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Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Parallel computing paradigm"

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Gorodnyaya, Lidia. "FUNCTIONAL PROGRAMMING FOR PARALLEL COMPUTING." Bulletin of the Novosibirsk Computing Center. Series: Computer Science, no. 45 (2021): 29–48. http://dx.doi.org/10.31144/bncc.cs.2542-1972.2021.n45.p29-48.

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The paper is devoted to modern trends in the application of functional programming to the problems of organizing parallel computations. Functional programming is considered as a meta-paradigm for solving the problems of developing multi-threaded programs for multiprocessor complexes and distributed systems, as well as for solving the problems associated with rapid IT development. The semantic and pragmatic principles of functional programming and consequences of these principles are described. The paradigm analysis of programming languages and systems is used, which allows assessing their similarities and differences. Taking into account these features is necessary when predicting the course of application processes, as well as when planning the study and organization of program development. There are reasons to believe that functional programming is capable of improving program performance through its adaptability to modeling and prototyping. A variety of features and characteristics inherent in the development and debugging of long-lived parallel computing programs is shown. The author emphasizes the prospects of functional programming as a universal technique for solving complex problems burdened with difficult to verify and poorly compatible requirements. A brief outline of the requirements for a multiparadigm parallel programming language is given.
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2

Zmejev, D. N., and N. N. Levchenko. "Aspects of Creating Parallel Programs in Dataflow Programming Paradigm." Informacionnye Tehnologii 28, no. 11 (November 17, 2022): 597–606. http://dx.doi.org/10.17587/it.28.597-606.

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The imperative programming paradigm is the main one for creating sequential and parallel programs for the vast majority of modern computers, including supercomputers. A feature of the imperative paradigm is the sequence of commands. This feature is an obstacle to the creation of efficient parallel programs, since parallelism is achieved at the expense of additional code. One of the solutions to the problem of overhead for parallel computing is the creation of such a computing model and the architecture of the system that implements it, for which the parallel execution of the algorithm is an immanent property. This model is a dataflow computing model with a dynamically formed context and the architecture of the parallel dataflow computing system "Buran". A complete transition to dataflow systems is hampered, among other things, by the conceptual difference between the dataflow programming paradigm and the imperative one. The article compares these two paradigms. First, parallel data processing is an inherent property of a dataflow program. Second, the dataflow program consists of three elements: a set of initial data, a program code, and a parameterizable distribution function. And third, a conceptually different approach to the algorithmization of the task — the data themselves store information about who should process them (in traditional programs, on the contrary, the command stores information about what data should be processed). The article also presents the structure of a dataflow program and the route for creating a dataflow algorithm. The translation of basic algorithmic constructions (following, branching, loops) is considered on the example of simple problems.
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3

Wang, Nen-Zi, and Hsin-Yi Chen. "A cross-platform parallel programming model for fluid-film lubrication optimization." Industrial Lubrication and Tribology 70, no. 6 (August 13, 2018): 1002–11. http://dx.doi.org/10.1108/ilt-11-2016-0283.

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Purpose A cross-platform paradigm (computing model), which combines the graphical user interface of MATLAB and parallel Fortran programming, for fluid-film lubrication analysis is proposed. The purpose of this paper is to take the advantages of effective multithreaded computing of OpenMP and MATLAB’s user-friendly interface and real-time display capability. Design/methodology/approach A validation of computing performance of MATLAB and Fortran coding for solving two simple sliders by iterative solution methods is conducted. The online display of the particles’ search process is incorporated in the MATLAB coding, and the execution of the air foil bearing optimum design is conducted by using OpenMP multithreaded computing in the background. The optimization analysis is conducted by particle swarm optimization method for an air foil bearing design. Findings It is found that the MATLAB programs require prolonged execution times than those by using Fortran computing in iterative methods. The execution time of the air foil bearing optimum design is significantly minimized by using the OpenMP computing. As a result, the cross-platform paradigm can provide a useful graphical user interface. And very little code rewritting of the original numerical models is required, which is usually optimized for either serial or parallel computing. Research limitations/implications Iterative methods are commonly applied in fluid-film lubrication analyses. In this study, iterative methods are used as the solution methods, which may not be an effective way to compute in the MATLAB’s setting. Originality/value In this study, a cross-platform paradigm consisting of a standalone MATLAB and Fortran codes is proposed. The approach combines the best of the two paradigms and each coding can be modified or maintained independently for different applications.
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Lohani, Bhanu Prakash, Vimal Bibhu, and Ajit Singh. "Review of Evolutionary Algorithms based on parallel computing paradigm." International Journal of Computer Science and Engineering 4, no. 6 (June 25, 2017): 1–4. http://dx.doi.org/10.14445/23488387/ijcse-v4i6p101.

