Assessing Paleoenvironmental and Geomorphic Variability in Relationship to Paleoindian Site Burial; Centennial Valley, Montana

Wave action along the shores of Lima Reservoir in Centennial Valley, Montana is actively eroding the southern margins of three neighboring Paleoindian sites. Despite ostensible similarity among the sites, major site formation differences are apparent in exposed sediments. Shoreline cutbank exposures one-to-five meters high connect the sites and reveal a complicated geomorphic history. Although each site contains artifact evidence of terminal Pleistocene-early Holocene occupations, Paleoindian components at these three localities occur in very different contexts: one is buried, while the other two are apparent surface scatters. This raise the question of why sites of the same age are in both buried and exposed contexts. Moreover, buried sites are more likely to have preserved spatial layout and sites with buried components are more likely to be considered significant under National Register of Historic Places criteria. These factors therefore prompt the management question of where might other buried sites be located in the valley? In order to answer these questions, I used a multi-pronged approach including optically stimulated luminescence dating, sediment grain size analysis, stratigraphic profiling and sediment facies analysis. I accomplished two nested objectives with this research. First, I reconstructed the last 60,000 years of geomorphic events for the area surrounding the three sites in order to determine what conditions resulted in site burial. Second, I used those findings to outline criteria for differentiating occupation-age and pre-occupation-age stratigraphic layers in Centennial Valley. I determined, in part, that cultural-age deposits are present at both high and low elevations and that they may be marked by a specific soil sequence. The oldest packages, far pre-dating potential human occupation, are deep lake and high energy stream sediments that may be recognized by soil color alteration and thick gypsum horizons

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

The ongoing hardware evolution exhibits an escalation in the number, as well as in the heterogeneity, of computing resources. The pressure to maintain reasonable levels of performance and portability forces application developers to leave the traditional programming paradigms and explore alternative solutions. PaStiX is a parallel sparse direct solver, based on a dynamic scheduler for modern hierarchical manycore architectures. In this paper, we study the benefits and limits of replacing the highly specialized internal scheduler of the PaStiX solver with two generic runtime systems: PaRSEC and StarPU. The tasks graph of the factorization step is made available to the two runtimes, providing them the opportunity to process and optimize its traversal in order to maximize the algorithm efficiency for the targeted hardware platform. A comparative study of the performance of the PaStiX solver on top of its native internal scheduler, PaRSEC, and StarPU frameworks, on different execution environments, is performed. The analysis highlights that these generic task-based runtimes achieve comparable results to the application-optimized embedded scheduler on homogeneous platforms. Furthermore, they are able to significantly speed up the solver on heterogeneous environments by taking advantage of the accelerators while hiding the complexity of their efficient manipulation from the programmer.Comment: Heterogeneity in Computing Workshop (2014

GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP

Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale linearly with luminosity increase, compensated only partially by an increase of computing resources. The extension of fast simulation approaches to more use cases, covering a larger fraction of the simulation budget, is only part of the solution due to intrinsic precision limitations. The remainder corresponds to speeding-up the simulation software by several factors, which is out of reach using simple optimizations on the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport codes in order to make them benefit from fine-grained parallelism features such as vectorization, but also from increased code and data locality. This paper presents extensively the results and achievements of this R&D, as well as the conclusions and lessons learnt from the beta prototype.Comment: 34 pages, 26 figures, 24 table

Archaeological Survey of Upper Leon Creek Terraces, Bexar County, Texas

In June and July 1994, the Center for Archaeological Research (CAR) of The University of Texas at San Antonio (UTSA) conducted an archaeological survey on a 147-acre tract of land along Leon Creek in northern San Antonio for Pape-Dawson Engineers. The archaeological work was needed for compliance with U. S. Army Corps of Engineers permit requirements before construction of a water storage facility. Four archaeological sites (41BX40, 4IBX47 , 4IBX48, and 4IBX50) had been recorded within this area in 1970 by avocational archaeologists. Additionally, CAR staff members conducted a brief reconnaissance over a 60-acre portion of the property in 1992. Fieldwork consisted of pedestrian survey, 222 shovel tests, one 1-x-1-m test unit, backhoe trenches, plowing, and a geomorphological study by Lee Nordt of Texas A&M University. Evidence from this work suggests that two of the previously recorded sites, 4IBX40 and 4IBX47, are actually part of a single, largely intact, Early and Middle Archaic period site covering approximately 30 acres of the project area. The single site will retain the trinomial 4IBX47. The site contains three components: a Middle Archaic one in the upper 50 cm of the northern part of the site; an Early Archaic component, also in the upper 50 cm, found in the western part of the site; and a component of unknown age buried approximately 80-120 cm below the surface in the central part of the site. A transitional Archaic projectile point was found outside the boundaries of 4IBX47. Further investigation of this site is recommended before construction of the water storage facility. A series of simulated sampling experiments was also conducted with the shovel test data to evaluate the effectiveness of different sampling designs

Improving Structural Features Prediction in Protein Structure Modeling

Proteins play a vital role in the biological activities of all living species. In nature, a protein folds into a specific and energetically favorable three-dimensional structure which is critical to its biological function. Hence, there has been a great effort by researchers in both experimentally determining and computationally predicting the structures of proteins. The current experimental methods of protein structure determination are complicated, time-consuming, and expensive. On the other hand, the sequencing of proteins is fast, simple, and relatively less expensive. Thus, the gap between the number of known sequences and the determined structures is growing, and is expected to keep expanding. In contrast, computational approaches that can generate three-dimensional protein models with high resolution are attractive, due to their broad economic and scientific impacts. Accurately predicting protein structural features, such as secondary structures, disulfide bonds, and solvent accessibility is a critical intermediate step stone to obtain correct three-dimensional models ultimately. In this dissertation, we report a set of approaches for improving the accuracy of structural features prediction in protein structure modeling. First of all, we derive a statistical model to generate context-based scores characterizing the favorability of segments of residues in adopting certain structural features. Then, together with other information such as evolutionary and sequence information, we incorporate the context-based scores in machine learning approaches to predict secondary structures, disulfide bonds, and solvent accessibility. Furthermore, we take advantage of the emerging high performance computing architectures in GPU to accelerate the calculation of pairwise and high-order interactions in context-based scores. Finally, we make these prediction methods available to the public via web services and software packages