenon on multicore processors under deeply-scaled FinFET technologies is investigated in this paper. To do this accurately, a cross-layer framework, spanning device, circuit, and architecture levels is initially introduced. Using this framework, leakage and dynamic power consumptions as well as frequency levels of in-order(More)
Physiological signals are often spatiotemporal dependent. Some of these signals include electroencephalogram (EEG), electromyogram (EMG) or electrocardiogram (ECG) signals, just to name a few. Coupled-fractional dynamical systems have shown to capture such properties, but methods to determine where to place sensors for these dynamical systems are still(More)