A Linear Algebra Approach to Fast DNA Mixture Analysis Using GPUs

Analysis of DNA samples is an important step in forensics, and the speed of analysis can impact investigations. Comparison of DNA sequences is based on the analysis of short tandem repeats (STRs), which are short DNA sequences of 2-5 base pairs. Current forensics approaches use 20 STR loci for analysis. The use of single nucleotide polymorphisms (SNPs) has utility for analysis of complex DNA mixtures. The use of tens of thousands of SNPs loci for analysis poses significant computational challenges because the forensic analysis scales by the product of the loci count and number of DNA samples to be analyzed. In this paper, we discuss the implementation of a DNA sequence comparison algorithm by re-casting the algorithm in terms of linear algebra primitives. By developing an overloaded matrix multiplication approach to DNA comparisons, we can leverage advances in GPU hardware and algoithms for Dense Generalized Matrix-Multiply (DGEMM) to speed up DNA sample comparisons. We show that it is possible to compare 2048 unknown DNA samples with 20 million known samples in under 6 seconds using a NVIDIA K80 GPU.Comment: Accepted for publication at the 2017 IEEE High Performance Extreme Computing conferenc

Julia implementation of the Dynamic Distributed Dimensional Data Model

Julia is a new language for writing data analysis programs that are easy to implement and run at high performance. Similarly, the Dynamic Distributed Dimensional Data Model (D4M) aims to clarify data analysis operations while retaining strong performance. D4M accomplishes these goals through a composable, unified data model on associative arrays. In this work, we present an implementation of D4M in Julia and describe how it enables and facilitates data analysis. Several experiments showcase scalable performance in our new Julia version as compared to the original Matlab implementation

Large Scale Simulations of a Ship Power System with Energy Storage and Multiple Directed Energy Loads

A large scale Simulink® simulation model of the electrical power system of a ship is described. The model includes the major systems onboard, from prime movers to the actual loads, and incorporates several intermittent duty loads along with continuous duty loads. Three types of energy storage systems have been modeled: flywheels, batteries, and capacitors. Therefore, critical issues like stability, reconfigurability, fault management, and minimum rating of energy storage units can be studied. The presence of energy storage has also allowed the study of how these systems can be used to improve the overall performance of the ship. Typical functions, for example, would include load leveling of the power bus, an uninterruptible power supply function for sections of the ship, and the potential for fuel efficiency improvement by reducing the number of turbines being run at fractional loads to fewer being run closer to their optimal specific fuel efficiency point. Typical outputs of the simulations are presented and discussed. In addition, several challenges presented by the scale of the simulations, the software platform used, and the underlying modeling philosophy are discussed with an outlook toward future improvements both in the computing hardware and in the programming methods.Center for Electromechanic

Fast GPU-Based Seismogram Simulation From Microseismic Events in Marine Environments Using Heterogeneous Velocity Models

A novel approach is presented for fast generation of synthetic seismograms due to microseismic events, using heterogeneous marine velocity models. The partial differential equations (PDEs) for the 3D elastic wave equation have been numerically solved using the Fourier domain pseudo-spectral method which is parallelizable on the graphics processing unit (GPU) cards, thus making it faster compared to traditional CPU based computing platforms. Due to computationally expensive forward simulation of large geological models, several combinations of individual synthetic seismic traces are used for specified microseismic event locations, in order to simulate the effect of realistic microseismic activity patterns in the subsurface. We here explore the patterns generated by few hundreds of microseismic events with different source mechanisms using various combinations, both in event amplitudes and origin times, using the simulated pressure and three component particle velocity fields via 1D, 2D and 3D seismic visualizations.Shell Projects and Technolog