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Zhao, Jin, Fan, Song, Zhou, and Jiang. "High-performance Overlay Analysis of Massive Geographic Polygons That Considers Shape Complexity in a Cloud Environment." ISPRS International Journal of Geo-Information 8, no. 7 (June 26, 2019): 290. http://dx.doi.org/10.3390/ijgi8070290.

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: Overlay analysis is a common task in geographic computing that is widely used in geographic information systems, computer graphics, and computer science. With the breakthroughs in Earth observation technologies, particularly the emergence of high-resolution satellite remote-sensing technology, geographic data have demonstrated explosive growth. The overlay analysis of massive and complex geographic data has become a computationally intensive task. Distributed parallel processing in a cloud environment provides an efficient solution to this problem. The cloud computing paradigm represented by Spark has become the standard for massive data processing in the industry and academia due to its large-scale and low-latency characteristics. The cloud computing paradigm has attracted further attention for the purpose of solving the overlay analysis of massive data. These studies mainly focus on how to implement parallel overlay analysis in a cloud computing paradigm but pay less attention to the impact of spatial data graphics complexity on parallel computing efficiency, especially the data skew caused by the difference in the graphic complexity. Geographic polygons often have complex graphical structures, such as many vertices, composite structures including holes and islands. When the Spark paradigm is used to solve the overlay analysis of massive geographic polygons, its calculation efficiency is closely related to factors such as data organization and algorithm design. Considering the influence of the shape complexity of polygons on the performance of overlay analysis, we design and implement a parallel processing algorithm based on the Spark paradigm in this paper. Based on the analysis of the shape complexity of polygons, the overlay analysis speed is improved via reasonable data partition, distributed spatial index, a minimum boundary rectangular filter and other optimization processes, and the high speed and parallel efficiency are maintained.
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6

Yu, Qiu Dong, Yun Chen Tian, and Xu Feng Hua. "Research on Security of Agricultural Information Model Based on Cloud Computing." Applied Mechanics and Materials 687-691 (November 2014): 1970–73. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1970.

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In 2007, as a new computing paradigm, Cloud Computing go into people's sight. It is a technology that develop with the parallel computing, distributed computing, utility computing, a new computing paradigm and the emergence of grid computing development. It is also the result of network storage, virtualization and load balancing development. As an Internet-based super computing paradigm, cloud computing allows users to dynamically share the hardware, software, and data resources. In the process of sharing resources, it is inevitable to involve security issues of network transmission. In order to solve the security problems of network data integration cloud computing facing agricultural resources, this study proposes a network security model which can be proved to be much useful in the near future.
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7

Sbalzarini, Ivo F. "Abstractions and Middleware for Petascale Computing and Beyond." International Journal of Distributed Systems and Technologies 1, no. 2 (April 2010): 40–56. http://dx.doi.org/10.4018/jdst.2010040103.

