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parallel Automatic Registration of large Scale Microscopic Images on Multiprocessor CPUs and GPUs

Parallel Automatic Registration of Large Scale Microscopic I...

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ieee International symposium on parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Lee Cooper Kun Huang Manuel Ujaldon Center of Comprehensive Informatics Emory University Atlanta GA USA Biomedical Informatics Department Ohio State Uinversity Columbus OH USA Computer Architecture Department University of Malaga Malaga Spain

During the present decade, emerging architectures like multicore CPUs and graphics processing units (GPUs) have steadily gained popularity for their ability to deploy high computational power at a low cost. In this paper, we combine parallelization techniques on a cooperative cluster of multicore CPUs and multisocket GPUs to apply their joint computational power to an automatic image registration algorithm intended for the analysis of high-resolution microscope images. Registration methods pose a computational challenge within the biomedical field due to the large size of microscope image data sets, which typically extend to the Terabyte scale. We analyze this application to identify those parts which are more favorable to the CPU and GPU execution models and decompose the process accordingly. Performance results are presented for two sets of images: mouse placenta (16K × 16K pixels) and mouse mammary tumor (23K × 62K pixels). Execution times are shown on different multi-node, multi-socket and multi-core configurations to provide performance insights about the most effective approach.

关键词： graphics processing unit Microscopy Multicore processing Sockets Random access memory parallel processing Hardware

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Conformal visualization for partially-immersive platforms

Conformal visualization for partially-immersive platforms

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ieee Annual International symposium Virtual Reality

作者： Kaloian Petkov Charilaos Papadopoulos Min Zhang Arie E. Kaufman Xianfeng Gu Computer Science Department Stony Brook University Stony Brook NY USA

Current VR systems such as the CAVE provide an effective platform for the immersive exploration of large 3D data. A major limitation is that in most cases at least one display surface, such as a ceiling or a back wall, is missing due to space, access or cost constraints. This partially-immersive visualization results in a substantial loss of visual information that may be acceptable for some applications; however, it becomes a major obstacle for critical tasks that need to utilize the users' entire field of vision. We have developed a conformal rendering pipeline for the visualization of datasets on partially-immersive platforms. The angle-preserving conformal mapping approach is used to render the 360° view directly onto arbitrary display configurations. It has the desirable property of preserving shapes locally, which is important for identifying shape-based features in the data. Our conformal visualization technique is applicable to rasterization, volume rendering and real-time raytracing, and in contrast to image-based retargeting approaches, it constructs accurate, artifact-free stereoscopic images. We demonstrate our conformal visualization pipeline in the 5-sided CAVE for Immersive Virtual Colonoscopy, as well as architectural and abstract data exploration. Our user study shows that on the visual polyp detection task, conformal visualization leads to improved sensitivity at comparable examination times against the traditional rendering approach.

关键词： Rendering (computer graphics) Measurement data visualization Shape visualization Conformal mapping Geometry

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High Performance data Mining Using R on Heterogeneous Platforms

High Performance Data Mining Using R on Heterogeneous Platfo...

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ieee International symposium on parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Prabhat Kumar Berkin Ozisikyilmaz Wei-Keng Liao Gokhan Memik Alok Choudhary Department of Electrical Engineering and Computer Science Northwestern University Evanston IL USA

The exponential increase in the generation and collection of data has led us in a new era of data analysis and information extraction. Conventional systems based on general-purpose processors are unable to keep pace with the heavy computational requirements of data mining techniques. High performance co-processors like GPUs and FPGAs have the potential to handle large computational workloads. In this paper, we present a scalable framework aimed at providing a platform for developing and using high performance data mining applications on heterogeneous platforms. The framework incorporates a software infrastructure and a library of high performance kernels. Furthermore, it includes a variety of optimizations which increase the throughput of applications. The framework spans multiple technologies including R, GPUs, multi-core CPUs, MPI, and parallelnet CDF harnessing their capabilities for high-performance computations. This paper also introduces the concept of interleaving GPU kernels from multiple applications providing significant performance gain. Thus, in comparison to other tools available for data mining, our framework provides an easy-to-use and scalable environment both for application development and execution. The framework is available as a software package which can be easily integrated in the R programming environment.

