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Networks-on-chips (NoCs) are gaining in popularity as replacement for shared medium interconnects in chip-multiprocessors (CMPs) and multiprocessor systems-on-chips, and their performance becoming essential to system performance. There have been emerging studies to achieve better power/energy efficiency without performance degradation on NoCs. However, there are still non-negligible latency issues caused by the mechanism of power efficient approaches. To alleviate the latency problem and to transfer data efficiently with the high utilization of interconnect resources, we propose an on-chip network architecture that improves latency and bandwidth. Increasing the data/link widths across the network may considerably resolve this problem but is a costly proposition both in terms of device area and of power. Alternatively, we propose a dual-path router architecture that efficiently exploits path diversity to attain low latency without significant hardware overhead. By: 1) doubling the number of injection and ejection ports; 2) splitting packets into two halves; 3) recomposing routing policy to support path diversity; and 4) provisioning the network hardware design, we can considerably enhance network resource utilization to achieve much higher performance in latency. The proposed simultaneous dual-path routing (SDPR) scheme outperformed the conventional dimension order routing (DOR) technique across synthetic workloads by 31%–40% in average latency and up to a 100% improvement in throughput performance running on a 49-core CMP. Our synthesizable model for the SDPR router and network provides accurate power and area reports. According to the synthesis reports, SDPR incurs insignificant overhead compared to the baseline XY DOR router. [ABSTRACT FROM PUBLISHER]

Current research on sleep using experimental animals is limited by the expense and time-consuming nature of traditional EEG/EMG recordings. We present here an alternative, noninvasive approach utilizing piezoelectric films configured as highly sensitive motion detectors. These film strips attached to the floor of the rodent cage produce an electrical output in direct proportion to the distortion of the material. During sleep, movement associated with breathing is the predominant gross body movement and, thus, output from the piezoelectric transducer provided an accurate respiratory trace during sleep. During wake, respiratory movements are masked by other motor activities. An automatic pattern recognition system was developed to identify periods of sleep and wake using the piezoelectric generated signal. Due to the complex and highly variable waveforms that result from subtle postural adjustments in the animals, traditional signal analysis techniques were not sufficient for accurate classification of sleep versus wake. Therefore, a novel pattern recognition algorithm was developed that successfully distinguished sleep from wake in approximately 95% of all epochs. This algorithm may have general utility for a variety of signals in biomedical and engineering applications. This automated system for monitoring sleep is noninvasive, inexpensive, and may be useful for large-scale sleep studies including genetic approaches towards understanding sleep and sleep disorders, and the rapid screening of the efficacy of sleep or wake promoting drugs. [ABSTRACT FROM AUTHOR]