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As high-performance computing moves to the petascale and beyond, a number of algorithmic and software challenges need to be addressed. This paper reviews the main performance-limiting factors in today’s high-performance computing software and outlines a possible new programming paradigm to address them. The proposed paradigm is based on abstract parallel data structures and operations that encapsulate much of the complexity of an application, but still make communication overhead explicit. The authors argue that all numerical simulations can be formulated in terms of the presented abstractions, which thus define an abstract semantic specification language for parallel numerical simulations. Simulations defined in this language can automatically be translated to source code containing the appropriate calls to a middleware that implements the underlying abstractions. Finally, the structure and functionality of such a middleware are outlined while demonstrating its feasibility on the example of the parallel particle-mesh library (PPM).
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8

LIN, RONG, STEPHAN OLARIU, JAMES L. SCHWING, and JINGYUAN ZHANG. "COMPUTING ON RECONFIGURABLE BUSES—A NEW COMPUTATIONAL PARADIGM." Parallel Processing Letters 04, no. 04 (December 1994): 465–76. http://dx.doi.org/10.1142/s0129626494000430.

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Up to now, buses have been used exclusively to ferry data around. The contribution of this work is to show that buses can be used both as topological descriptors and as powerful computational devices. We illustrate the power of this paradigm by designing two fast algorithms for image segmentation and parallel visibility. Our algorithm for image segmentation uses a novel technique invol ving building a bus around every region of interest in the image. With a binary image pretiled in the natural way on a reconfigurable mesh of size N×N our segmentation algorithm runs in O( log N) time, improving by a factor of O( log N) over the state of the art. Next, we exhibit a very simple algorithm to solve the parallel visibility problem on an image of size N×N. Our algorithm runs in O( log N) time. The only previously-known algorithm for this problem runs in O( log N) time on a hypercube with N processors. To support these algorithms, a set of basic building blocks are developed which are of independent interest. These include solutions to the following problems on a bus on length N: (1) computing the prefix maxima of items stored by the processors on the bus, even if none of the processors knows its rank on the bus; (2) computing the rank of every processor on the bus; (3) electing a leader on a closed bus.
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9

Moreno Escobar, Jesús Jaime, Oswaldo Morales Matamoros, Ricardo Tejeida Padilla, Liliana Chanona Hernández, Juan Pablo Francisco Posadas Durán, Ana Karen Pérez Martínez, Ixchel Lina Reyes, and Hugo Quintana Espinosa. "Biomedical Signal Acquisition Using Sensors under the Paradigm of Parallel Computing." Sensors 20, no. 23 (December 7, 2020): 6991. http://dx.doi.org/10.3390/s20236991.

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There are several pathologies attacking the central nervous system and diverse therapies for each specific disease. These therapies seek as far as possible to minimize or offset the consequences caused by these types of pathologies and disorders in the patient. Therefore, comprehensive neurological care has been performed by neurorehabilitation therapies, to improve the patients’ life quality and facilitating their performance in society. One way to know how the neurorehabilitation therapies contribute to help patients is by measuring changes in their brain activity by means of electroencephalograms (EEG). EEG data-processing applications have been used in neuroscience research to be highly computing- and data-intensive. Our proposal is an integrated system of Electroencephalographic, Electrocardiographic, Bioacoustic, and Digital Image Acquisition Analysis to provide neuroscience experts with tools to estimate the efficiency of a great variety of therapies. The three main axes of this proposal are: parallel or distributed capture, filtering and adaptation of biomedical signals, and synchronization in real epochs of sampling. Thus, the present proposal underlies a general system, whose main objective is to be a wireless benchmark in the field. In this way, this proposal could acquire and give some analysis tools for biomedical signals used for measuring brain interactions when it is stimulated by an external system during therapies, for example. Therefore, this system supports extreme environmental conditions, when necessary, which broadens the spectrum of its applications. In addition, in this proposal sensors could be added or eliminated depending on the needs of the research, generating a wide range of configuration limited by the number of CPU cores, i.e., the more biosensors, the more CPU cores will be required. To validate the proposed integrated system, it is used in a Dolphin-Assisted Therapy in patients with Infantile Cerebral Palsy and Obsessive–Compulsive Disorder, as well as with a neurotypical one. Event synchronization of sample periods helped isolate the same therapy stimulus and allowed it to be analyzed by tools such as the Power Spectrum or the Fractal Geometry.
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Joshi, R. K., and D. J. Ram. "Anonymous remote computing: a paradigm for parallel programming on interconnected workstations." IEEE Transactions on Software Engineering 25, no. 1 (1999): 75–90. http://dx.doi.org/10.1109/32.748919.

