This paper describes a technique for calculating the switching activity of a set of registers shared by dierent data values. Based on the assumption that the joint pdf (probability density function) of the primary input random variables is known or that a suciently large number of input vectors has been given, the register assignment problem for minimum power consumption is formulated as a minimum cost clique covering of an appropriately dened compatibility graph (which is shown to be transitively orientable). The problem is then solved optimally (in polynomial time) using a max-cost ow algorithm. Experimental results conrm the viability and usefulness of the approach in minimizing power consumption during the register assignment phase of the behavioral synthesis process.
Abstract. Regional monitoring of rock slope failures by the seismic technique is rarely studied due to significant source location errors, and it still lacks the signal features needed for understanding events of this type because of the complex mass movement involved. To better understand events of this type, ten known events along highways in Taiwan were analyzed. First, a hybrid approach (GeoLoc) composed of cross-correlation-based and amplitude-attenuation-based approaches was applied, and it produced a location error of maximum 3.19 km for the ten events. Then, we analyzed the ratio of local magnitude (ML) and duration magnitude (MD) and found that a threshold of 0.85 yields successful classification between rock slope failure and earthquake. Further, the GeoLoc can retrieve the seismic parameters, such as signal amplitude at the source (A0) and ML of events, which are crucial for constructing scaling law with source volume (V). Indeed, Log(V) = 1.12 ML + 3.08 and V = 77,290 A00.44 derived in this study provide the lower bound of volume estimation, since the seismic parameters based on peak amplitudes cannot represent the full process of mass loss. Second, while video records correspond with seismic signals, the processes of toppling and sliding present column- and V-shaped spectrograms, respectively. The impacts of rockfall directly link directly to the pulses of seismic signals. Here, all spectrogram features of events can be identified by event volumes larger than 2,000 m3, corresponding to the farthest epicenter distance ~2.5 km. The previous results were obtained using the GeoLoc scheme for providing the government rapid reports for reference. Finally, a recent event on 12th June 2020 was used to examine the GeoLoc scheme’s feasibility. We estimated the event's volume by the two scalings: 3,838 m3 and 3,019 m3, which was roughly consistent with the volume estimation of 5,142 m3 from the digital elevation model. The physical processes, including rockfall, toppling, and complex motion behaviors of rock interacting with slope inferred from the spectrogram features were comprehensively supported by the video record and field investigation. We also demonstrated that the GeoLoc scheme, which has been implemented in Sinwulu catchment, Taiwan, can provide fast reports, including the location, volume, and physical process of events of this type to the public soon after they occur.
Abstract-We present a dynamic programming technique for solving the multiple supply voltage scheduling problem in both nonpipelined and functionally pipelined data-paths. The scheduling problem refers to the assignment of a supply voltage level (selected from a fixed and known number of voltage levels) to each operation in a data flow graph so as to minimize the average energy consumption for given computation time or throughput constraints or both. The energy model is accurate and accounts for the input pattern dependencies, re-convergent fanout induced dependencies, and the energy cost of level shifters. Experimental results show that using three supply voltage levels on a number of standard benchmarks, an average energy saving of 40.19% (with a computation time constraint of 1.5 times the critical path delay) can be obtained compared to using a single supply voltage level.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.