Narrow Results

Using matched performance data and annual salary data of Japanese professional footballers, we examine the discrepancy between productivity and wages. We find that high productivity, as measured by effort and skill, contributes to raising the probability of winning matches in the Japanese professional football league, but that players’ effort and skills are not well reflected in their wages, with wages sometimes even having a negative influence on performance. Furthermore, we find that players’ attributes, such as experience, are larger drivers of wage levels than effort or skill level. The evidence suggests a seniority-based pay scale in a professional football league in the sense that reputation and “names” have market value. This discrepancy between productivity and wages suggests that there may exist inefficiency in payroll even in the professional labor market.

The rapid development of chemical enterprises has not only improved the material foundation of society, but also brought serious environmental and pollution problems. In order to provide decision-making basis for basic chemical enterprises to achieve green Supply Chain Management (SCM) and green innovation, the study proposes a hypothesis and conceptual model on the impact of green SCM on enterprise performance under the influence of green innovation. Measurement scales for each dimension are designed and a questionnaire survey is conducted. The reliability and validity of the sample data are examined in turn, the consistency of each dimension is determined through correlation analysis. Finally, a regression model is used to examine the correlation of the three variables. The results indicated that the cumulative total deviation variance explained by the dimensions of green supply chain innovation, business performance and green innovation in basic chemical enterprises were 80.101%, 77.425% and 74.526%, respectively. Green procurement had a significant negative impact on the performance of basic chemical enterprises. Green recycling and internal environmental management had a negative influence on enterprise performance. The research results contribute to promoting the sustainable development of chemical enterprises, providing new perspectives and methods for the practice of knowledge management, and offering guidance for chemical enterprises on how to better manage and apply knowledge, which is beneficial for the research and practice of knowledge management.

A steady flow combined heat pump cycle model with heat resistance, heat leakage and internal irreversibility is built in this paper. The optimal performance of the model is studied. The relation between optimal heating load and coefficient of performance (COP), as well as the maximum COP and the corresponding heating load are derived.

The Fast Fourier Transform is a mainstay of certain numerical techniques for solving fluid dynamics problems. The Connection Machine CM-2 is the target for an investigation into the design of multidimensional SIMD parallel FFT algorithms for high performance. Critical algorithm design issues are discussed, necessary machine performance measurements are identified and made, and the performance of the developed FFT programs are measured. Our FFT programs are compared to the currently best Cray-2 FFT library program, CFFT2.

We have implemented pure gauge Quantum Chromo-dynamics (QCD) on the massively-parallel Connection Machine, in *Lisp. We describe our program in some detail, and give performance measurements for it. With no tuning or optimization, the code runs at approximately 500 to 1000 Mflops on a 64K CM-2, depending on the VP ratio.

The Connection Machine CM-2 computer represents the state of the art in supercomputer performance at this time, with peak rates of over 20 Gflops in 32-bit precision. While theoretical peak rates are essentially never attained, remarkable performance is possible on real applications. We discuss a number of CM-2 applications including implicit and explicit PDE solvers as well as spectral methods. We demonstrate delivered performance over a gigaflop in each case, and ranging as high as 3.8 gigaflops in the case of conjugate gradient solution of elliptic PDE.

We describe 2D and 3D Fast Helmholtz and Poisson Direct Solvers for the CM-2 and provide performance data for them on grids with up to 4 million points and using 65,536 processors. Performance of 1.1 Gflops is attained in 2D, and over 850 Mflops in 3D. The solution of the Helmholtz equation on a 2048×2048 grid takes under half a second, and on a 128×128×256 3D grid it requires .54 seconds. We have iteratively solved more general elliptic PDE by conjugate gradient methods at 3.8 Gflops. The fast solver has been used to provide a pre-conditioner for the conjugate gradient solver, which is then limited in performance to 1.3 Gflops, but results in far fewer iterations.

We also describe several partial and complete applications ranging from oil reservoir simulation to oceanographic modeling. In the latter case we present the first results of spectral models running on the CM-2. We emphasize the issues involved in attaining these levels of performance and compare in most cases with CRAY-XMP performance for the same algorithm. All results are for algorithms written in a high-level language.

Beginning in 1988, the Numerical Aerodynamic Simulation (NAS) organization at NASA Ames Research Center has studied the usability of highly parallel computers on computational fluid dynamics and other aerophysics applications. Presently this organization operates a CM-2 with 32,768 nodes and an Intel iPSC/860 with 128 nodes. This note gives an overview of the experience in using these systems, highlights both strong points and weak points of each, and discusses what improvements will be required in future highly parallel systems in order that they can gain acceptance in the mainstream of scientific computing.