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Дисертації з теми "Parallel computing paradigm"

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Li, Xiaofeng. "A parallel computing paradigm for transcription network construction from microarray data /." Available to subscribers only, 2007. http://proquest.umi.com/pqdweb?did=1483473751&sid=22&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Chantamas, Wittaya. "A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm." Kent State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=kent1259610266.

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Hodaňová, Andrea. "Využití funkcionálních jazyků pro hardwarovou akceleraci." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236231.

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The aim of this thesis is to research how the functional paradigm can be used for hardware acceleration with an emphasis on data-parallel tasks. The level of abstraction of the traditional hardware description languages, such as VHDL or Verilog, is becoming to low. High-level languages from the domains of software development and modeling, such as C/C++, SystemC or MATLAB, are experiencing a boom for hardware description on the algorithmic or behavioral level. Functional Languages are not so commonly used, but they outperform imperative languages in verification, the ability to capture inherent paralellism and the compactness of code. Data-parallel task are often accelerated on FPGAs, GPUs and multicore processors. In this thesis, we use a library for general-purpose GPU programs called Accelerate and extend it to produce VHDL. Accelerate is a domain-specific language embedded into Haskell with a backend for the NVIDIA CUDA platform. We use the language and its frontend, and create a new backend for high-level synthesis of circuits in VHDL.
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Van, Huyssteen Salomon Stephanus. "Parallel paradigms in optimal structural design." Thesis, Stellenbosch : Stellenbosch University, 2011. http://hdl.handle.net/10019.1/18017.

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Thesis (MScEng)--Stellenbosch University, 2011.
ENGLISH ABSTRACT: Modern-day processors are not getting any faster. Due to the power consumption limit of frequency scaling, parallel processing is increasingly being used to decrease computation time. In this thesis, several parallel paradigms are used to improve the performance of commonly serial SAO programs. Four novelties are discussed: First, replacing double precision solvers with single precision solvers. This is attempted in order to take advantage of the anticipated factor 2 speed increase that single precision computations have over that of double precision computations. However, single precision routines present unpredictable performance characteristics and struggle to converge to required accuracies, which is unfavourable for optimization solvers. Second, QP and dual are statements pitted against one another in a parallel environment. This is done because it is not always easy to see which is best a priori. Therefore both are started in parallel and the competing threads are cancelled as soon as one returns a valid point. Parallel QP vs. dual statements prove to be very attractive, converging within the minimum number of outer iterations. The most appropriate solver is selected as the problem properties change during the iteration steps. Thread cancellation poses problems caused by threads having to wait to arrive at appropriate checkpoints, thus su ering from unnecessarily long wait times because of struggling competing routines. Third, multiple global searches are started in parallel on a shared memory system. Problems see a speed increase of nearly 4x for all problems. Dynamically scheduled threads alleviate the need for set thread amounts, as in message passing implementations. Lastly, the replacement of existing matrix-vector multiplication routines with optimized BLAS routines, especially BLAS routines targeted at GPGPU technologies (graphics processing units), proves to be superior when solving large matrix-vector products in an iterative environment. These problems scale well within the hardware capabilities and speedups of up to 36x are recorded.
AFRIKAANSE OPSOMMING: Hedendaagse verwerkers word nie vinniger nie as gevolg van kragverbruikingslimiet soos die verwerkerfrekwensie op-skaal. Parallelle prosesseering word dus meer dikwels gebruik om berekeningstyd te laat daal. Verskeie parallelle paradigmas word gebruik om die prestasie van algemeen sekwensiële optimeringsprogramme te verbeter. Vier ontwikkelinge word bespreek: Eerste, is die vervanging van dubbel presisie roetines met enkel presisie roetines. Dit poog om voordeel te trek uit die faktor 2 spoed verbetering wat enkele presisie berekeninge het oor dubbel presisie berekeninge. Enkele presisie roetines is onvoorspelbaar en sukkel in meeste gevalle om die korrekte akkuraatheid te vind. Tweedens word QP teen duale algoritmes in ’n parallel omgewing gebruik. Omdat dit nie altyd voor die tyd maklik is om te sien watter een die beste gaan presteer nie, word almal in parallel begin en die mededingers word dan gekanselleer sodra een terugkeer met ’n geldige KKT punt. Parallele QP teen duale algoritmes blyk om baie aantreklik te wees. Konvergensie gebeur in alle gevalle binne die minimum aantal iterasies. Die mees geskikte algoritme word op elke iterasie gebruik soos die probleem eienskappe verander gedurende die iterasie stappe. “Thread” kanseleering hou probleme in en word veroorsaak deur “threads” wat moet wag om die kontrolepunte te bereik, dus ly die beste roetines onnodig as gevolg van meededinger roetines was sukkel. Derdens, verskeie globale optimerings word in parallel op ’n “shared memory” stelsel begin. Probleme bekom ’n spoed verhoging van byna vier maal vir alle probleme. Dinamiese geskeduleerde “threads” verlig die behoefte aan voorafbepaalde “threads” soos gebruik word in die “message passing” implementerings. Laastens is die vervanging van die bestaande matriks-vektor vermenigvuldiging roetines met geoptimeerde BLAS roetines, veral BLAS roetines wat gerig is op GPGPU tegnologië. Die GPU roetines bewys om superieur te wees wanneer die oplossing van groot matrix-vektor produkte in ’n iteratiewe omgewing gebruik word. Hierdie probleme skaal ook goed binne die hardeware se vermoëns, vir die grootste probleme wat getoets word, word ’n versnelling van 36 maal bereik.
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5

