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T Rydén, J Heydorn Lagerlöf, J Hemmingsson, I Marin, J Svensson, M Båth, P Gjertsson, P Bernhardt
BACKGROUND: Full Monte Carlo (MC)-based SPECT reconstructions have a strong potential for correcting for image degrading factors, but the reconstruction times are long. The objective of this study was to develop a highly parallel Monte Carlo code for fast, ordered subset expectation maximum (OSEM) reconstructions of SPECT/CT images. The MC code was written in the Compute Unified Device Architecture language for a computer with four graphics processing units (GPUs) (GeForce GTX Titan X, Nvidia, USA)...
January 4, 2018: EJNMMI Physics
Dmitri Matenine, Geoffroi Côté, Julia Mascolo-Fortin, Yves Goussard, Philippe Després
PURPOSE: Iterative reconstruction algorithms in computed tomography (CT) require a fast method for computing the intersection distances between the trajectories of photons and the object, also called ray-tracing or system matrix computation. This work focused on the thin-ray model and is aimed at comparing different system matrix handling strategies using graphical processing units (GPUs). METHODS: In this work, the system matrix is modeled by thin rays intersecting a regular grid of box-shaped voxels, known to be an accurate representation of the forward projection operator in CT...
December 6, 2017: Medical Physics
Daniel Probst, Jean-Louis Reymond
Motivation: During the past decade, big data has become a major tool in scientific endeavors. While statistical methods and algorithms are well-suited for analyzing and summarizing enormous amounts of data, the results do not allow for a visual inspection of the entire data. Current scientific software, including R packages and Python libraries such as ggplot2, matplotlib, and, do not support interactive visualizations of datasets exceeding 100,000 data points on the web. Other solutions enable the web-based visualization of big data only through data reduction or statistical representations...
November 24, 2017: Bioinformatics
Aaron Michael Hagan, Amit Sawant, Michael Folkerts, Arezoo Modiri
We report on the design, implementation and characterization of a multi-graphic processing unit (GPU) computational platform for higher-order optimization in radiotherapy treatment planning. In collaboration with a commercial vendor (Varian Medical Systems, Palo Alto, CA), a research prototype GPU-enabled Eclipse (V13.6) workstation was configured. The hardware consisted of dual 8-core xeon processors, 256 GB RAM and four NVIDIA Tesla K80 general purpose GPUs. We demonstrate the utility of this platform for large radiotherapy optimization problems through the development and characterization of a parallelized particle swarm optimization (PSO) four dimensional (4D) intensity modulated radiation therapy (IMRT) technique...
November 23, 2017: Physics in Medicine and Biology
Philippe Després, Xun Jia
Tomographic image reconstruction is a computationally demanding task, even more so when advanced models are used to describe a more complete and accurate picture of the image formation process. Such advanced modeling and reconstruction algorithms can lead to better images, often with less dose, but at the price of long calculation times that are hardly compatible with clinical workflows. Fortunately, reconstruction tasks can often be executed advantageously on Graphics Processing Units (GPUs), which are exploited as massively parallel computational engines...
October 2017: Physica Medica: PM
Alan Pryor, Colin Ophus, Jianwei Miao
Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. Here, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods...
2017: Advanced Structural and Chemical Imaging
Timothy Blattner, Walid Keyrouz, Shuvra S Bhattacharyya, Milton Halem, Mary Brady
Designing applications for scalability is key to improving their performance in hybrid and cluster computing. Scheduling code to utilize parallelism is difficult, particularly when dealing with data dependencies, memory management, data motion, and processor occupancy. The Hybrid Task Graph Scheduler (HTGS) improves programmer productivity when implementing hybrid workflows for multi-core and multi-GPU systems. The Hybrid Task Graph Scheduler (HTGS) is an abstract execution model, framework, and API that increases programmer productivity when implementing hybrid workflows for such systems...
