Optimizing the Distributed Hydrology Soil Vegetation Model for Uncertainty Assessment With Serial, Multicore and Distributed Accelerations

Hydrology is the study of water. Hydrology tracks various attributes of water such as its quality and movement. As a tool Hydrology allows researchers to investigate topics such as the impacts of wildfires, logging, and commercial development. With perfect and complete data collection researchers could answer these questions with complete certainty. However, due to cost and potential sources of error this is impractical. As such researchers rely on simulations. The Distributed Hydrology Soil Vegetation Model(also referenced to as DHSVM) is a scientific mathematical model to numerically represent watersheds. Hydrology, as with all fields, continues to produce large amounts of data from researchers. As the stores of data increase the scientific models that process them require occasional improvements to better handle processing the masses of information. This paper investigates DHSVM as a serial C program. The paper implements and analyzes various high performance computing advancements to the original code base. Specifically this paper investigates compiler optimization, implementing par- allel computing with OpenMP, and adding distributed computing with OpenMPI. DHSVM was also tuned to run many instances on California Polytechnic State Uni- visity, San Luis Obispo’s high performance computer cluster. These additions to DHSVM help speed-up the results returned to researches, and improves DHSVM’s ability to be used with uncertainty analysis methods. iv This paper was able to improve the performance of DHSVM 2 times with serial and compiler optimization. In addition to the serial and compiler optimizations this paper found that OpenMP provided a noticeable speed up on hardware, that also scaled as the hardware improved. The pareallel optimization doubled DHSVM’s speed again on commodity hardware. Finally it was found that OpenMPI was best used for running multiple instances of DHSVM. All combined this paper was able to improve the performance of DHSVM by 4.4 times per instance, and allow it to run multiple instances on computing clusters

Visual Code: Breaking the Binary

This project seeks to create an accessible programming language that is more visually based. Although some solutions exist, namely MIT’s Scratch, nothing has caught up to the mobile age. This proj- ect aims to reframe creating a game or app into the context of tell- ing a story, putting character creation first. By researching sto- ry-telling and how people learn, and by applying technical and user interface design knowledge, this project intends to deliver a soft- ware solution that opens introductory coding education to more people

Determinants of leader cells in collective cell migration.

Contains fulltext : 88409.pdf (publisher's version ) (Open Access)Collective migration is a basic mechanism of cell translocation during morphogenesis, wound repair and cancer invasion. Collective movement requires cells to retain cell-cell contacts, exhibit group polarization with defined front-rear asymmetry, and consequently move as one multicellular unit. Depending on the cell type, morphology of the group and the tissue context, distinct mechanisms control the leading edge dynamics and guidance. Leading edge migration may either result from adhesion to ECM and contractile pulling, or from forward pushing. The leading edge consists of either one or few dedicated tip cells or a multicellular leading row that generate adhesion and traction towards the tissue substrate. Alternatively, a multicellular bud consisting of many cells protrudes collectively by proliferation and growth thereby mechanically expanding and pushing towards the tissue stroma. Each type of collective guidance engages distinct spatiotemporal molecular control and feedback towards rearward cells and the adjacent tissue microenvironment; these include intrinsic polarity mechanisms regulated by the interplay between cell-cell and cell-ECM interactions; or the heterotypic integration of stromal cells that adopt leader cell functions. We here classify molecular and mechanical mechanisms of leading function in collective cell migration during morphogenesis and wound repair and discuss how these are recapitulated during collective invasion of cancer cells