QCDGPU: open-source package for Monte Carlo lattice simulations on OpenCL-compatible multi-GPU systems

The multi-GPU open-source package QCDGPU for lattice Monte Carlo simulations of pure SU(N) gluodynamics in external magnetic field at finite temperature and O(N) model is developed. The code is implemented in OpenCL, tested on AMD and NVIDIA GPUs, AMD and Intel CPUs and may run on other OpenCL-compatible devices. The package contains minimal external library dependencies and is OS platform-independent. It is optimized for heterogeneous computing due to the possibility of dividing the lattice into non-equivalent parts to hide the difference in performances of the devices used. QCDGPU has client-server part for distributed simulations. The package is designed to produce lattice gauge configurations as well as to analyze previously generated ones. QCDGPU may be executed in fault-tolerant mode. Monte Carlo procedure core is based on PRNGCL library for pseudo-random numbers generation on OpenCL-compatible devices, which contains several most popular pseudo-random number generators.Comment: Presented at the Third International Conference "High Performance Computing" (HPC-UA 2013), Kyiv, Ukraine; 9 pages, 2 figure

Optimization of Local Routing for Connected Nodes with Single Output Ports - Part I: Theory

The optimization of packet flows in a set of cooperative nodes with single output ports is considered. A single output port relays a packet to a single connected node at a time. The different service time distributions to distinct connected nodes are considered in terms of multiclass queuing with a single first-come first-serve queue and a single server in each node. The analytic model is applied to cases of two, three and four connected nodes with M/M/1 queues relaying packets in a chosen direction. Analytical solutions for two connected nodes are obtained. The influence of other arbitrary packet flows is considered as background traffic. Directed links are used for local connectivity within the set of cooperative node

Fiscal equalization and regions' (un)willingness-to-tax: Evidence from Germany

Under cooperative federalism, when an identical tax tariff applies to all regions of a federation, usually redistribution rules are implemented to smooth fiscal differences. The administration of tax collection, however, is sometimes delegated to the regional level, leaving the regional administrations some discretion concerning the auditing of tax returns. Building on a stylized model, we show that under such conditions granted discretionary tax deductions at the level of tax units is positively related to state-specific marginal rates of loss (MRL), i.e., the fraction of an additional tax Euro raised in a region that the fiscal-equalization system redistributes to other jurisdictions. We empirically test the model's presumption using administrative income-tax micro data from Germany. Regression estimates comply with the implications of our model. --Fiscal federalism,rate of loss,income tax returns

Over-the-Air Integrated Sensing, Communication, and Computation in IoT Networks

To facilitate the development of Internet of Things (IoT) services, tremendous IoT devices are deployed in the wireless network to collect and pass data to the server for further processing. Aiming at improving the data sensing and delivering efficiency, the integrated sensing and communication (ISAC) technique has been proposed to design dual-functional signals for both radar sensing and data communication. To accelerate the data processing, the function computation via signal transmission is enabled by over-the-air computation (AirComp), which is based on the analog-wave addition property in a multi-access channel. As a natural combination, the emerging technology namely over-the-air integrated sensing, communication, and computation (Air-ISCC) adopts both the promising performances of ISAC and AirComp to improve the spectrum efficiency and reduce latency by enabling simultaneous sensing, communication, and computation. In this article, we provide a promptly overview of Air-ISCC by introducing the fundamentals, discussing the advanced techniques, and identifying the applications

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Achieving Fair Load Balancing by Invoking a Learning Automata-based Two Time Scale Separation Paradigm