关键词： Kernel data mining graphics processing unit Libraries Computer architecture Optimization parallel processing

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Recognition-driven 3D navigation in large-scale virtual environments

Recognition-driven 3D navigation in large-scale virtual envi...

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ieee Annual International symposium Virtual Reality

作者： Wei Guan Suya You Ulrich Neumann Computer Graphics and Immersive Technologies University of Southern California USA

We present a recognition-driven navigation system for large-scale 3D virtual environments. The proposed system contains three parts, virtual environment reconstruction, feature database building and recognition-based navigation. The virtual environment is reconstructed automatically with LIDAR data and aerial images. The feature database is composed of image patches with features and registered location and orientation information. The database images are taken at different distances from the scenes with various viewing angles, and these images are then partitioned into smaller patches. When a user navigates the real world with a handheld camera, the captured image is used to estimate its location and orientation. These location and orientation information are also reflected in the virtual environment. With the proposed patch approach, the recognition is robust to large occlusions and can be done in real time. Experiments show that our proposed navigation system is efficient and well synchronized with real world navigation.

关键词： Navigation Cameras databases Three dimensional displays Virtual environment Buildings visualization

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An environment for visualizing higher dimensional measured data

An environment for visualizing higher dimensional measured d...

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ieee Instrumentation and Measurement Technology Conference

作者： Lee Barford Roberto Lopez-Hernandez Michael J. McGuffin Measurement Research Laboratory Agilent Technologies Inc. Reno NV USA École de technologie supérieure Montreal QUE Canada

Over the last few decades, the ability of instrumentation to measure large volumes of data has literally been growing exponentially. It is increasingly easy to build a measurement system with a large number of channels that come from acquisition cards and networked sensors. Analysis and statistics from raw measurements yeild derived measurements that add to the dimensionality of the space that a measurement user needs to understand to gain knowledge or solve problems from the data. It is therefore necessary to create methods that permit the exploration of such large and high dimensional sets of measured data within the limitations of the graphics rendering capabilities, screen sizes, and input devices that can reasonably be built into instrumentation and measurement systems. The problem addressed in this paper is that of vizualizing measured data of higher dimension (>; 10) and moderately large size. We present a software prototype that uses multiple complementary graphical views to display multidimensional data, with coordinated highlighting across views and flexible selection techniques. Here, we describe a tool providing a new combination of existing methods, scatterplot matrices (SPLOMs) and parallel coordinate plots (PCPs), for exploring higher dimensional data. We demonstrate the tool's application to measured orthogonal frequency-division multiplexing (OFDM) signals including identifying the nature of a disturbance in the signal.

关键词： data visualization Prototypes Image color analysis Size measurement Constellation diagram Gain measurement

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Towards an Effective Unified Programming Model for Many-Cores

Towards an Effective Unified Programming Model for Many-Core...

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ieee International symposium on parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Ana Lucia Varbanescu Pieter Hijma Rob van Nieuwpoort Henri Bal Parallel and Distributed Systems Group Delft University of Technnology Netherlands Computing Systems Group Vrije Universiteit Amsterdam Netherlands ASTRON Dwingeloo Netherlands

Building an effective programming model for many-core processors is challenging. On the one hand, the increasing variety of platforms and their specific programming models force users to take a hardware-centric approach not only for implementing parallel applications, but also for designing them. This approach diminishes portability and, eventually, limits performance. On the other hand, to effectively cope with the increased number of large-scale workloads that require parallelization, a portable, application-centric programming model is desirable. Such a model enables programmers to focus first on extracting and exploiting parallelism from their applications, as opposed to generating parallelism for specific hardware, and only second on platform-specific implementation and optimizations. In this paper, we first present a survey of programming models designed for programming three families of many-cores: general purpose many-cores (GPMCs), graphics processing units (GPUs), and the Cell/B.E.. We analyze the usability of these models, their ability to improve platform programmability, and the specific features that contribute to this improvement. Next, we also discuss two types of generic models: parallelism-centric and application-centric. We also analyze their features and impact on platform programmability. Based on this analysis, we recommend two application-centric models (OmpSs and OpenCL) as promising candidates for a unified programming model for many-cores and we discuss potential enhancements for them.

