Caladan: a distributed meta-OS for data center disaggregation

Data center resource disaggregation promises cost savings by pool-ing compute, storage and memory resources into separate, net-worked nodes. The benefits of this model are clear, but a closer lookshows that its full performance and efficiency potential cannot beeasily realized. Existing systems use CPUs pervasively to interface ar-bitrary devices with the network and to orchestrate communicationamong them, reducing the benefits of disaggregation.In this paper we presentCaladan, a novel system with a trusteduni-versal resource fabricthat interconnects all resources and efficientlyoffloads the system and application control planes to SmartNICs,freeing server CPUs to execute application logic. Caladan offersthree core services: capability-driven distributed name space, virtualdevices, and direct inter-device communications. These servicesare implemented in a trustedmeta-kernelthat executes in per-nodeSmartNICs. Low-level device drivers running on the commodity hostOS are used for setting up accelerators and I/O devices, and exposingthem to Caladan. Applications run in a distributed fashion acrossCPUs and multiple accelerators, which in turn can directly performI/O, i.e., access files, other accelerators or host services. Our dis-tributed dataflow runtime runs on top of this substrate. It orchestratesthe distributed execution, connecting disaggregated resources usingdata transfers and inter-device communication, while eliminatingthe performance bottlenecks of the traditional CPU-centric design

'I like money, I like many things'. The relationship between drugs and crime from the perspective of young people in contact with criminal justice systems

Based on research undertaken as part of the EU funded EPPIC project, this paper aims to update and elaborate on the relationship between drug use and offending behaviours by exploring variations within a cross-national sample of drug-experienced young people in touch with criminal justice systems. Adopting a trajectory-based approach, interviews were undertaken with 198 young people aged 15–25 in six European countries (Austria, Denmark, Germany, Italy, Poland, and UK). Data were analysed by applying the Bennett and Holloway categorization of the drugs-crime link, with a focus on the concept of social exclusion as developed by Seddon. Three main types of mechanisms (economic, pharmaceutical, and lifestyles) are used to interpret the data, showing how the relationship between drugs and offending can vary according to type of substances and over time. Furthermore, it can be associated with very different degrees of social exclusion and needs. The results suggest that while economic inequalities still play key roles in explaining drug use and offending, both behaviours can originate from a state of relative deprivation, resulting from the contradictions inherent in ‘bulimic societies’ that raise aspirations and desires while providing young people scarce opportunities for self-realisation and social recognition

Distribution of the time at which the deviation of a Brownian motion is maximum before its first-passage time

We calculate analytically the probability density $P(t_m)$ of the time $t_m$ at which a continuous-time Brownian motion (with and without drift) attains its maximum before passing through the origin for the first time. We also compute the joint probability density $P(M,t_m)$ of the maximum $M$ and $t_m$. In the driftless case, we find that $P(t_m)$ has power-law tails: $P(t_m)\sim t_m^{-3/2}$ for large $t_m$ and $P(t_m)\sim t_m^{-1/2}$ for small $t_m$. In presence of a drift towards the origin, $P(t_m)$ decays exponentially for large $t_m$. The results from numerical simulations are in excellent agreement with our analytical predictions.Comment: 13 pages, 5 figures. Published in Journal of Statistical Mechanics: Theory and Experiment (J. Stat. Mech. (2007) P10008, doi:10.1088/1742-5468/2007/10/P10008

Area distribution and the average shape of a L\'evy bridge

We consider a one dimensional L\'evy bridge x_B of length n and index 0 < \alpha < 2, i.e. a L\'evy random walk constrained to start and end at the origin after n time steps, x_B(0) = x_B(n)=0. We compute the distribution P_B(A,n) of the area A = \sum_{m=1}^n x_B(m) under such a L\'evy bridge and show that, for large n, it has the scaling form P_B(A,n) \sim n^{-1-1/\alpha} F_\alpha(A/n^{1+1/\alpha}), with the asymptotic behavior F_\alpha(Y) \sim Y^{-2(1+\alpha)} for large Y. For \alpha=1, we obtain an explicit expression of F_1(Y) in terms of elementary functions. We also compute the average profile < \tilde x_B (m) > at time m of a L\'evy bridge with fixed area A. For large n and large m and A, one finds the scaling form = n^{1/\alpha} H_\alpha({m}/{n},{A}/{n^{1+1/\alpha}}), where at variance with Brownian bridge, H_\alpha(X,Y) is a non trivial function of the rescaled time m/n and rescaled area Y = A/n^{1+1/\alpha}. Our analytical results are verified by numerical simulations.Comment: 21 pages, 4 Figure

Single-crossover dynamics: finite versus infinite populations

Populations evolving under the joint influence of recombination and resampling (traditionally known as genetic drift) are investigated. First, we summarise and adapt a deterministic approach, as valid for infinite populations, which assumes continuous time and single crossover events. The corresponding nonlinear system of differential equations permits a closed solution, both in terms of the type frequencies and via linkage disequilibria of all orders. To include stochastic effects, we then consider the corresponding finite-population model, the Moran model with single crossovers, and examine it both analytically and by means of simulations. Particular emphasis is on the connection with the deterministic solution. If there is only recombination and every pair of recombined offspring replaces their pair of parents (i.e., there is no resampling), then the {\em expected} type frequencies in the finite population, of arbitrary size, equal the type frequencies in the infinite population. If resampling is included, the stochastic process converges, in the infinite-population limit, to the deterministic dynamics, which turns out to be a good approximation already for populations of moderate size.Comment: 21 pages, 4 figure

Observation of interatomic Coulombic decay induced by double excitation of helium in nanodroplets

Interatomic Coulombic decay (ICD) plays a crucial role in weakly bound complexes exposed to intense or high-energy radiation. So far, neutral or ionic atoms or molecules have been prepared in singly excited electron or hole states which can transfer energy to neighboring centers and cause ionization and radiation damage. Here we demonstrate that a doubly excited atom, despite its extremely short lifetime, can decay by ICD; evidenced by high-resolution photoelectron spectra of He nanodroplets excited to the 2s2p+ state. We find that ICD proceeds by relaxation into excited He$^*$He$^+$ atom-pair states, in agreement with calculations. The ability of inducing ICD by resonant excitation far above the single-ionization threshold opens opportunities for controlling radiation damage to a high degree of element specificity and spectral selectivity.Comment: 6 pages, 4 figures, to be submitted to PR

Universal Order Statistics of Random Walks

We study analytically the order statistics of a time series generated by the successive positions of a symmetric random walk of n steps with step lengths of finite variance \sigma^2. We show that the statistics of the gap d_{k,n}=M_{k,n} -M_{k+1,n} between the k-th and the (k+1)-th maximum of the time series becomes stationary, i.e, independent of n as n\to \infty and exhibits a rich, universal behavior. The mean stationary gap (in units of \sigma) exhibits a universal algebraic decay for large k, /\sigma\sim 1/\sqrt{2\pi k}, independent of the details of the jump distribution. Moreover, the probability density (pdf) of the stationary gap exhibits scaling, Proba.(d_{k,\infty}=\delta)\simeq (\sqrt{k}/\sigma) P(\delta \sqrt{k}/\sigma), in the scaling regime when \delta\sim \simeq \sigma/\sqrt{2\pi k}. The scaling function P(x) is universal and has an unexpected power law tail, P(x) \sim x^{-4} for large x. For \delta \gg the scaling breaks down and the pdf gets cut-off in a nonuniversal way. Consequently, the moments of the gap exhibit an unusual multi-scaling behavior.Comment: 5 pages, 3 figures. Revised version, typos corrected. Accepted for publication in Physical Review Letter

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors