The scheduling of sparse matrix-vector multiplication on a massively parallel dap computer

An efficient data structure is presented which supports general unstructured sparse matrix-vector multiplications on a Distributed Array of Processors (DAP). This approach seeks to reduce the inter-processor data movements and organises the operations in batches of massively parallel steps by a heuristic scheduling procedure performed on the host computer. The resulting data structure is of particular relevance to iterative schemes for solving linear systems. Performance results for matrices taken from well known Linear Programming (LP) test problems are presented and analysed

Adapting the interior point method for the solution of LPs on serial, coarse grain parallel and massively parallel computers

In this paper we describe a unified scheme for implementing an interior point algorithm (IPM) over a range of computer architectures. In the inner iteration of the IPM a search direction is computed using Newton's method. Computationally this involves solving a sparse symmetric positive definite (SSPD) system of equations. The choice of direct and indirect methods for the solution of this system, and the design of data structures to take advantage of serial, coarse grain parallel and massively parallel computer architectures, are considered in detail. We put forward arguments as to why integration of the system within a sparse simplex solver is important and outline how the system is designed to achieve this integration

Does money matter in inflation forecasting?.

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation

The stellar content of the infalling molecular clump G286.21+0.17

The early evolution during massive star cluster formation is still uncertain. Observing embedded clusters at their earliest stages of formation can provide insight into the spatial and temporal distribution of the stars and thus probe different star cluster formation models. We present near-infrared imaging of an 8'*13'(5.4pc*8.7pc) region around the massive infalling clump G286.21+0.17(also known as BYF73). The stellar content across the field is determined and photometry is derived in order to { obtain} stellar parameters for the cluster members. We find evidence for some sub-structure (on scales less than a pc diameter) within the region with apparently at least three different sub-clusters associated with the molecular clump based on differences in extinction and disk fractions. At the center of the clump we identify a deeply embedded sub-cluster. Near-infrared excess is detected for 39-44% in the two sub-clusters associated with molecular material and 27% for the exposed cluster. Using the disk excess as a proxy for age this suggests the clusters are very young. The current total stellar mass is estimated to be at least 200 Msun. The molecular core hosts a rich population of pre-main sequence stars. There is evidence for multiple events of star formation both in terms of the spatial distribution within the star forming region and possibly from the disk frequency.Comment: Submitted to A

W Plus Multiple Jets at the LHC with High Energy Jets

We study the production of a W boson in association with n hard QCD jets (for n>=2), with a particular emphasis on results relevant for the Large Hadron Collider (7 TeV and 8 TeV). We present predictions for this process from High Energy Jets, a framework for all-order resummation of the dominant contributions from wide-angle QCD emissions. We first compare predictions against recent ATLAS data and then shift focus to observables and regions of phase space where effects beyond NLO are expected to be large.Comment: 19 pages, 9 figure

Thermodynamics of O(N) sigma models: 1/N corrections

The thermodynamics of the O(N) linear and nonlinear sigma models in 3+1 dimensions is studied. We calculate the pressure to next-to-leading order in the 1/N expansion and show that at this order, temperature-independent renormalization is only possible at the minimum of the effective potential. The 1/N expansion is found to be a good expansion for N as low as 4, which is the case relevant for low-energy QCD phenomenology. We consider the cases with and without explicit symmetry breaking. We show that previous next-to-leading order calculations of the pressure are either breaking down in the temperatures of interest, or based on unjustifiable high-energy approximations.Comment: 11 pages, 5 figures, revte

The mass content of the Sculptor dwarf spheroidal galaxy

We present a new determination of the mass content of the Sculptor dwarf spheroidal galaxy, based on a novel approach which takes into account the two distinct stellar populations present in this galaxy. This method helps to partially break the well-known mass-anisotropy degeneracy present in the modelling of pressure-supported stellar systems.Comment: 6 pages, 3 figures. To appear in the proceedings of IAU Symposium 254 "The Galaxy disk in a cosmological context", Copenhagen, June 200

Enumeration of chord diagrams on many intervals and their non-orientable analogs

Two types of connected chord diagrams with chord endpoints lying in a collection of ordered and oriented real segments are considered here: the real segments may contain additional bivalent vertices in one model but not in the other. In the former case, we record in a generating function the number of fatgraph boundary cycles containing a fixed number of bivalent vertices while in the latter, we instead record the number of boundary cycles of each fixed length. Second order, non-linear, algebraic partial differential equations are derived which are satisfied by these generating functions in each case giving efficient enumerative schemes. Moreover, these generating functions provide multi-parameter families of solutions to the KP hierarchy. For each model, there is furthermore a non-orientable analog, and each such model likewise has its own associated differential equation. The enumerative problems we solve are interpreted in terms of certain polygon gluings. As specific applications, we discuss models of several interacting RNA molecules. We also study a matrix integral which computes numbers of chord diagrams in both orientable and non-orientable cases in the model with bivalent vertices, and the large-N limit is computed using techniques of free probability.Comment: 23 pages, 7 figures; revised and extended versio

Interplay between nanometer-scale strain variations and externally applied strain in graphene

We present a molecular modeling study analyzing nanometer-scale strain variations in graphene as a function of externally applied tensile strain. We consider two different mechanisms that could underlie nanometer-scale strain variations: static perturbations from lattice imperfections of an underlying substrate and thermal fluctuations. For both cases we observe a decrease in the out-of-plane atomic displacements with increasing strain, which is accompanied by an increase in the in-plane displacements. Reflecting the non-linear elastic properties of graphene, both trends together yield a non-monotonic variation of the total displacements with increasing tensile strain. This variation allows to test the role of nanometer-scale strain variations in limiting the carrier mobility of high-quality graphene samples