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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)
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)
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)
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 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)
Constantly advancing integration capability is paving the way for the construction of the extremely large scale continuum of the Internet where entities or things from vastly varied domains are uniquely addressable and interacting seamlessly to form a giant networked system of systems known as the Internet-of-Things (IoT). In contrast to this visionary(More)