关键词： Programming parallel processing Computer architecture data models Concurrent computing Computational modeling Productivity

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Moving the Code to the data - Dynamic Code Deployment Using ActiveSpaces

Moving the Code to the Data - Dynamic Code Deployment Using ...

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International symposium on parallel and Distributed Processing (IPDPS)

作者： Ciprian Docan Manish Parashar Julian Cummings Scott Klasky Rutgers University Piscataway NJ USA California Institute of Technology Pasadena CA USA Oak Ridge National Laboratory Oak Ridge TN USA

Managing the large volumes of data produced by emerging scientific and engineering simulations running on leadership-class resources has become a critical challenge. The data has to be extracted off the computing nodes and transported to consumer nodes so that it can be processed, analyzed, visualized, archived, etc. Several recent research efforts have addressed data-related challenges at different levels. One attractive approach is to offload expensive I/O operations to a smaller set of dedicated computing nodes known as a staging area. However, even using this approach, the data still has to be moved from the staging area to consumer nodes for processing, which continues to be a bottleneck. In this paper, we investigate an alternate approach, namely moving the data-processing code to the staging area rather than moving the data. Specifically, we present the Active Spaces framework, which provides (1) programming support for defining the data-processing routines to be downloaded to the staging area, and (2) run-time mechanisms for transporting binary codes associated with these routines to the staging area, executing the routines on the nodes of the staging area, and returning the results. We also present an experimental performance evaluation of Active Spaces using applications running on the Cray XT5 at Oak Ridge National Laboratory. Finally, we use a coupled fusion application workflow to explore the trade-offs between transporting data and transporting the code required for data processing during coupling, and we characterize the sweet spots for each option.

关键词： Kernel Servers Couplings data visualization Computational modeling data models Three dimensional displays

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parallelTopics: A probabilistic approach to exploring document collections

ParallelTopics: A probabilistic approach to exploring docume...

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ieee symposium on Visual Analytics Science and Technology (VAST)

作者： Wenwen Dou Xiaoyu Wang Remco Chang William Ribarsky UNC-Charlotte USA Tufts University USA

Scalable and effective analysis of large text corpora remains a challenging problem as our ability to collect textual data continues to increase at an exponential rate. To help users make sense of large text corpora, we present a novel visual analytics system, parallel-Topics, which integrates a state-of-the-art probabilistic topic model Latent Dirichlet Allocation (LDA) with interactive visualization. To describe a corpus of documents, parallelTopics first extracts a set of semantically meaningful topics using LDA. Unlike most traditional clustering techniques in which a document is assigned to a specific cluster, the LDA model accounts for different topical aspects of each individual document. This permits effective full text analysis of larger documents that may contain multiple topics. To highlight this property of the model, parallelTopics utilizes the parallel coordinate metaphor to present the probabilistic distribution of a document across topics. Such representation allows the users to discover single-topic vs. multi-topic documents and the relative importance of each topic to a document of interest. In addition, since most text corpora are inherently temporal, parallelTopics also depicts the topic evolution over time. We have applied parallelTopics to exploring and analyzing several text corpora, including the scientific proposals awarded by the National Science Foundation and the publications in the VAST community over the years. To demonstrate the efficacy of parallelTopics, we conducted several expert evaluations, the results of which are reported in this paper.

