Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control

The rapid increase in the performance of graphics hardware, coupled with recent improvements in its programmability has lead to its adoption in many non-graphics applications, including wide variety of scientific computing fields. At the same time, a number of important dynamic optimal policy problems in economics are athirst of computing power to help overcome dual curses of complexity and dimensionality. We investigate if computational economics may benefit from new tools on a case study of imperfect information dynamic programming problem with learning and experimentation trade-off that is, a choice between controlling the policy target and learning system parameters. Specifically, we use a model of active learning and control of linear autoregression with unknown slope that appeared in a variety of macroeconomic policy and other contexts. The endogeneity of posterior beliefs makes the problem difficult in that the value function need not be convex and policy function need not be continuous. This complication makes the problem a suitable target for massively-parallel computation using graphics processors. Our findings are cautiously optimistic in that new tools let us easily achieve a factor of 15 performance gain relative to an implementation targeting single-core processors and thus establish a better reference point on the computational speed vs. coding complexity trade-off frontier. While further gains and wider applicability may lie behind steep learning barrier, we argue that the future of many computations belong to parallel algorithms anyway.Graphics Processing Units, CUDA programming, Dynamic programming, Learning, Experimentation

Bayesian fan charts for U.K. inflation: forecasting and sources of uncertainty in an evolving monetary system

We estimate a Bayesian vector autoregression for the U.K. with drifting coefficients and stochastic volatilities. We use it to characterize posterior densities for several objects that are useful for designing and evaluating monetary policy, including local approximations to the mean, persistence, and volatility of inflation. We present diverse sources of uncertainty that impinge on the posterior predictive density for inflation, including model uncertainty, policy drift, structural shifts and other shocks. We use a recently developed minimum entropy method to bring outside information to bear on inflation forecasts. We compare our predictive densities with the Bank of England's fan charts

Econometric Evaluation of Rational Belief Models

The paper proposes a method for construction, estimation, and testing the Rational Beliefs (RB) models. RB models, due to Kurz, 1994, allow agents' beliefs to differ from the Rational Expectations (RE), but require that beliefs cannot be contradicted by past data. By implication, RB and RE must agree in strictly stationary worlds, while a disagreement is allowed in non-stationary setting. The estimation method involves sample counterparts to the conditional and unconditional moment restrictions formed from the Euler equations and rationality conditions. In essence, the method deduces systems of conditional beliefs consistent with the conditional moment restriction posed by the Euler equations. Consistent test statistics then discriminates the rationality from non-rationality. The attractive features are (i) the estimation and testing procedures are implemented without solving explicitly for RB equilibria, (ii) learning is permitted, and (iii) both the econometrician and the economic agents are put on the ``equal footing'' in the sense of Muth, 1961 and ``down to earth''. Under flexible regularity conditions, the test statistics are shown to converge in distribution to the continuous functionals of generalized Brownian bridges, whose coordinates are projections on the space of moment functions that are used to phrase the rationality conditions. As a result, the limit distributions are non-standard or standard, depending on whether the test statistic is itself a function of finite-dimensional projection or a functional of the whole process, respectively. The resampling and simulation methods allow for valid approximation of either distribution. A simple estimated model of aggregate consumption and stock market behavior, populated by investors with rational beliefs, points to the variation in agents' sentiments as a dominant source of asset price volatility.

Практики взаимодействия государственных и негосударственных акторов в контексте регулирования системы массовой коммуникации в Pоссийской Федерации

