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Acceleration of GPU-based ultrasound simulation via data compression 28

Acceleration of GPU-based ultrasound simulation via data com...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Haigh, Andrew A. McCreath, Eric C. Australian Natl Univ Res Sch Comp Sci Canberra ACT Australia

ISBN: (纸本)9781479941162

The realistic simulation of ultrasound wave propagation is computationally intensive. The large size of the grid and low degree of reuse of data means that it places a great demand on memory bandwidth. Graphics processing Units (GPUs) have attracted attention for performing scientific calculations due to their potential for efficiently performing large numbers of floating point computations. However, many applications may be limited by memory bandwidth, especially for data sets whose size is larger than that of the GPU platform. This problem is only partially mitigated by applying the standard technique of breaking the grid into regions and overlapping the computation of one region with the host-device memory transfer of another. In this paper, we implement a memory-bound GPU-based ultrasound simulation and evaluate the use of a technique for improving performance by compressing the data into a fixed-point representation that reduces the time required for inter-host- device transfers. We demonstrate a speedup of 1.5 times on a simulation where the data is broken into regions that must be copied back and forth between the CPU and GPU. We develop a model that can be used to determine the amount of temporal blocking required to achieve near optimal performance, without extensive experimentation. This technique may also be applied to GPU-based scientific simulations in other domains such as computational fluid dynamics and electromagnetic wave simulation.

关键词： GPGPU Data compression parallel architectures Memory architecture Nonlinear acoustics

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parallel Bayesian Network Modelling for Pervasive Health Monitoring System 28

Parallel Bayesian Network Modelling for Pervasive Health Mon...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Qian, Xiujuan Wang, Yongli Jiang, Xiaohui Nanjing Univ Sci & Technol Dept Comp Sci & Engn Nanjing 210094 Jiangsu Peoples R China

ISBN: (纸本)9781479941162

Nowadays patients are experiencing pervasive health monitoring service. In order to improve the quality of service, managers and clinicians need to analyze plentiful data collected by medical information system. In this way, because they can acquire useful knowledge, wise decision will be made and the treatment and prevention will become more effective. Since Heart Disease (HD) is considered as one of the main reasons of death for adults, heart disease analysis deserves more attention. This paper uses Bayesian networks to analyze heart disease and presents a method to conform the sequence of network nodes from sample dataset. This method overcomes the limitation of traditional algorithms, which require experts of medical field give the order of network nodes. In addition, in order to shorten the analysis time, a parallel optimization technique is adopted to accelerate the establishment of HD diagnosis model over large amounts of data. Experiments show that the proposed method can improve the accuracy of the modeling and shorten the modeling time to some extent.

关键词： Heart Disease Analysis Bayesian Networks parallel Optimization

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A New parallel Algorithm for Two-Pass Connected Component Labeling 28

A New Parallel Algorithm for Two-Pass Connected Component La...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Gupta, Siddharth Palsetia, Diana Patwary, Md. Mostofa Ali Agrawal, Ankit Choudhary, Alok Northwestern Univ Dept Elect Engn & Comp Sci Evanston IL 60208 USA

ISBN: (纸本)9781479941162

Connected Component Labeling (CCL) is an important step in pattern recognition and image processing. It assigns labels to the pixels such that adjacent pixels sharing the same features are assigned the same label. Typically, CCL requires several passes over the data. We focus on two-pass technique where each pixel is given a provisional label in the first pass whereas an actual label is assigned in the second pass. We present a scalable parallel two-pass CCL algorithm, called PAREMSP, which employs a scan strategy and the best union-find technique called REMSP, which uses REM's algorithm for storing label equivalence information of pixels in a 2-D image. In the first pass, we divide the image among threads and each thread runs the scan phase along with REMSP simultaneously. In the second phase, we assign the final labels to the pixels. As REMSP is easily parallelizable, we use the parallel version of REMSP for merging the pixels on the boundary. Our experiments show the scalability of PAREMSP achieving speedups up to 20.1 using 24 cores on shared memory architecture using OpenMP for an image of size 465.20 MB. We find that our proposed parallel algorithm achieves linear scaling for a large resolution fixed problem size as the number of processing elements are increased. Additionally, the parallel algorithm does not make use of any hardware specific routines, and thus is highly portable.

关键词： CCL Image processing OpenMP Pattern Recognition Union-FInd

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Using Physical Stigmergy in Decentralized Optimization Under Multiple Non-separable Constraints: Formal Methods and an Intelligent Lighting Example 28

Using Physical Stigmergy in Decentralized Optimization Under...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Pavlic, Theodore P. Arizona State Univ Sch Life Sci Tempe AZ 85287 USA