关键词： Probabilistic logic visualization Entropy Analytical models Text analysis Semantics Text processing

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ARIES systems code development, visualization and application

ARIES systems code development, visualization and applicatio...

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ieee/NPSS symposium on Fusion Engineering

作者： Lane Carlson Mark Tillack Farrokh Najmabadi Charles Kessel Center for Energy Research University of California-San Diego La Jolla CA USA Princeton Plasma Physics Laboratory Princeton NJ USA

The ARIES research program has utilized its comprehensive ARIES systems code (ASC) and a new graphical user interface for visualizing the parameter space as important tools in its analysis of fusion power plant designs. Recently, the ASC has undergone modifications to accommodate different divertor designs, each having unique pumping powers, helium and liquid-metal pumps thermal heat recovery, and the latest material, fabrication, and costing algorithms. The modifications and changes made to the code have been documented and verified by members of the ARIES team to ensure accuracy of implementation and self-consistency of design. The code has also been modified to display a wider range of inputs/outputs, formulas, and algorithms for a greater degree of transparency and verification. After the changes to the code were completed and the version locked, the ASC has been employed to continue to scan the physics and technology operating space for relevant power plant designs. Four corners of aggressiveness and conservativeness in both physics and technology serve as the boundaries for the scans. The Visual ARIES Systems Scanning Tool (VASST) has been used in parallel with the ASC scans to visualize the tremendous amounts of data resulting from these detailed systems scans. Displaying the data in a colorful and intuitive visual environment and giving the user explorative and visual interaction has helped extract meaningful relationships and trends from the data. Initially, broad scans from the ASC and VASST indicated areas of interest where further detail was needed. Further scans with a higher degree of detail helped enhance and further refine the database. After the final scans, VASST facilitated in displaying and filtering the large database to choose two "strawmen" data points at two of the four corners of the aggressive/conservative operating space. These points then served as reference designs so more detailed design and calculations could be done. The results of th

关键词： Silicon carbide visualization Fingers Materials databases

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Tomographic performance characteristics of the IQ●SPECT system

Tomographic performance characteristics of the IQ●SPECT sys...

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ieee symposium on Nuclear Science (NSS/MIC)

作者： Ramya Rajaram Manojeet Bhattacharya Xinhong Ding Ron Malmin Trudy D. Rempel A. Hans Vija Johannes Zeintl Molecular Imaging Siemens Medical Solutions Inc. Hoffman Estates IL USA

The IQ·SPECT system was introduced by Siemens in 2010 to significantly improve the efficiency of myocardial perfusion imaging (MPI) using conventional, large field-of-view (FOV) SPECT and SPECT·CT systems. With IQ·SPECT, it is possible to perform MPI scans in one-fourth the time or using one-fourth the administered dose as compared to a standard protocol using parallel-hole collimators. This improvement is achieved by means of a proprietary multifocal collimator that rotates around the patient in a cardio-centric orbit resulting in a four-fold magnification of the heart while keeping the entire torso in the FOV. The data are reconstructed using an advanced reconstruction algorithm that incorporates measured values for gantry deflections, collimator-hole angles, and system point response function. This article explores the boundary conditions of IQ·SPECT imaging, as measured using the data Spectrum ® cardiac torso phantom with the cardiac insert. Impact on reconstructed image quality was evaluated for variations in positioning of the myocardium relative to the sweet spot, scan-arc limitations, and for low-dose imaging protocols. Reconstructed image quality was assessed visually using the INVIA 4DMSPECT and quantitatively using Siemens internal IQ assessment software. The results indicated that the IQ·SPECT system is capable of tolerating possible mispositioning of the myocardium relative to the sweet spot by the operator, and that no artifacts are introduced by the limited angle coverage. We also found from the study of multiple low dose protocols that the dwell time will need to be adjusted in order to acquire data with sufficient signal-to-noise ratio for good reconstructed image quality.

关键词： Materials Biomedical imaging Protocols Computed tomography visualization Single photon emission computed tomography

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