Introduction: The article represents the author's interpretation of the actor composition of implementing information policy in modern Russia. Special attention is paid to the analysis of the main conditions of interaction between state and non-state structures of the Russian Federation in the process of determining priorities and strategies for ensuring information security in Russia. The problem of this research is actualized by increasing dependence of the mass communication domestic system on modern global geopolitical threats and foreign policy challenges. Russia and Russian society need a set of effective tools and methods to ensure the security and stability of the mass communication system. Methodology and methods: The main methodology of this study is the principles of the communicative approach (N. Wiener, C. Deutsch). Besides, the ideas about the technological core of political communication find their scientific and practical application (S.V. Volodenkov, M. Castells, S.V. Schwarzenberg). The analysis of the combination of public political communication and the processes of administrative-state management is based on the conclusions, which are contained in the articles of G. Lassuela and O.F. Shabrov. The empirical basis of the research is the public opinion polls of "Levada Center". Analysis: The modern world is increasingly differentiated by the degree of information richness: the more the country is informationally open, the faster the production of new ideas, their inclusion in political decisions. The modern process of political communication has shifted to greater interactivity. Information policy, political regulation of the mass communication system becomes the leading sphere of management activities of state and non-state structures. Discussion: The indicative model development of politicalcommunicative interaction of information policy actors in the Russian Federation is hampered by a number of problems. Some of them are associated with established practices of political administration by state institutions of information processes. Other problems come from the unwillingness of civil structures to carry out the functions of public political management in the field of information security. The result is a decline in public confidence in political information and the Russian media. Results: The author proposes the main forms of coordinated interaction of state and non-state actors in the field of information regulation, ensuring the information security of the Russian Federation. The researcher substantiates the idea of the relationship of the mass communication system development with the formation of information and communication competencies of the Russian Federation population

Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control

The rapid increase in the performance of graphics hardware, coupled with recent improvements in its programmability has lead to its adoption in many non-graphics applications, including wide variety of scientific computing fields. At the same time, a number of important dynamic optimal policy problems in economics are athirst of computing power to help overcome dual curses of complexity and dimensionality. We investigate if computational economics may benefit from new tools on a case study of imperfect information dynamic programming problem with learning and experimentation trade-off that is, a choice between controlling the policy target and learning system parameters. Specifically, we use a model of active learning and control of linear autoregression with unknown slope that appeared in a variety of macroeconomic policy and other contexts. The endogeneity of posterior beliefs makes the problem difficult in that the value function need not be convex and policy function need not be continuous. This complication makes the problem a suitable target for massively-parallel computation using graphics processors. Our findings are cautiously optimistic in that new tools let us easily achieve a factor of 15 performance gain relative to an implementation targeting single-core processors and thus establish a better reference point on the computational speed vs. coding complexity trade-off frontier. While further gains and wider applicability may lie behind steep learning barrier, we argue that the future of many computations belong to parallel algorithms anyway

Mathematical model of the mechanical properties of Ti-alloyed hypoeutectic cast iron for mixer blades

The object of research is hypoeutectic cast iron intended for cast parts operating under abrasive friction conditions. Such parts are mixer blades, the operational properties of which include durability, assessed by abrasion resistance and strength. To give the blades such properties, cast irons, which are materials of the blades, are alloyed with elements that contribute to the formation of carbides of various compositions. The main problem that impedes the targeted selection of materials for mixer blades or finished blades from different materials or different chemical composition is the lack of substantiated selection criteria. If the shipment is carried out only with the provision of data on the chemical composition of the alloy, it is necessary to be able to evaluate the expected mechanical properties, in particular abrasion resistance and strength. Using the methods of regression analysis, a mathematical model has been obtained that includes two regression equations, which allows for a targeted selection of the chemical composition that provides the maximum possible value of mechanical properties – ultimate strength and coefficient of wear resistance. Optimization of the chemical composition, carried out according to this model, made it possible to determine the following chemical composition: C=2.94 %, Ceq=3.3 %, Ti=1.56 %, providing the maximum ultimate strength σb=391 MPa; C=2.78 %, Ceq=3.14 %, Ti=1.61 %, providing a maximum wear resistance coefficient Kwr=12 %. In the case of priority of the strength criterion, the calculated optimal chemical composition makes it possible to reduce the mass-dimensional characteristics of the mixing units of the mixers. A procedure is proposed for using this model to select a batch of blades with the expected best performance propertie

Translation arrest of potato virus X RNA in Krebs-2 cell-free system: RNase H cleavage promoted by complementary oligodeoxynucleotides

AbstractTranslation arrest of genomic potato virus X (PVX) RNA promoted by complementary oligodeoxynucleotides in Krebs-2 cell-free system is described. 14–15 mer oligodeoxynucleotides complementary to the 5′-proximal cistron of PVX RNA were shown to induce specific truncation of the major non-structural polypeptide coded by PVX RNA. Evidence is presented that effective translational arrest of PVX RNA in the presence of complementary oligonucleotides restults from the site-specific cleavage of RNA by endogenous RNase H intrinsic to the Krebs-2 extract. No similar translational arrest was found in the rabbit reticulocyte lysate cell-free system