Author's accepted manuscript.© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this article, we consider the problem of load balancing (LB), but, unlike the approaches that have been proposed earlier, we attempt to resolve the problem in a fair manner (or rather, it would probably be more appropriate to describe it as an ε-fair manner because, although the LB can, probably, never be totally fair, we achieve this by being ``as close to fair as possible''). The solution that we propose invokes a novel stochastic learning automaton (LA) scheme, so as to attain a distribution of the load to a number of nodes, where the performance level at the different nodes is approximately equal and each user experiences approximately the same Quality of the Service (QoS) irrespective of which node that he/she is connected to. Since the load is dynamically varying, static resource allocation schemes are doomed to underperform. This is further relevant in cloud environments, where we need dynamic approaches because the available resources are unpredictable (or rather, uncertain) by virtue of the shared nature of the resource pool. Furthermore, we prove here that there is a coupling involving LA's probabilities and the dynamics of the rewards themselves, which renders the environments to be nonstationary. This leads to the emergence of the so-called property of ``stochastic diminishing rewards.'' Our newly proposed novel LA algorithm ε-optimally solves the problem, and this is done by resorting to a two-time-scale-based stochastic learning paradigm. As far as we know, the results presented here are of a pioneering sort, and we are unaware of any comparable results.acceptedVersio

Love and taxes - and matching institutions

We study a setting with search frictions in the marriage market and with incomplete contracting inside the family. Everyone prefers a partner that has high income and is a perfect emotional match, but compromises must often be struck. A high income earner may abstain from marrying a low-income earner even though they would be a perfect match emotionally, because the highincome earner may dislike the implicit income redistribution implied by the marriage. Redistributive income taxation may ease this problem. Income matching institutions that secure that people largely from the same income groups meet each other can substitute for redistribution, so that optimal redistribution is reduced. We also introduce a divorce option. Redistributive taxation is shown both to further and stabilize marriage. -- Wenn Menschen mit unterschiedlichem Einkommen heiraten, führt dies zu einer Umverteilung innerhalb der Ehe von der wirtschaftlich stärkeren zur wirtschaftlich schwächeren Person. Zwei Personen, die zufällig aufeinander treffen und aufgrund ähnlicher Interessen und Neigungen gut zueinander passen, werden auch die finanziellen Folgen einer Heirat berücksichtigen. Falls die Person mit hohem Einkommen diese Umverteilung als zu stark empfindet, kommt die Ehe nicht zustande. Die Rente, die z.B. dadurch entsteht, dass das Paar ähnliche Interessen hat oder gemeinsamen Hobbys nachgehen kann, geht in diesem Fall verloren. Progressive Besteuerung führt zu einer Angleichung der Einkommensverteilung und verringert daher die Wahrscheinlichkeit, dass Ehen aufgrund hoher Einkommensunterschiede nicht zustande kommen. Aus wohlfahrtstheoretischer Sicht ist dies ein positiver Aspekt umverteilender Besteuerung, der bisher in der Literatur nicht berücksichtigt wurde. Die optimale Höhe der Besteuerung hängt von den Matching-Institutionen ab, d.h. davon wer wen auf dem Heiratsmarkt trifft. Treffen vorwiegend Personen mit unterschiedlichem Einkommen und ähnlichen Interessen aufeinander, ist der positive Effekt der Besteuerung besonders wirksam. In diesem Fall ist der optimale Steuersatz umso höher, je ähnlicher die Interessen der potentiellen Partner ist. Umgekehrt kann progressive Besteuerung in einer Gesellschaft, in der vorwiegend Personen mit ohnehin ähnlichem Einkommen aufeinandertreffen, kaum etwas bewirken. Daher fällt in diesem Fall der optimale Steuersatz umso geringer aus, je ähnlicher die Einkommen der potentiellen Paare auf dem Heiratsmarkt sind.Marriage,optimal taxation,emotional rents,love,incomplete contracts,assortative mating,divorce

Fiscal equalization and regions' (un)willingness-to-tax: Evidence from Germany

Under cooperative federalism, when an identical tax tariff applies to all regions of a federation, usually redistribution rules are implemented to smooth fiscal differences. The administration of tax collection, however, is sometimes delegated to the regional level, leaving the regional administrations some discretion concerning the auditing of tax returns. Building on a stylized model, we show that under such conditions granted discretionary tax deductions at the level of tax units is positively related to state-specific marginal rates of loss (MRL), i.e., the fraction of an additional tax Euro raised in a region that the fiscal-equalization system redistributes to other jurisdictions. We empirically test the model's presumption using administrative income-tax micro data from Germany. Regression estimates comply with the implications of our model