Lanczos eigensolution method for high-performance computers

The theory, computational analysis, and applications are presented of a Lanczos algorithm on high performance computers. The computationally intensive steps of the algorithm are identified as: the matrix factorization, the forward/backward equation solution, and the matrix vector multiples. These computational steps are optimized to exploit the vector and parallel capabilities of high performance computers. The savings in computational time from applying optimization techniques such as: variable band and sparse data storage and access, loop unrolling, use of local memory, and compiler directives are presented. Two large scale structural analysis applications are described: the buckling of a composite blade stiffened panel with a cutout, and the vibration analysis of a high speed civil transport. The sequential computational time for the panel problem executed on a CONVEX computer of 181.6 seconds was decreased to 14.1 seconds with the optimized vector algorithm. The best computational time of 23 seconds for the transport problem with 17,000 degs of freedom was on the the Cray-YMP using an average of 3.63 processors

A Lanczos eigenvalue method on a parallel computer

Eigenvalue analyses of complex structures is a computationally intensive task which can benefit significantly from new and impending parallel computers. This study reports on a parallel computer implementation of the Lanczos method for free vibration analysis. The approach used here subdivides the major Lanczos calculation tasks into subtasks and introduces parallelism down to the subtask levels such as matrix decomposition and forward/backward substitution. The method was implemented on a commercial parallel computer and results were obtained for a long flexible space structure. While parallel computing efficiency for the Lanczos method was good for a moderate number of processors for the test problem, the greatest reduction in time was realized for the decomposition of the stiffness matrix, a calculation which took 70 percent of the time in the sequential program and which took 25 percent of the time on eight processors. For a sample calculation of the twenty lowest frequencies of a 486 degree of freedom problem, the total sequential computing time was reduced by almost a factor of ten using 16 processors

State and Local Anti-Predatory Lending Laws: The Effect of Legal Enforcement Mechanisms

Subprime mortgage lending has grown rapidly in recent years and with it, so have concerns about predatory lending. In response to evidence of predatory lending, most states have enacted new laws or expanded existing laws to address abuses in the subprime home loan market. The effect of these statutes is a matter of debate. This paper seeks to improve the understanding of this increasingly important issue and pays particular attention to the role that legal enforcement mechanisms play in this context. The results of the analysis are consistent with the view that anti-predatory lending laws influence subprime lending markets and that disaggregating the details of the overall legal framework into its component parts is essential for understanding subprime market dynamics. The restrictions, coverage, and enforcement components all have significant relationships with subprime market outcomes, with the coverage relationship found to be broadly consistent with the reverse lemons hypothesis put forward by Ho and Pennington-Cross (2007). The results also suggest that the newer mini-HOEPA laws have had an impact on the subprime market above and beyond the older preexisting laws, particularly for subprime originations. Broader coverage through these new laws is associated with higher origination likelihoods, while increased restrictions through the mini-HOEPA laws are associated with lower origination propensities

The Impact of State Anti-Predatory Lending Laws: Policy Implications and Insights

The subprime mortgage market, which consists of high-cost loans designed for borrowers with weak credit, has grown tremendously over the past ten years. Between 1993 and 2005, the subprime market experienced an average annual growth rate of 26 percent. As this market emerged, so did allegations that subprime loans contained predatory features or were the result of predatory sales practices.3 In the worst cases, brokers deceived borrowers about the meaning of loan terms or falsely promised to assist them in obtaining future refinance loans with better terms. In other situations, borrowers entered into loans with low teaser rates, not aware how high their monthly payments could go when their interest rates reset

Homeownership and Nontraditional and Subprime Mortgages

This article documents the growth and geographic distribution of nontraditional mortgages (NTMs) and subprime mortgages during 2000-2006, and examines the association between these products and homeownership at the county level between 2000 and 2012. It finds a significant relationship between the origination of NTM and subprime mortgages during the boom and changes in the number of homeowners (positive during the 2000-2006 period and negative during the 2006-2012 period) but no significant relationship with the change in the homeownership rate. Looking at specific categories of the population, the results indicate a positive relationship between the presence of NTMs and subprime mortgages and increased numbers of homeowners for young households as well as for low income and minority households, but the relationship is smaller than for the general population. Overall, the relationship between NTMs and homeownership is stronger than the relationship between subprime mortgages and homeownership during the boom and it is less negative during the bust

Elevated protein concentrations in newborn blood and the risks of autism spectrum disorder, and of social impairment, at age 10 years among infants born before the 28th week of gestation

Among the 1 of 10 children who are born preterm annually in the United States, 6% are born before the third trimester. Among children who survive birth before the 28th week of gestation, the risks of autism spectrum disorder (ASD) and non-autistic social impairment are severalfold higher than in the general population. We examined the relationship between top quartile inflammation-related protein concentrations among children born extremely preterm and ASD or, separately, a high score on the Social Responsiveness Scale (SRS total score ≥65) among those who did not meet ASD criteria, using information only from the subset of children whose DAS-II verbal or non-verbal IQ was ≥70, who were assessed for ASD, and who had proteins measured in blood collected on ≥2 days (N = 763). ASD (N = 36) assessed at age 10 years is associated with recurrent top quartile concentrations of inflammation-related proteins during the first post-natal month (e.g., SAA odds ratio (OR); 95% confidence interval (CI): 2.5; 1.2–5.3) and IL-6 (OR; 95% CI: 2.6; 1.03–6.4)). Top quartile concentrations of neurotrophic proteins appear to moderate the increased risk of ASD associated with repeated top quartile concentrations of inflammation-related proteins. High (top quartile) concentrations of SAA are associated with elevated risk of ASD (2.8; 1.2–6.7) when Ang-1 concentrations are below the top quartile, but not when Ang-1 concentrations are high (1.3; 0.3–5.8). Similarly, high concentrations of TNF-α are associated with heightened risk of SRS-defined social impairment (N = 130) (2.0; 1.1–3.8) when ANG-1 concentrations are not high, but not when ANG-1 concentrations are elevated (0.5; 0.1–4.2)