ISBN: (纸本)9781479941162

In this paper, a distributed asynchronous algorithm for intelligent lighting is presented that minimizes collective power use while meeting multiple user lighting constraints simultaneously and requires very little communication among agents participating in the distributed computation. Consequently, the approach is arbitrarily scalable, adapts to exogenous disturbances, and is robust to failures of individual agents. This algorithm is an example of a decentralized primal-space algorithm for constrained non-linear optimization that achieves coordination between agents using stigmergic memory cues present in the physical system as opposed to explicit communication and synchronization. Not only does this work make of stigmergy, a property first used to describe decentralized decision making in eusocial insects, but details of the algorithm are inspired by classic social foraging theory and more recent results in eusocial-insect macronutrient regulation. This theoretical analysis in this paper guarantees that the decentralized stigmergically coupled system converges to within a finite neighborhood of the optimal resource allocation. These results are validated using a hardware implementation of the algorithm in a small-scale intelligent lighting scenario. There are other real-time distributed resource allocation applications that are amenable to these methods, like distributed power generation;in general, this paper means to provide proof of concept that physical variables in cyberphysical systems can be leveraged to reduce the communication burden of algorithms.

关键词： Optimization algorithms Resource allocation Pareto optimality Constrained optimization Intelligent lighting Bioinspiration Agents and autonomous systems Decentralized control distributed optimization Stigmergy

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Machine-Learning-Based Identification of Defect Patterns in Semiconductor Wafer Maps: An Overview and Proposal 28

Machine-Learning-Based Identification of Defect Patterns in ...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Adly, Fatima Yoo, Paul D. Muhaidat, Sami Al-Hammadi, Yousof Khalifa Univ Dept ECE Abu Dhabi U Arab Emirates Univ Sydney Ctr Distributed & High Performance Comp J12 Sydney NSW 2006 Australia

ISBN: (纸本)9781479941162

Wafers are formed from very thin layers of a semiconductor material;hence, they are highly susceptible to various kinds of defects. The defects are most likely to occur during the lengthy and complex fabrication process, which can include hundreds of steps. Wafer defects are generally caused by machine inaccuracy, chemical stains, physical damages, human mistakes, and atmospheric conditions. The defective chips tend to have several unique spatial patterns across the wafer, namely ring, spot, repetitive and cluster patterns. To locate such defect patterns, wafer maps are used to visualize and ultimately lead to better understanding of what happened during the process failure. To identify the unique patterns of defects and to find the point of manufacturing process that causes such defects accurately, nature-inspired model-free machine-learning techniques have been well accepted. This paper thus reviews the theoretical and experimental literature of such models with a focus on model learnability and efficiency-related issues involving data reduction and transformation techniques, which could be seen as the key model properties to deal with big data applications.

关键词： wafer defect patterns wafer map nature-inspired machine-learning and classification

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A General Model Checking Framework for Various Memory Consistency Models 28

A General Model Checking Framework for Various Memory Consis...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Abe, Tatsuya Maeda, Toshiyuki RIKEN Adv Inst Computat Sci Kobe Hyogo Japan

ISBN: (纸本)9781479941162

Relaxed memory consistency models are common and essential when multiple processes share a single global address space, such as when using multicore CPUs, partitioned global address space languages, and so forth. Programming within these models is difficult and error prone, because of non-intuitive behaviors that could not occur in a sequential memory consistency model. In addition, because the memory consistency models vary from language to language, and CPU to CPU, a program which may work correctly on one system may not work on another. To address the problem, this paper describes a model checking framework in which users are able to check their programs under various memory consistency models. More specifically, our framework provides a base model that exhibits very relaxed behaviors, and users are able to define various consistency models by adding constraints to the base model. This paper also describes a prototype implementation of a model checker based on the proposed framework. We have specified the necessary constraints for three practical existing memory consistency models (UPC, Coarray Fortran, and Itanium). Our model checker verified some example programs correctly, and confirmed the expected differences among the three models.

关键词： Memory consistency model Model checking Unified parallel C Coarray Fortran Itanium

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Scalable System Environment Caching and Sharing for distributed Virtual Machines 28

Scalable System Environment Caching and Sharing for Distribu...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Long, Teng Yoon, Ilchul Sussman, Alan Porter, Adam Memon, Atif Univ Maryland Dept Comp Sci College Pk MD 20742 USA State Univ New York Dept Comp Sci Incheon South Korea

ISBN: (纸本)9781479941162

Virtual machines have become very widely used in many software development communities. Developers can conveniently provision specific machine configurations using VMs, and those VMs can contain operating systems, libraries, and other applications required to build and execute their software under development. However, the size of full VM images and network bandwidth limitations makes large-scale reuse of VMs among distributed groups of developers extremely difficult. In this paper we address the problem of provisioning software configurations realized as virtual machine images rapidly and incrementally from a set of pristine VM states, by caching and sharing configuration fragments between developer groups. We first formally model the entire configuration space that might be cached and shared between groups, describe the design of our infrastructure to incrementally provision configurations from its fragments, and finally evaluate the performance of our approach with an example scenario common in software testing. Our experimental results show that our approach can help developers reduce the time and resource requirements for provisioning software configurations.