Fernandez, Héctor. "Coordination flexible fondée sur la métaphore chimique dans les infrastructures de services." Phd thesis, Université Rennes 1, 2012. http://tel.archives-ouvertes.fr/tel-00717057.

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Avec le développement de l'Internet des services, composer dynamiquement des services distribués faiblement couplés est devenu le nouveau challenge du calcul à large échelle. Alors que la composition de services est devenue un élément clef des plates-formes orientées service, les systèmes de composition de services suivent pour la plupart une approche centralisée connaissant l'ensemble des informations de flux de contrôle et de données du workflow, posant un certain nombre de problèmes, notamment de passage à l'échelle et de fiabilité. Dans un monde où les plates-formes sont de plus en plus dynamiques, de nouveaux mécanismes de coordination dynamiques sont requis. Dans ce contexte, des métaphores naturelles, et en particulier la méthapore chimique, ont gagné une attention particulière récemment, car elles fournissent des abstractions pour une coordination flexible d'entités. Dans cette thèse, nous présentons un système de gestion de workflow fondée sur la métaphore chimique, qui fournit un modèle d'exécution haut-niveau pour l'exécution centralisée et décentralisée de compositions (ou workflows). Selon ce modèle, les services sont vus comme des molécules qui flottent dans une solution chimique. La coordination de ces services est effectuée par un ensemble de réactions entre ces molécules exprimant l'exécution décentralisée d'un workflow. Par ailleurs, si le paradigme chimique est aujourd'hui considéré comme un modèle de coordination prometteur, il manque des résultats expérimentaux. Ainsi, nous avons développé un prototype logiciel. Des expériences ont été menées avec des workflows d'applications réelles pour montrer la viabilité de notre modèle.
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6

(11132985), Thamir Qadah. "High-performant, Replicated, Queue-oriented Transaction Processing Systems on Modern Computing Infrastructures." Thesis, 2021.