December 2017: Journal of Signal Processing Systems
Xiaodong Li, Jiangfeng Wan, Sheng Zhang, Ping Lin, Yanshi Zhang, Guanghui Yang, Mengke Wang, Wenshan Duan, Jian'an Sun, Lei Yang
A spallation target is one of the three core parts of the accelerator driven subcritical system (ADS), which has already been investigated for decades. Recently, a gravity-driven Dense Granular-flow Target (DGT) is proposed, which consists of a cylindrical hopper and an internal coaxial cylindrical beam pipe. The research on the flow rate and free surface are important for the design of the target whether in Heavy Liquid Metal (HLM) targets or the DGT. In this paper, the relations of flow rate and the geometry of the DGT are investigated...
2017: PloS One
Nan Qin, Chenyang Shen, Min-Yu Tsai, Marco Pinto, Zhen Tian, Georgios Dedes, Arnold Pompos, Steve B Jiang, Katia Parodi, Xun Jia
PURPOSE: One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy...
September 12, 2017: International Journal of Radiation Oncology, Biology, Physics
Laurens D M Peters, Jörg Kussmann, Christian Ochsenfeld
An efficient scheme for the calculation of Born-Oppenheimer molecular dynamics (BOMD) simulations is introduced. It combines the corrected small basis set Hartree-Fock (HF-3c) method by Sure and Grimme [J. Comput. Chem. 2013, 43, 1672], extended Lagrangian BOMD (XL-BOMD) by Niklasson et al. [J. Chem. Phys. 2009, 130, 214109], and the calculation of the two electron integrals on graphics processing units (GPUs) [J. Chem. Phys. 2013, 138, 134114; J. Chem. Theory Comput. 2015, 11, 918]. To explore the parallel performance of our strong scaling implementation of the method, we present timings and extract, as its validation and first illustrative application, high-quality vibrational spectra from simulated trajectories of β-carotene, paclitaxel, and liquid water (up to 500 atoms)...
October 25, 2017: Journal of Chemical Theory and Computation
Sebastián Bronte, Luis M Bergasa, Daniel Pizarro, Rafael Barea
This paper presents a sequential non-rigid reconstruction method that recovers the 3D shape and the camera pose of a deforming object from a video sequence and a previous shape model of the object. We take PTAM (Parallel Mapping and Tracking), a state-of-the-art sequential real-time SfM (Structure-from-Motion) engine, and we upgrade it to solve non-rigid reconstruction. Our method provides a good trade-off between processing time and reconstruction error without the need for specific processing hardware, such as GPUs...
October 14, 2017: Sensors
Filippo Bistaffa, Nicola Bombieri, Alessandro Farinelli
Bucket elimination (BE) is a framework that encompasses several algorithms, including belief propagation (BP) and variable elimination for constraint optimization problems (COPs). BE has significant computational requirements that can be addressed by using graphics processing units (GPUs) to parallelize its fundamental operations, i.e., composition and marginalization, which operate on functions represented by large tables. We propose a novel approach to parallelize these operations with GPUs, which optimizes the table layout so to achieve better performance in terms of increased speedup and scalability...
November 2017: IEEE Transactions on Cybernetics
ThienLuan Ho, Seung-Rohk Oh, HyunJin Kim
Approximate string matching with k-differences has a number of practical applications, ranging from pattern recognition to computational biology. This paper proposes an efficient memory-access algorithm for parallel approximate string matching with k-differences on Graphics Processing Units (GPUs). In the proposed algorithm, all threads in the same GPUs warp share data using warp-shuffle operation instead of accessing the shared memory. Moreover, we implement the proposed algorithm by exploiting the memory structure of GPUs to optimize its performance...
2017: PloS One
Gang Mei, Liangliang Xu, Nengxiong Xu
This paper focuses on designing and implementing parallel adaptive inverse distance weighting (AIDW) interpolation algorithms by using the graphics processing unit (GPU). The AIDW is an improved version of the standard IDW, which can adaptively determine the power parameter according to the data points' spatial distribution pattern and achieve more accurate predictions than those predicted by IDW. In this paper, we first present two versions of the GPU-accelerated AIDW, i.e. the naive version without profiting from the shared memory and the tiled version taking advantage of the shared memory...