The aim of this work is to provide a model for the dynamic implementation of finite automata for enhanced performance. Investigations have shown that hardcoded finite automata outperforms the traditional table-driven implementation up to some threshold. Moreover, the kind of string being recognized plays a major role in the overall processing speed of the string recognizer. Various experiments are depicted to show when the advantages of using hardcoding as basis for implementing finite automata (instead of using the classical table-driven approach) become manifest. The model, a dynamic algorithm that combines both hardcoding and table-driven is introduced.

The spatial and temporal locality of reference on which cache memory relies to minimize cache swaps, is exploited to design a new algorithm for finite automaton string recognition. It is shown that the algorithm, referred to as the Dynamic State Allocation algorithm outperforms the traditional table-driven algorithm for strings that tend to repeatedly access the same set of states, provided that the string is long enough to amortize the allocation cost. Further improvements on the algorithm result in even better performance.

Table-driven (TD) DFA-based string processing algorithms are examined from a number of vantage points. Firstly, various strategies for implementing such algorithms in a cache-efficient manner are identified. The denotational semantics of such algorithms is encapsulated in a function whose various arguments are associated with each implementation strategy. This formal view of the implementation strategies suggests twelve different algorithms, each blending together the implementation strategies in a particular way. The performance of these algorithms is examined in against a set of artificially generated data. Results indicate a number of cases where the new algorithms outperform the traditional TD algorithm.

The Parallel Random Access Machine is a very strong model of parallel computing that has resisted cost-efficient implementation attempts for decades. Recently, the development of VLSI technology has provided means for indirect on-chip implementation, but there are different variants of the PRAM model that provide different performance, area and power figures and it is not known how their implementations compare to each others. In this paper we measure the performance and estimate the cost of practical implementations of four PRAM models including EREW, Limited Arbitrary CRCW, Full Arbitrary CRCW, Full Arbitrary Multioperation CRCW on our Eclipse chip multiprocessor framework. Interestingly, the most powerful model shows the lowest simulation cost and highest performance/area and performance/power figures.

Both the post-order heap and the M-heap have a full binary tree structure and have constant amortized insertion and O(logn) deletion time complexities.

This paper proposes a simple array version of the M-heap, called AM-heap. The AM-heap has a complete binary tree structure and its array indexing scheme is the same as the simple indexing scheme of the conventional binary heap. An insertion on an AM-heap takes constant amortized time and a deletion takes O(logn) time where n is the number of elements in an AM-heap. The AM-heap resolves the open problem that is to design an array version of the M-heap. Also, it is simpler than the post-order heap to implement and debug.

We show that the leftist tree data structure may be adapted to obtain data structures that permit the double-ended priority queue operations Insert, DeleteMin, DeleteMax, and Merge to be done in O(log n) time where n is the size of the resulting queue. The operations FindMin and FindMax can be done in O(1) time. Experimental results are also presented.

A microbeam system was installed at Dynamitron laboratory at Tohoku University and is applicable to simultaneous in-air/in-vacuum PIXE, RBS, SE, and STIM analyses, and 3D µ-CT. Insufficient beam brightness of the source and field contamination of the microbeam line restricted spatial resolution. In order to improve the performance of Tohoku microbeam system, optimization and modification of the ion source and microbeam system were performed. By the modification of the system, the beam brightness of the system was increased to 1.0 pA·µm^-2·mrad^-2·MeV^-1 at the half divergence of 0.2 mrad. Considering the brightness and the magnification, obtainable target current will be 200 and 900 pA for beam spot sizes of 1.0 × 1.0 and 2.0 × 2.0 µm², respectively. The modification of the source meets both the lifetime and the performance. The parasitic field contamination of the system was reduced down to less than 0.5 % by replacing the beam scanner chamber and a part of beam duct. Both resolution and beam currents are sufficient for our applications of in-air/in-vacuum PIXE, RBS, SE, and STIM analyses and 3D PIXE-µ-CT.