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With the shifting landscape of computing hardware architectures and the emergence of new computing environments (e.g., large main-memory systems, hundreds of CPUs, distributed and virtualized cloud-based resources), state-of-the-art designs of transaction processing systems that rely on conventional wisdom suffer from lost performance optimization opportunities. This dissertation challenges conventional wisdom to rethink the design and implementation of transaction processing systems for modern computing environments.

We start by tackling the vertical hardware scaling challenge, and propose a deterministic approach to transaction processing on emerging multi-sockets, many-core, shared memory architecture to harness its unprecedented available parallelism. Our proposed priority-based queue-oriented transaction processing architecture eliminates the transaction contention footprint and uses speculative execution to improve the throughput of centralized deterministic transaction processing systems. We build QueCC and demonstrate up to two orders of magnitude better performance over the state-of-the-art.

We further tackle the horizontal scaling challenge and propose a distributed queue-oriented transaction processing engine that relies on queue-oriented communication to eliminate the traditional overhead of commitment protocols for multi-partition transactions. We build Q-Store, and demonstrate up to 22x improvement in system throughput over the state-of-the-art deterministic transaction processing systems.

Finally, we propose a generalized framework for designing distributed and replicated deterministic transaction processing systems. We introduce the concept of speculative replication to hide the latency overhead of replication. We prototype the speculative replication protocol in QR-Store and perform an extensive experimental evaluation using standard benchmarks. We show that QR-Store can achieve a throughput of 1.9 million replicated transactions per second in under 200 milliseconds and a replication overhead of 8%-25%compared to non-replicated configurations.
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Mishra, Ashirbad. "Efficient betweenness Centrality Computations on Hybrid CPU-GPU Systems." Thesis, 2016. http://hdl.handle.net/2005/2718.

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Analysis of networks is quite interesting, because they can be interpreted for several purposes. Various features require different metrics to measure and interpret them. Measuring the relative importance of each vertex in a network is one of the most fundamental building blocks in network analysis. Between’s Centrality (BC) is one such metric that plays a key role in many real world applications. BC is an important graph analytics application for large-scale graphs. However it is one of the most computationally intensive kernels to execute, and measuring centrality in billion-scale graphs is quite challenging. While there are several existing e orts towards parallelizing BC algorithms on multi-core CPUs and many-core GPUs, in this work, we propose a novel ne-grained CPU-GPU hybrid algorithm that partitions a graph into two partitions, one each for CPU and GPU. Our method performs BC computations for the graph on both the CPU and GPU resources simultaneously, resulting in a very small number of CPU-GPU synchronizations, hence taking less time for communications. The BC algorithm consists of two phases, the forward phase and the backward phase. In the forward phase, we initially and the paths that are needed by either partitions, after which each partition is executed on each processor in an asynchronous manner. We initially compute border matrices for each partition which stores the relative distances between each pair of border vertex in a partition. The matrices are used in the forward phase calculations of all the sources. In this way, our hybrid BC algorithm leverages the multi-source property inherent in the BC problem. We present proof of correctness and the bounds for the number of iterations for each source. We also perform a novel hybrid and asynchronous backward phase, in which each partition communicates with the other only when there is a path that crosses the partition, hence it performs minimal CPU-GPU synchronizations. We use a variety of implementations for our work, like node-based and edge based parallelism, which includes data-driven and topology based techniques. In the implementation we show that our method also works using variable partitioning technique. The technique partitions the graph into unequal parts accounting for the processing power of each processor. Our implementations achieve almost equal percentage of utilization on both the processors due to the technique. For large scale graphs, the size of the border matrix also becomes large, hence to accommodate the matrix we present various techniques. The techniques use the properties inherent in the shortest path problem for reduction. We mention the drawbacks of performing shortest path computations on a large scale and also provide various solutions to it. Evaluations using a large number of graphs with different characteristics show that our hybrid approach without variable partitioning and border matrix reduction gives 67% improvement in performance, and 64-98.5% less CPU-GPU communications than the state of art hybrid algorithm based on the popular Bulk Synchronous Paradigm (BSP) approach implemented in TOTEM. This shows our algorithm's strength which reduces the need for larger synchronizations. Implementing variable partitioning, border matrix reduction and backward phase optimizations on our hybrid algorithm provides up to 10x speedup. We compare our optimized implementation, with CPU and GPU standalone codes based on our forward phase and backward phase kernels, and show around 2-8x speedup over the CPU-only code and can accommodate large graphs that cannot be accommodated in the GPU-only code. We also show that our method`s performance is competitive to the state of art multi-core CPU and performs 40-52% better than GPU implementations, on large graphs. We show the drawbacks of CPU and GPU only implementations and try to motivate the reader about the challenges that graph algorithms face in large scale computing, suggesting that a hybrid or distributed way of approaching the problem is a better way of overcoming the hurdles.
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Книги з теми "Parallel computing paradigm"

