Accelerating scientific computations with mixed precision algorithms

On modern architectures, the performance of 32-bit operations is often at least twice as fast as the performance of 64-bit operations. By using a combination of 32-bit and 64-bit floating point arithmetic, the performance of many dense and sparse linear algebra algorithms can be significantly enhanced while maintaining the 64-bit accuracy of the resulting solution. The approach presented here can apply not only to conventional processors but also to other technologies such as Field Programmable Gate Arrays (FPGA), Graphical Processing Units (GPU), and the STI Cell BE processor. Results on modern processor architectures and the STI Cell BE are presented.

Program summary

Program title: ITER-REFCatalogue identifier: AECO_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECO_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 7211No. of bytes in distributed program, including test data, etc.: 41 862Distribution format: tar.gzProgramming language: FORTRAN 77Computer: desktop, serverOperating system: Unix/LinuxRAM: 512 MbytesClassification: 4.8External routines: BLAS (optional)Nature of problem: On modern architectures, the performance of 32-bit operations is often at least twice as fast as the performance of 64-bit operations. By using a combination of 32-bit and 64-bit floating point arithmetic, the performance of many dense and sparse linear algebra algorithms can be significantly enhanced while maintaining the 64-bit accuracy of the resulting solution.Solution method: Mixed precision algorithms stem from the observation that, in many cases, a single precision solution of a problem can be refined to the point where double precision accuracy is achieved. A common approach to the solution of linear systems, either dense or sparse, is to perform the LU factorization of the coefficient matrix using Gaussian elimination. First, the coefficient matrix A is factored into the product of a lower triangular matrix L and an upper triangular matrix U. Partial row pivoting is in general used to improve numerical stability resulting in a factorization PA=LU, where P is a permutation matrix. The solution for the system is achieved by first solving Ly=Pb (forward substitution) and then solving Ux=y (backward substitution). Due to round-off errors, the computed solution, x, carries a numerical error magnified by the condition number of the coefficient matrix A. In order to improve the computed solution, an iterative process can be applied, which produces a correction to the computed solution at each iteration, which then yields the method that is commonly known as the iterative refinement algorithm. Provided that the system is not too ill-conditioned, the algorithm produces a solution correct to the working precision.Running time: seconds/minutes     

Processor Efficient Parallel Matching

In this paper we consider the problem of finding perfect matchings in parallel. We present a RNC algorithm with almost optimal work with respect to sequential algorithms, i.e., it uses O(n ^ω ) processors, where ω is the matrix multiplication exponent. Our algorithm is based on an RNC algorithm for computing determinant of a degree one polynomial matrix which is of independent interest. Research supported by KBN grant 1P03A01830.     

Lock-in amplifier error prediction and correction in frequency sweep measurements

This article proposes an analytical algorithm for predicting errors in lock-in amplifiers (LIAs) working with time-varying reference frequency. Furthermore, a simple method for correcting such errors is presented. The reference frequency can be swept in order to measure the frequency response of a system within a given spectrum. The continuous variation of the reference frequency produces a measurement error that depends on three factors: the sweep speed, the LIA low-pass filters, and the frequency response of the measured system. The proposed error prediction algorithm is based on the final value theorem of the Laplace transform. The correction method uses a double-sweep measurement. A mathematical analysis is presented and validated with computational simulations and experimental measurements.     

Model-based tracking by classification in a tiny discrete pose space

A method is presented for tracking 3D objects as they transform rigidly in space within a sparse range image sequence. The method operates in discrete space and exploits the coherence across image frames that results from the relationship between known bounds on the object's velocity and the sensor frame rate. These motion bounds allow the interframe transformation space to be reduced to a reasonable and indeed tiny size, comprising only tens or hundreds of possible states. The tracking problem is in this way cast into a classification framework, effectively trading off localization precision for runtime efficiency and robustness. The method has been implemented and tested extensively on a variety of freeform objects within a sparse range data stream comprising only a few hundred points per image. It has been shown to compare favorably against continuous domain iterative closest point (ICP) tracking methods, performing both more efficiently and more robustly. A hybrid method has also been implemented that executes a small number of ICP iterations following the initial discrete classification phase. This hybrid method is both more efficient than the ICP alone and more robust than either the discrete classification method or the ICP separately     

Zur semantischen Interoperabilität in der Energiebranche: CIM IEC 61970

This contribution provides an introduction to the Common Information Model CIM which is an international standard maintained by the International Electrotechnical Commission IEC. Today’s market requirements towards the model are discussed, furthermore, we give an introduction to the history of the CIM, its serializations and scope of application. The contribution concludes with an overview of future use of the CIM for both science and commerce. Briefly, we focus on:

Message-based loose coupling of information systems

Exchange of power grid topologies with minimal communication and data overhead

Data quality assurance using ontology-based meta annotations and

Integration of heterogeneous standards in the utility domain. The contribution presents solutions to the use cases providing a better information management for the utility utilizing the Common Information Model.