Since the first demonstration of the quantum well infrared photodetector (QWIP) in the 1980s, there has been much progress in the application of QWIPs to the production infrared (IR) imaging systems. At this time, focal plane arrays (FPAs) made from QWIPs are readily available for insertion in IR cameras with formats as large as 640 × 480 pixels. Several organizations now have commercially available IR camera systems using QWIPs. In spite of the low single-pixel quantum efficiency relative to MCT, excellent IR imagery has been demonstrated with large format (640 × 480 pixels) single-band and moderate format (256 × 256 pixels) dual-band FPAs. With a large-format staring FPA, one can integrate the signal current for a relatively long time to produce images of similar quality to that from a scanned line array run at the same frame rate. In fact, it can be shown that due to the nature of the noise in a QWIP device, the noise performance of a QWIP FPA can be better than that of MCT FPA as long as the conversion efficiency (the product of the quantum efficiency and the photoconductive gain) is high enough for the read-out integrated circuit (ROIC) integration capacitor to be filled in a frame time. In this chapter the results of laboratory and field tests on large-format single-color QWIP FPAs operating in the LWIR band and dual-band FPAs operating in both the MWIR and LWIR bands simultaneously will be shown. Single-color and dual-band arrays will be shown to give excellent imaging performance and that dual-band FPAs offer unique capabilities to investigate the phenomenology of targets and backgrounds. The performance of the FPAs will be presented from a system performance perspective over a wide range of operating conditions (temperature, bias, integration time, etc.). Results of measurements of noise-equivalent temperature difference (NEΔT), minimum resolvable temperature difference (MRTD measured as a function of target spatial frequency), responsivity, and dark current will be reported. Imagery collected in the field will show the utility of large-format LWIR FPAs for increasing the range at which targets can be identified over previous-generation scanning imagers. Dual-band imagery collected using a QWIP FPA will show how such an array as part of a future imaging system may be able to exploit differences in the IR signatures of targets and backgrounds in the MWIR and LWIR bands to enhance the visibility of targets in cluttered environments. We also show how such an array can be used to make accurate remote temperature measurements. Finally, we will compare the performance of state-of-the-art FPAs made from QWIPs and MCT.

A full Newton lattice Boltzmann method is developed for time-steady flows. The general method involves the construction of a residual form for the time-steady, nonlinear Boltzmann equation in terms of the probability distribution. Bounce-back boundary conditions are also incorporated into the residual form. Newton's method is employed to solve the resulting system of non-linear equations. At each Newton iteration, the sparse, banded, Jacobian matrix is formed from the dependencies of the non-linear residuals on the components of the particle distribution. The resulting linear system of equations is solved using a direct solver designed for sparse, banded matrices. For the Stokes flow limit, only one matrix solve is required. Two dimensional flow about a periodic array of disks is simulated as a proof of principle, and the numerical efficiency is carefully assessed. For the case of Stokes flow (Re = 0) with resolution 251×251, the proposed method performs more than 100 times faster than a standard, fully explicit implementation.

This paper provides a mathematical description based on the theory of differential equations, for the dynamics of lactate production and removal. Analytical and numerical results for training/exercise of endurance of athletes are presented based on the common concept of training impulse (Trimp). The relationships between activity, production rate, and removal strategies of lactate are studied. Parameters are estimated from published data. A model for optimum removal of lactate after exercise is developed. The model provides realistic predictions when compared with experimental results. We show some specific examples for the usefulness of the mathematical model by studying some recent problems discussed in the literature. (a) Is interval exercise more beneficial than steady-state exercise? (b) What is the optimum aerobic power during recovery? We discuss whether steady-state exercise gives higher Trimp than interval exercise, when imposing an upper boundary for the lactate concentration as a constraint. The model allows for testing all imaginable kinds of steady-state and interval exercises in search of the optimal exercise regime for individuals with various kinds of characteristics. In general, the dynamic model constitute a powerful tool describing the processes by which the concentration of lactate can be studied and controlled to decrease fatigue and increase endurance.

The gradual evolution of language features and approaches used for the programming of distributed memory machines underwent substantial advances in the 1990s. One of the most promising and widely praised approaches was based on data parallelism and resulted in High Performance Fortran. This paper reports on an experiment using that approach based on a commercial distributed memory machine, available compilers and simple test programs. The results are disappointing and not encouraging. The variety of components involved and the lack of detailed knowledge available for the compilers compound the difficulties of obtaining results and doing comparisons. The results show great variation and question the premise that communication is the decisive factor in performance determination. The results are also a contribution towards the difficult tasks of predicating performance on a distributed memory computer.

When designing and implementing highly efficient scientific applications for parallel computers such as clusters of workstations, it is inevitable to consider and to optimize the single-CPU performance of the codes. For this purpose, it is particularly important that the codes respect the hierarchical memory designs that computer architects employ in order to hide the effects of the growing gap between CPU performance and main memory speed. In this article, we present techniques to enhance the single-CPU efficiency of lattice Boltzmann methods which are commonly used in computational fluid dynamics. We show various performance results for both 2D and 3D codes in order to emphasize the effectiveness of our optimization techniques.

Collective communication performance is critical in a number of MPI applications. In this paper we focus on two widely used primitives, broadcast and reduce, and present experimental results obtained on a cluster of PC connected by InfiniBand. We integrated our algorithms in the MPICH library and we used MPICH implementation of broadcast and reduce primitives to compare the performance of our algorithms based on α-trees. Our tests show that the MPICH implementation can be improved.