1

Associative computing: A programming paradigm for massively parallel computers. New York: Plenum Press, 1992.

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2

Tianruo, Yang Laurence, and Guo Minyi, eds. High performance computing: Paradigm and infrastructure. Hoboken, N.J: J. Wiley, 2005.

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3

Potter, Jerry L. Associative Computing: A Programming Paradigm for Massively Parallel Computers. Boston, MA: Springer US, 1992.

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4

Fault tolerance for multicomputers: The application-oriented paradigm. Norwood, N.J: Ablex Pub., 1997.

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5

Sørevik, Tor, Fredrik Manne, Assefaw Hadish Gebremedhin, and Randi Moe, eds. Applied Parallel Computing. New Paradigms for HPC in Industry and Academia. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-70734-4.

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6

Leopold, Claudia. Parallel and distributed computing: A survey of models, paradigms, and approaches. New York: Wiley, 2001.

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David, Kramer, Weiss Jan-Philipp, and SpringerLink (Online service), eds. Facing the Multicore - Challenge II: Aspects of New Paradigms and Technologies in Parallel Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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8

Keller, Rainer. Facing the Multicore-Challenge III: Aspects of New Paradigms and Technologies in Parallel Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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9

Yang, Laurence T., and Minyi Guo. High-Performance Computing: Paradigm and Infrastructure. Wiley & Sons, Incorporated, John, 2008.

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Yang, Laurence T., and Minyi Guo. High-Performance Computing : Paradigm and Infrastructure. Wiley-Interscience, 2005.

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Частини книг з теми "Parallel computing paradigm"

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Kapsalis, A., G. D. Smith, and V. J. Rayward-Smith. "A unified paradigm for parallel Genetic Algorithms." In Evolutionary Computing, 131–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58483-8_11.

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Baumann, Ronald, Christian Engelmann, and Al Geist. "A Parallel Plug-In Programming Paradigm." In High Performance Computing and Communications, 823–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11847366_85.

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Rauber, Thomas, Gudula Rünger, and Reinhard Wilhelm. "An application specific parallel programming paradigm." In High-Performance Computing and Networking, 735–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0046708.

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Aversa, Rocco, Marco Avvenuti, Antonio Cuomo, Beniamino Di Martino, Giuseppe Di Modica, Salvatore Distefano, Antonio Puliafito, et al. "The Cloud@Home Project: Towards a New Enhanced Computing Paradigm." In Euro-Par 2010 Parallel Processing Workshops, 555–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21878-1_68.

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Chakravorty, Sayantan, Aaron Becker, Terry Wilmarth, and Laxmikant Kalé. "A Case Study in Tightly Coupled Multi-paradigm Parallel Programming." In Languages and Compilers for Parallel Computing, 279–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89740-8_19.

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Nazareth, J. L. "Multialgorithms for Parallel Computing: A New Paradigm for Optimization." In Applied Optimization, 183–222. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-6594-6_10.

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Cheatham, Thomas, Amr Fahmy, Dan Stefanescu, and Leslie Valiant. "Bulk Synchronous Parallel Computing — A Paradigm for Transportable Software." In Tools and Environments for Parallel and Distributed Systems, 61–76. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4123-3_4.

