Dynamic remapping decisions in multi-phase parallel computations

The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary

An optimal repartitioning decision policy

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem

Constraints from TcT_c and the isotope effect for MgB2_2

With the constraint that $T_c = 39$ K, as observed for MgB$_2$, we use the Eliashberg equations to compute possible allowed values of the isotope coefficient, $\beta$. We find that while the observed value $\beta= 0.32$ can be obtained in principle, it is difficult to reconcile a recently calculated spectral function with such a low observed value

The influence of the atmospheric boundary layer on nocturnal layers of noctuids and other moths migrating over southern Britain

Insects migrating at high altitude over southern Britain have been continuously monitored by automatically-operating, vertical-looking radars over a period of several years. During some occasions in the summer months, the migrants were observed to form well-defined layer concentrations, typically at heights of 200-400 m, in the stable night-time atmosphere. Under these conditions, insects are likely to have control over their vertical movements and are selecting flight heights which are favourable for long-range migration. We therefore investigated the factors influencing the formation of these insect layers by comparing radar measurements of the vertical distribution of insect density with meteorological profiles generated by the UK Met. Office’s Unified Model (UM). Radar-derived measurements of mass and displacement speed, along with data from Rothamsted Insect Survey light traps provided information on the identity of the migrants. We present here three case studies where noctuid and pyralid moths contributed substantially to the observed layers. The major meteorological factors influencing the layer concentrations appeared to be: (a) the altitude of the warmest air, (b) heights corresponding to temperature preferences or thresholds for sustained migration and (c), on nights when air temperatures are relatively high, wind-speed maxima associated with the nocturnal jet. Back-trajectories indicated that layer duration may have been determined by the distance to the coast. Overall, the unique combination of meteorological data from the UM and insect data from entomological radar described here show considerable promise for systematic studies of high-altitude insect layering

The Coupled Electronic-Ionic Monte Carlo Simulation Method

Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have developed to perform QMC for the electrons coupled to a classical Monte Carlo simulation of the ions. In this method, one estimates the Born-Oppenheimer energy E(Z) where Z represents the ionic degrees of freedom. That estimate of the energy is used in a Metropolis simulation of the ionic degrees of freedom. Important aspects of this method are how to deal with the noise, which QMC method and which trial function to use, how to deal with generalized boundary conditions on the wave function so as to reduce the finite size effects. We discuss some advantages of the CEIMC method concerning how the quantum effects of the ionic degrees of freedom can be included and how the boundary conditions can be integrated over. Using these methods, we have performed simulations of liquid H2 and metallic H on a parallel computer.Comment: 27 pages, 10 figure

Cognitive behaviour therapy versus counselling intervention for anxiety in young people with high-functioning autism spectrum disorders: a pilot randomised controlled trial

The use of cognitive-behavioural therapy (CBT) as a treatment for children and adolescents with autism spectrum disorder (ASD) has been explored in a number of trials. Whilst CBT appears superior to no treatment or treatment as usual, few studies have assessed CBT against a control group receiving an alternative therapy. Our randomised controlled trial compared use of CBT against person-centred counselling for anxiety in 36 young people with ASD, ages 12–18. Outcome measures included parent- teacher- and self-reports of anxiety and social disability. Whilst each therapy produced improvements inparticipants, neither therapy was superior to the other to a significant degree on any measure. This is consistent with findings for adults

Presolar He and Ne Isotopes in Single Circumstellar SiC Grains

Noble gas isotopes in presolar silicon carbide (SiC) dust grains from primitive meteorites provide, together with major element isotopic compositions, insight into the nucleosynthetic output of different types of evolved stars >4.5 Gyr ago. We report here new results from helium and neon isotopic analyses of single presolar SiC grains with sizes between 0.6 and 6.3 μm using an ultrahigh sensitivity mass spectrometer. These noble gas studies were complemented by an ion microprobe study (NanoSIMS) of Si, C, and N isotopic compositions of the same grains. About 40%, or 46 of the 110 grains analyzed, contain nucleosynthetic 22Ne and/or 4He from their parent stars above our mass spectrometer's detection limit. We discuss the possible stellar sources using isotopic ratios as constraints combined with new model predictions for low- to intermediate-mass (1.5, 2, 3, and 5 M☉) asymptotic giant branch (AGB) stars of different metallicities (1, 1/2, 1/3, and 1/6 Z☉). Most SiC grains are of the mainstream type and originated in low-mass AGB stars. We find a higher-than-expected percentage of A/B type grains, with some containing 22Ne and/or 4He. In addition, we find one noble gas-rich nova grain candidate, one supernova grain (X-type grain), and one 22Ne-rich X- or Z-type grain candidate

Radio emission from Supernova Remnants

The explosion of a supernova releases almost instantaneously about 10^51 ergs of mechanic energy, changing irreversibly the physical and chemical properties of large regions in the galaxies. The stellar ejecta, the nebula resulting from the powerful shock waves, and sometimes a compact stellar remnant, constitute a supernova remnant (SNR). They can radiate their energy across the whole electromagnetic spectrum, but the great majority are radio sources. Almost 70 years after the first detection of radio emission coming from a SNR, great progress has been achieved in the comprehension of their physical characteristics and evolution. We review the present knowledge of different aspects of radio remnants, focusing on sources of the Milky Way and the Magellanic Clouds, where the SNRs can be spatially resolved. We present a brief overview of theoretical background, analyze morphology and polarization properties, and review and critical discuss different methods applied to determine the radio spectrum and distances. The consequences of the interaction between the SNR shocks and the surrounding medium are examined, including the question of whether SNRs can trigger the formation of new stars. Cases of multispectral comparison are presented. A section is devoted to reviewing recent results of radio SNRs in the Magellanic Clouds, with particular emphasis on the radio properties of SN 1987A, an ideal laboratory to investigate dynamical evolution of an SNR in near real time. The review concludes with a summary of issues on radio SNRs that deserve further study, and analyzing the prospects for future research with the latest generation radio telescopes.Comment: Revised version. 48 pages, 15 figure

The Interstellar Environment of our Galaxy

We review the current knowledge and understanding of the interstellar medium of our galaxy. We first present each of the three basic constituents - ordinary matter, cosmic rays, and magnetic fields - of the interstellar medium, laying emphasis on their physical and chemical properties inferred from a broad range of observations. We then position the different interstellar constituents, both with respect to each other and with respect to stars, within the general galactic ecosystem.Comment: 39 pages, 12 figures (including 3 figures in 2 parts

A Constrained Path Monte Carlo Method for Fermion Ground States

We describe and discuss a recently proposed quantum Monte Carlo algorithm to compute the ground-state properties of various systems of interacting fermions. In this method, the ground state is projected from an initial wave function by a branching random walk in an over-complete basis of Slater determinants. By constraining the determinants according to a trial wave function $|\psi_T\rangle$, we remove the exponential decay of signal-to-noise ratio characteristic of the sign problem. The method is variational and is exact if $|\psi_T\rangle$ is exact. We illustrate the method by describing in detail its implementation for the two-dimensional one-band Hubbard model. We show results for lattice sizes up to $16\times 16$ and for various electron fillings and interaction strengths. Besides highly accurate estimates of the ground-state energy, we find that the method also yields reliable estimates of other ground-state observables, such as superconducting pairing correlation functions. We conclude by discussing possible extensions of the algorithm.Comment: 29 pages, RevTex, 3 figures included; submitted to Phys. Rev.