关键词： Software testing

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Topology-aware Optimization of Communications for parallel Matrix Multiplication on Hierarchical Heterogeneous HPC Platforms 28

Topology-aware Optimization of Communications for Parallel M...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Malik, Tania Rychkov, Vladimir Lastovetsky, Alexey Quintin, Jean-Noel Univ Coll Dublin Sch Comp Sci & Informat Dublin 4 Ireland Bull SAS Extreme Comp R&D Paris France

ISBN: (纸本)9781479941162

Communications on hierarchical heterogeneous HPC platforms can be optimized based on topology information. For MPI, as a major programming tool for such platforms, a number of topology-aware implementations of collective operations have been proposed for optimal scheduling of messages. This approach improves communication performance and does not require to modify application source code. However, it is applicable to collective operations only and does not affect the parts of the application that are based on point-to-point exchanges. In this paper, we address the problem of efficient execution of data-parallel applications on interconnected clusters and present a topology-aware optimization that improves data partition by taking into account the entire communication flow of the application. This approach is also non-intrusive to the source code but application-specific. For illustration, we use parallel matrix multiplication, where the matrices are partitioned into irregular 2D rectangles assigned to different processors and arranged in columns, and the processors communicate over this partitioning vertically and horizontally. By rearranging the rectangles, we can minimize communications between different levels of the network hierarchy. Finding the optimal arrangement is NP-complete, therefore, we propose a heuristic based on evaluation of the communication flow on the given topology. We demonstrate the correctness and efficiency of the proposed approach by experimental results on multicore nodes and interconnected heterogeneous clusters.

关键词： heterogeneous clusters topology-aware communications data partitioning matrix multiplication

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Efficient Computation of the Phylogenetic Likelihood Function on the Intel MIC Architecture 28

Efficient Computation of the Phylogenetic Likelihood Functio...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Kozlov, Alexey M. Goll, Christian Stamatakis, Alexandros Heidelberg Inst Theoret Studies Sci Comp Grp Exelixis Lab Heidelberg Germany Karlsruhe Inst Technol Inst Theoret Informat D-76128 Karlsruhe Germany

ISBN: (纸本)9781479941162

Phylogenetic inference is the process of reconstructing the evolutionary history of species based on their traits, nowadays mostly using molecular sequence data. Current state-of-the-art inference methods, like Bayesian and Maximum Likelihood (ML) inference, rely on the Phylogenetic Likelihood Function (PLF) as their computational core. Due to the large number of floating-point operations involved, the PLF evaluation is the major bottleneck for large-scale phylogenetic analyses comprising thousands of genes or even whole genomes. Here, we describe an optimized implementation of the PLF kernel for the novel Intel Many Integrated Core (MIC) architecture. Using a MIC-based accelerator (Xeon Phi 5110P), we were able to achieve speedups ranging from 1.9x to 2.8x for different PLF kernels, compared to a highly optimized AVX implementation running on dual-socket Xeon E5-2680 system. By integrating the optimized PLF into the phylogenetic inference program RAxML-Light, we reduced the overall execution times by up to factor of two. To assess the scalability on multiple Xeon Phi cards, we also developed a hybrid MPI-OpenMP version of the ExaML code. When ExaML is executed on two coprocessors on the same node, we obtain speedups of up to a factor of 3.7 (vs. a CPU baseline) and 1.8 (vs. a single MIC). As expected, speedups increase with growing dataset size and become stable for alignments that require processing 1-2 million sites per MIC card.

关键词： bioinformatics phylogenetics maximum likelihood Intel MIC parallel processing MPI

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Construction of Porous Networks subjected to Geometric Restrictions by using OpenMP 28

Construction of Porous Networks subjected to Geometric Restr...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Gonzalez-Mendez, A. Roman-Alonso, G. Rojas-Gonzalez, F. Castro-Garcia, M. A. Aguilar-Cornejo, M. Cordero-Sanchez, S. Univ Autonoma Metropolitana Izt Dept Elect Engn Iztapalapa CDMX Mexico Univ Autonoma Metropolitana Izt Dept Chem Iztapalapa CDMX Mexico

ISBN: (纸本)9781479941162

The study of porous materials involves great importance for a vast number of industrial applications. In order to study some specific characteristics of materials, in-silico simulations can be employed. The particular simulation of pore networks described in this work finds its basis in the Dual Site-Bond Model (DSBM). Under this approach, a porous material is thought to be made of sites (cavities, bulges) interconnected to each other through bonds (throats, capillaries);while every site is connected to a number of bonds each bond is the link between two sites. At present, several computing algorithms have been implemented for the simulation of pore networks;nevertheless, only a few of these methods take into account the geometric restrictions that arise during the interconnection of a set of bonds to every site of the network. It is likely that introducing restrictions of this sort in the computing algorithms would lead to the implementation of more realistic pore networks. In this work, a sequential algorithm and its parallel computing version are proposed to construct pore networks, allowing geometrical restrictions among hollow entities. Our parallel approach uses OpenMP to create a set of threads (computing tasks) that work simultaneously on independent and random pore network regions. We discuss the obtained results.

关键词： Porous Networks parallel Computing Dual Site-Bond Model Multi-Core Programming OpenMP

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