September 2017: Royal Society Open Science
Kevin L Keys, Gary K Chen, Kenneth Lange
A genome-wide association study (GWAS) correlates marker and trait variation in a study sample. Each subject is genotyped at a multitude of SNPs (single nucleotide polymorphisms) spanning the genome. Here, we assume that subjects are randomly collected unrelateds and that trait values are normally distributed or can be transformed to normality. Over the past decade, geneticists have been remarkably successful in applying GWAS analysis to hundreds of traits. The massive amount of data produced in these studies present unique computational challenges...
December 2017: Genetic Epidemiology
Muaaz Gul Awan, Fahad Saeed
Modern high resolution Mass Spectrometry instruments can generate millions of spectra in a single systems biology experiment. Each spectrum consists of thousands of peaks but only a small number of peaks actively contribute to deduction of peptides. Therefore, pre-processing of MS data to detect noisy and non-useful peaks are an active area of research. Most of the sequential noise reducing algorithms are impractical to use as a pre-processing step due to high time-complexity. In this paper, we present a GPU based dimensionality-reduction algorithm, called G-MSR, for MS2 spectra...
August 2017: ACM-BCB: ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Markus Hadwiger, Ali K Al-Awami, Johanna Beyer, Marco Agus, Hanspeter Pfister
Recent advances in data acquisition produce volume data of very high resolution and large size, such as terabyte-sized microscopy volumes. These data often contain many fine and intricate structures, which pose huge challenges for volume rendering, and make it particularly important to efficiently skip empty space. This paper addresses two major challenges: (1) The complexity of large volumes containing fine structures often leads to highly fragmented space subdivisions that make empty regions hard to skip efficiently...
August 29, 2017: IEEE Transactions on Visualization and Computer Graphics
Siavash Malektaji, Ivan T Lima, Mauricio R Escobar I, Sherif S Sherif
BACKGROUND AND OBJECTIVE: An accurate and practical simulator for Optical Coherence Tomography (OCT) could be an important tool to study the underlying physical phenomena in OCT such as multiple light scattering. Recently, many researchers have investigated simulation of OCT of turbid media, e.g., tissue, using Monte Carlo methods. The main drawback of these earlier simulators is the long computational time required to produce accurate results. We developed a massively parallel simulator of OCT of inhomogeneous turbid media that obtains both Class I diffusive reflectivity, due to ballistic and quasi-ballistic scattered photons, and Class II diffusive reflectivity due to multiply scattered photons...
October 2017: Computer Methods and Programs in Biomedicine
Jyh-Da Wei, Hui-Jun Cheng, Chun-Yuan Lin, Jin Ye, Kuan-Yu Yeh
High-end graphics processing units (GPUs), such as NVIDIA Tesla/Fermi/Kepler series cards with thousands of cores per chip, are widely applied to high-performance computing fields in a decade. These desktop GPU cards should be installed in personal computers/servers with desktop CPUs, and the cost and power consumption of constructing a GPU cluster platform are very high. In recent years, NVIDIA releases an embedded board, called Jetson Tegra K1 (TK1), which contains 4 ARM Cortex-A15 CPUs and 192 Compute Unified Device Architecture cores (belong to Kepler GPUs)...
2017: Evolutionary Bioinformatics Online
Sascha Brück, Mauro Calderara, Mohammad Hossein Bani-Hashemian, Joost VandeVondele, Mathieu Luisier
Massively parallel algorithms are presented in this paper to reduce the computational burden associated with quantum transport simulations from first-principles. The power of modern hybrid computer architectures is harvested in order to determine the open boundary conditions that connect the simulation domain with its environment and to solve the resulting Schrödinger equation. While the former operation takes the form of an eigenvalue problem that is solved by a contour integration technique on the available central processing units (CPUs), the latter can be cast into a linear system of equations that is simultaneously processed by SplitSolve, a two-step algorithm, on general-purpose graphics processing units (GPUs)...
August 21, 2017: Journal of Chemical Physics
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