The solution of linear systems of equations with a structural analysis code on the NAS CRAY-2

Two methods for solving linear systems of equations on the NAS Cray-2 are described. One is a direct method; the other is an iterative method. Both methods exploit the architecture of the Cray-2, particularly the vectorization, and are aimed at structural analysis applications. To demonstrate and evaluate the methods, they were installed in a finite element structural analysis code denoted the Computational Structural Mechanics (CSM) Testbed. A description of the techniques used to integrate the two solvers into the Testbed is given. Storage schemes, memory requirements, operation counts, and reformatting procedures are discussed. Finally, results from the new methods are compared with results from the initial Testbed sparse Choleski equation solver for three structural analysis problems. The new direct solvers described achieve the highest computational rates of the methods compared. The new iterative methods are not able to achieve as high computation rates as the vectorized direct solvers but are best for well conditioned problems which require fewer iterations to converge to the solution

Mapping implicit spectral methods to distributed memory architectures

Spectral methods were proven invaluable in numerical simulation of PDEs (Partial Differential Equations), but the frequent global communication required raises a fundamental barrier to their use on highly parallel architectures. To explore this issue, a 3-D implicit spectral method was implemented on an Intel hypercube. Utilization of about 50 percent was achieved on a 32 node iPSC/860 hypercube, for a 64 x 64 x 64 Fourier-spectral grid; finer grids yield higher utilizations. Chebyshev-spectral grids are more problematic, since plane-relaxation based multigrid is required. However, by using a semicoarsening multigrid algorithm, and by relaxing all multigrid levels concurrently, relatively high utilizations were also achieved in this harder case

Efficient multitasking of Choleski matrix factorization on CRAY supercomputers

A Choleski method is described and used to solve linear systems of equations that arise in large scale structural analysis. The method uses a novel variable-band storage scheme and is structured to exploit fast local memory caches while minimizing data access delays between main memory and vector registers. Several parallel implementations of this method are described for the CRAY-2 and CRAY Y-MP computers demonstrating the use of microtasking and autotasking directives. A portable parallel language, FORCE, is used for comparison with the microtasked and autotasked implementations. Results are presented comparing the matrix factorization times for three representative structural analysis problems from runs made in both dedicated and multi-user modes on both computers. CPU and wall clock timings are given for the parallel implementations and are compared to single processor timings of the same algorithm

Gigaflop performance on a CRAY-2: Multitasking a computational fluid dynamics application

The methodology is described for converting a large, long-running applications code that executed on a single processor of a CRAY-2 supercomputer to a version that executed efficiently on multiple processors. Although the conversion of every application is different, a discussion of the types of modification used to achieve gigaflop performance is included to assist others in the parallelization of applications for CRAY computers, especially those that were developed for other computers. An existing application, from the discipline of computational fluid dynamics, that had utilized over 2000 hrs of CPU time on CRAY-2 during the previous year was chosen as a test case to study the effectiveness of multitasking on a CRAY-2. The nature of dominant calculations within the application indicated that a sustained computational rate of 1 billion floating-point operations per second, or 1 gigaflop, might be achieved. The code was first analyzed and modified for optimal performance on a single processor in a batch environment. After optimal performance on a single CPU was achieved, the code was modified to use multiple processors in a dedicated environment. The results of these two efforts were merged into a single code that had a sustained computational rate of over 1 gigaflop on a CRAY-2. Timings and analysis of performance are given for both single- and multiple-processor runs

Baseline age and time to major fracture in younger postmenopausal women

To estimate the incidence of first hip or clinical vertebral fracture or major osteoporotic (hip, clinical vertebral, proximal humerus or wrist) fracture in postmenopausal women receiving their first bone mineral density (BMD) test before age 65

Time to Clinically Relevant Fracture Risk Scores in Postmenopausal Women.

BackgroundClinical practice guidelines recommend use of fracture risk scores for screening and pharmacologic treatment decisions. The timing of occurrence of treatment-level (according to 2014 National Osteoporosis Foundation guidelines) or screening-level (according to 2011 US Preventive Services Task Force guidelines) fracture risk scores has not been estimated in postmenopausal women.MethodsWe conducted a retrospective competing risk analysis of new occurrence of treatment-level and screening-level fracture risk scores in postmenopausal women aged 50 years and older, prior to receipt of pharmacologic treatment and prior to first hip or clinical vertebral fracture.ResultsIn 54,280 postmenopausal women aged 50 to 64 years without a bone mineral density test, the time for 10% to develop a treatment-level FRAX score could not be estimated accurately because of rare incidence of treatment-level scores. In 6096 women who had FRAX scores calculated with bone mineral density, the estimated unadjusted time to treatment-level FRAX ranged from 7.6 years (95% confidence interval [CI], 6.6-8.7) for those aged 65 to 69, to 5.1 years (95% CI, 3.5-7.5) for those aged 75 to 79 at baseline. Of 17,967 women aged 50 to 64 with a screening-level FRAX at baseline, 100 (0.6%) experienced a hip or clinical vertebral fracture by age 65 years.ConclusionsPostmenopausal women with sub-threshold fracture risk scores at baseline were unlikely to develop a treatment-level FRAX score between ages 50 and 64 years. After age 65, the increased incidence of treatment-level fracture risk scores, osteoporosis, and major osteoporotic fracture supports more frequent consideration of FRAX and bone mineral density testing

Clonal evolution and resistance to EGFR blockade in the blood of colorectal cancer patients

Colorectal cancers (CRCs) evolve by a reiterative process of genetic diversification and clonal evolution. The molecular profile of CRC is routinely assessed in surgical or bioptic samples. Genotyping of CRC tissue has inherent limitations; a tissue sample represents a single snapshot in time, and it is subjected to spatial selection bias owing to tumor heterogeneity. Repeated tissue samples are difficult to obtain and cannot be used for dynamic monitoring of disease progression and response to therapy. We exploited circulating tumor DNA (ctDNA) to genotype colorectal tumors and track clonal evolution during treatment with the epidermal growth factor receptor (EGFR)-specific antibodies cetuximab or panitumumab. We identified alterations in ctDNA of patients with primary or acquired resistance to EGFR blockade in the following genes: KRAS, NRAS, MET, ERBB2, FLT3, EGFR and MAP2K1. Mutated KRAS clones, which emerge in blood during EGFR blockade, decline upon withdrawal of EGFR-specific antibodies, indicating that clonal evolution continues beyond clinical progression. Pharmacogenomic analysis of CRC cells that had acquired resistance to cetuximab reveals that upon antibody withdrawal KRAS clones decay, whereas the population regains drug sensitivity. ctDNA profiles of individuals who benefit from multiple challenges with anti-EGFR antibodies exhibit pulsatile levels of mutant KRAS. These results indicate that the CRC genome adapts dynamically to intermittent drug schedules and provide a molecular explanation for the efficacy of rechallenge therapies based on EGFR blockade