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Liu, Hui, and Minglu Li. "Paradigm of Multiparty Joint Authentication: Evolving Towards Trust Aware Grid Computing." In Parallel and Distributed Processing and Applications, 474–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30566-8_57.

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Bruggeman, Carl, and R. Kent Dybvig. "A new architecture design paradigm for parallel computing in scheme." In Lecture Notes in Computer Science, 362–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/bfb0018665.

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Gómez-Cárdenas, Alejandro, Xavi Masip-Bruin, Eva Marín-Tordera, Sarang Kahvazadeh, and Jordi Garcia. "A Hash-Based Naming Strategy for the Fog-to-Cloud Computing Paradigm." In Euro-Par 2017: Parallel Processing Workshops, 316–24. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75178-8_26.

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Тези доповідей конференцій з теми "Parallel computing paradigm"

1

Awatsuji, Yasuhiro, Jun Tanida, and Yoshiki Ichioka. "Evaluations of Optical Parallel Digital Discrete Correlators." In Optics in Computing. Washington, D.C.: Optica Publishing Group, 1997. http://dx.doi.org/10.1364/oc.1997.otue.6.

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Анотація:
Optical computing is a powerful information processing paradigm for massively data owing to attractive features of light such as parallelism, flexible connectivity, high density connectivity. Digital optical computing is most promising because of accuracy and processing flexibility. Several paradigm of digital optical computing have been proposed. [1-4]. These paradigms can provide space-invariant logical operations for digital and discrete image in parallel. In processing sequences of the paradigms, digital discrete correlation is considered as an essential operation. Efficiency of optical parallel digital discrete correlator (OPDDC) determines that of optical digital computing system. Although a lot of implementation have been presented, there are few systematic study on this subject.
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2

Dash, Yajnaseni. "An Insight into Parallel Computing Paradigm." In 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT). IEEE, 2019. http://dx.doi.org/10.1109/icicict46008.2019.8993136.

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Rover, D. T. "A performance visualization paradigm for data parallel computing." In Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences. IEEE, 1992. http://dx.doi.org/10.1109/hicss.1992.183288.

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Rani, K. Swarupa, V. Kamakshi Prasad, and C. Raghavendra Rao. "Periodic knowledge discovery through parallel paradigm." In 2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2012. http://dx.doi.org/10.1109/pdgc.2012.6449932.

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Atre, Medha, Birendra Jha, and Ashwini Rao. "Distributed Deep Learning Using Volunteer Computing-Like Paradigm." In 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2021. http://dx.doi.org/10.1109/ipdpsw52791.2021.00144.

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Allamanis, Miltiadis, and Chris Mavrakis. "Addon: A Paradigm for Large-Scale Document Discussion." In Parallel and Distributed Computing and Networks / Software Engineering. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.720-056.

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Yang, Zhi, Changqin Yin, and Yan Liu. "A Cost-Based Resource Scheduling Paradigm in Cloud Computing." In 2011 12th International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT). IEEE, 2011. http://dx.doi.org/10.1109/pdcat.2011.1.

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Murdocca, Miles J., and Atul Sharma. "Application of optically reconfigurable interconnects to the dataflow parallel computing paradigm." In Aerospace Sensing, edited by Dennis R. Pape. SPIE, 1992. http://dx.doi.org/10.1117/12.139915.

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Ma, Kun, Shuhui Liu, Yongzheng Lin, Ziqiang Yu, and Ke Ji. "Parallel Grouping Particle Swarm Optimization with Stream Processing Paradigm." In 2017 IEEE 19th International Conference on High Performance Computing and Communications Workshops (HPCCWS). IEEE, 2017. http://dx.doi.org/10.1109/hpccws.2017.00010.

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Shang, Ling, Serge Petiton, and Maxime Hugues. "A New Parallel Paradigm for Block-Based Gauss-Jordan Algorithm." In 2009 Eighth International Conference on Grid and Cooperative Computing (GCC). IEEE, 2009. http://dx.doi.org/10.1109/gcc.2009.75.

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