Generalizing Amdahl’s Law for Power and Energy

Extending Amdahl\u27s law to identify optimal power-performance configurations requires considering the interactive effects of power, performance, and parallel overhead

MEASURING THE RETURNS TO AGRICULTURAL EXPERIMENT STATION RESEARCH EXPENDITURES FOR CORN, WHEAT AND SOYBEANS

Research and Development/Tech Change/Emerging Technologies,

Molecular Dynamics Simulation of Macromolecules Using Graphics Processing Unit

Molecular dynamics (MD) simulation is a powerful computational tool to study the behavior of macromolecular systems. But many simulations of this field are limited in spatial or temporal scale by the available computational resource. In recent years, graphics processing unit (GPU) provides unprecedented computational power for scientific applications. Many MD algorithms suit with the multithread nature of GPU. In this paper, MD algorithms for macromolecular systems that run entirely on GPU are presented. Compared to the MD simulation with free software GROMACS on a single CPU core, our codes achieve about 10 times speed-up on a single GPU. For validation, we have performed MD simulations of polymer crystallization on GPU, and the results observed perfectly agree with computations on CPU. Therefore, our single GPU codes have already provided an inexpensive alternative for macromolecular simulations on traditional CPU clusters and they can also be used as a basis to develop parallel GPU programs to further speedup the computations.Comment: 21 pages, 16 figure

Determination of the Sign of g factors for Conduction Electrons Using Time-resolved Kerr Rotation

The knowledge of electron g factor is essential for spin manipulation in the field of spintronics and quantum computing. While there exist technical difficulties in determining the sign of g factor in semiconductors by the established magneto-optical spectroscopic methods. We develop a time resolved Kerr rotation technique to precisely measure the sign and the amplitude of electron g factor in semiconductors

Characterizing time series : when Granger causality triggers complex networks

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIH* human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length

Residual Symmetries for Neutrino Mixing with a Large theta_13 and Nearly Maximal delta_D

The residual Z^s_2(k) and bar Z^s_2(k) symmetries induce a direct and unique phenomenological relation with theta_x (= theta_13) expressed in terms of the other two mixing angles, theta_s (= theta_12) and theta_a (= theta_23), and the Dirac CP phase delta_D. Z^s_2(k) predicts a theta_x probability distribution centered around 3^o ~ 6^o with an uncertainty of 2^o to 4^o while those from bar Z^s_2(k) are approximately a factor of two larger. Either result fits the T2K, MINOS and Double CHOOZ measurements. Alternately a prediction for the Dirac CP phase delta_D results in a peak at +-74^o (+-106^o) for Z^s_2(k) or +-123^o (+-57^o) for bar Z^s_2(k) which is consistent with the latest global fit. We also give a distribution for the leptonic Jarslkog invariant J_v which can provide further tests from measurements at T2K and NOvA.Comment: Accepted for publication in PR

Application of Instantons: Quenching of Macroscopic Quantum Coherence and Macroscopic Fermi-Particle Configurations

Starting from the coherent state representation of the evolution operator with the help of the path-integral, we derive a formula for the low-lying levels $E = \epsilon_0 - 2\triangle\epsilon cos (s+\xi)\pi$ of a quantum spin system. The quenching of macroscopic quantum coherence is understood as the vanishing of $cos (s+\xi)\pi$ in disagreement with the suppression of tunneling (i.e. $\triangle\epsilon = 0$) as claimed in the literature. A new configuration called the macroscopic Fermi-particle is suggested by the character of its wave function. The tunneling rate ($(2\triangle\epsilon)/(\pi)$) does not vanish, not for integer spin s nor for a half-integer value of s, and is calculated explicitly (for the position dependent mass) up to the one-loop approximation.Comment: 13 pages, LaTex, no figure

An Analysis Framework for Inter-User Interference in IEEE 802.15.6 Body Sensor Networks: A Stochastic Geometry Approach

Inter-user interference occurs when multiple body sensor networks (BSNs) are transmitting simultaneously in close proximity to each other. Interference analysis in BSNs is challenging due to the hybrid medium access control (MAC) and the specific channel characteristics of BSNs. This paper presents a stochastic geometry analysis framework for inter-user interference in IEEE 802.15.6 BSNs. An extended Matern point process is proposed to model the complex spatial distribution of the interfering BSNs caused by the hybrid MAC defined in IEEE 802.15.6. We employ stochastic geometry approach to evaluate the performance of BSNs, considering the specific channel characteristics of BSNs in the vicinity of human body. Performance metrics are derived in terms of outage probability and spatial throughput in the presence of inter-user interference. We conduct performance evaluation through extensive simulations and show that the simulation results fit well with the analytic results. Insights are provided on the determination of the interference detection range, the BSN density, and the design of MAC for BSNs