     

Security Policy Conflicts in Service-oriented Systems

This paper considers methods for knowledge exploitation in security policies for Service-Oriented Architecture (SOA) environments, discovering the modality conflicts in particular. Two algorithms for discovering SOA-specific modality conflicts are proposed. First, a trivial (ad-hoc) approach is presented and further extended by the improved algorithm which offers lower time complexity. The formal verification of the proposal is followed by experimental results confirming the expected supremacy of the improved algorithm.     

Geoadditive expectile regression

Quantile regression has emerged as one of the standard tools for regression analysis that enables a proper assessment of the complete conditional distribution of responses even in the presence of heteroscedastic errors. Quantile regression estimates are obtained by minimising an asymmetrically weighted sum of absolute deviations from the regression line, a decision theoretic formulation of the estimation problem that avoids a full specification of the error term distribution. Recent advances in mean regression have concentrated on making the regression structure more flexible by including nonlinear effects of continuous covariates, random effects or spatial effects. These extensions often rely on penalised least squares or penalised likelihood estimation with quadratic penalties and may therefore be difficult to combine with the linear programming approaches often considered in quantile regression. As a consequence, geoadditive expectile regression based on minimising an asymmetrically weighted sum of squared residuals is introduced. Different estimation procedures are presented including least asymmetrically weighted squares, boosting and restricted expectile regression. The properties of these procedures are investigated in a simulation study and an analysis on rental fees in Munich is provided where the geoadditive specification allows for an analysis of nonlinear effects of the size of flats or the year of construction and the spatial distribution of rents simultaneously.     

Capability and limitation of max- and sum-type construction of Lyapunov functions for networks of iISS systems

This paper addresses the problem of verifying stability of networks whose subsystems admit dissipation inequalities of integral input-to-state stability (iISS). We focus on two ways of constructing a Lyapunov function satisfying a dissipation inequality of a given network. Their difference from one another is elucidated from the viewpoint of formulation, relation, fundamental limitation and capability. One is referred to as the max-type construction resulting in a Lipschitz continuous Lyapunov function. The other is the sum-type construction resulting in a continuously differentiable Lyapunov function. This paper presents geometrical conditions under which the Lyapunov construction is possible for a network comprising $n\ge 2$ subsystems. Although the sum-type construction for general $n>2$ has not yet been reduced to a readily computable condition, we obtain a simple condition of iISS small gain in the case of $n=2$. It is demonstrated that the max-type construction fails to offer a Lyapunov function if the network contains subsystems which are not input-to-state stable (ISS).     

An automated Thixo‐Forging Plant for Steel Parts

The scope of the article is to describe the automated production of a thixoformed steel part. The production plant was set up within a prototype initiative at the Institute of Metal Forming in cooperation with the Institute of Automatic Control of RWTH Aachen University and industrial partners. Preliminary experiments showed that the quality of the formed parts varied to a great extent due to changing production conditions since the handling of the billet was carried out manually. To eliminate the possible disturbances introduced by the manual handling of the billet, an automation concept has been elaborated in order to guarantee a defined production environment. An industrial robot (KUKA) fulfils the handling tasks like the feeding of the induction coil with the feedstock material and the placing of the heated billet into the hydraulic press. The removal of the formed part from the press is realised by a simple mechanical device in order to be able to use only one gripper. The design of the gripper ensures a minimal heat loss during handling. The induction coil, the gripper system and the cavity are flooded with inert gas in order to prevent scaling. The sequence control for the production of a part is realised on the controller of the robot which provides sufficient PLC functionality and can be easily equipped with the required I/O components to trigger the different automation components.     

Autoimmune Neutropenia and Immune-Dysregulation in a Patient Carrying a TINF2 Variant

In recent years, the knowledge about the immune-mediated impairment of bone marrow precursors in immune-dysregulation and autoimmune disorders has increased. In addition, immune-dysregulation, secondary to marrow failure, has been reported as being, in some cases, the most evident and early sign of the disease and making the diagnosis of both groups of disorders challenging. Dyskeratosis congenita is a disorder characterized by premature telomere erosion, typically showing marrow failure, nail dystrophy and leukoplakia, although incomplete genetic penetrance and phenotypes with immune-dysregulation features have been described. We report on a previously healthy 17-year-old girl, with a cousin successfully treated for acute lymphoblastic leukemia, who presented with leukopenia and neutropenia. The diagnostic work-up showed positive anti-neutrophil antibodies, leading to the diagnosis of autoimmune neutropenia, a slightly low NK count and high TCR-αβ+-double-negative T-cells. A next-generation sequencing (NGS) analysis showed the 734C>A variant on exon 6 of the TINF2 gene, leading to the p.Ser245Tyr. The telomere length was short on the lymphocytes and granulocytes, suggesting the diagnosis of an atypical telomeropathy showing with immune-dysregulation. This case underlines the importance of an accurate diagnostic work-up of patients with immune-dysregulation, who should undergo NGS or whole exome sequencing to identify specific disorders that deserve targeted follow-up and treatment.