• Title, Summary, Keyword: Parallel Computing

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An Optimized Iterative Semantic Compression Algorithm And Parallel Processing for Large Scale Data

  • Jin, Ran;Chen, Gang;Tung, Anthony K.H.;Shou, Lidan;Ooi, Beng Chin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.6
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    • pp.2761-2781
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    • 2018
  • With the continuous growth of data size and the use of compression technology, data reduction has great research value and practical significance. Aiming at the shortcomings of the existing semantic compression algorithm, this paper is based on the analysis of ItCompress algorithm, and designs a method of bidirectional order selection based on interval partitioning, which named An Optimized Iterative Semantic Compression Algorithm (Optimized ItCompress Algorithm). In order to further improve the speed of the algorithm, we propose a parallel optimization iterative semantic compression algorithm using GPU (POICAG) and an optimized iterative semantic compression algorithm using Spark (DOICAS). A lot of valid experiments are carried out on four kinds of datasets, which fully verified the efficiency of the proposed algorithm.

Fully Homomorphic Encryption Based On the Parallel Computing

  • Tan, Delin;Wang, Huajun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.1
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    • pp.497-522
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    • 2018
  • Fully homomorphic encryption(FHE) scheme may be the best method to solve the privacy leakage problem in the untrusted servers because of its ciphertext calculability. However, the existing FHE schemes are still not being put into the practical applications due to their low efficiency. Therefore, it is imperative to find a more efficient FHE scheme or to optimize the existing FHE schemes so that they can be put into the practical applications. In this paper, we optimize GSW scheme by using the parallel computing, and finally we get a high-performance FHE scheme, namely PGSW scheme. Experimental results show that the time overhead of the homomorphic operations in new FHE scheme will be reduced manyfold with the increasing of processing units number. Therefore, our scheme can greatly reduce the running time of homomorphic operations and improve the performance of FHE scheme through sacrificing hardware resources. It can be seen that our FHE scheme can catalyze the development of FHE.

Parallel LDPC Decoding on a Heterogeneous Platform using OpenCL

  • Hong, Jung-Hyun;Park, Joo-Yul;Chung, Ki-Seok
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.6
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    • pp.2648-2668
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    • 2016
  • Modern mobile devices are equipped with various accelerated processing units to handle computationally intensive applications; therefore, Open Computing Language (OpenCL) has been proposed to fully take advantage of the computational power in heterogeneous systems. This article introduces a parallel software decoder of Low Density Parity Check (LDPC) codes on an embedded heterogeneous platform using an OpenCL framework. The LDPC code is one of the most popular and strongest error correcting codes for mobile communication systems. Each step of LDPC decoding has different parallelization characteristics. In the proposed LDPC decoder, steps suitable for task-level parallelization are executed on the multi-core central processing unit (CPU), and steps suitable for data-level parallelization are processed by the graphics processing unit (GPU). To improve the performance of OpenCL kernels for LDPC decoding operations, explicit thread scheduling, vectorization, and effective data transfer techniques are applied. The proposed LDPC decoder achieves high performance and high power efficiency by using heterogeneous multi-core processors on a unified computing framework.

Analysis of Implementing Mobile Heterogeneous Computing for Image Sequence Processing

  • BAEK, Aram;LEE, Kangwoon;KIM, Jae-Gon;CHOI, Haechul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.4948-4967
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    • 2017
  • On mobile devices, image sequences are widely used for multimedia applications such as computer vision, video enhancement, and augmented reality. However, the real-time processing of mobile devices is still a challenge because of constraints and demands for higher resolution images. Recently, heterogeneous computing methods that utilize both a central processing unit (CPU) and a graphics processing unit (GPU) have been researched to accelerate the image sequence processing. This paper deals with various optimizing techniques such as parallel processing by the CPU and GPU, distributed processing on the CPU, frame buffer object, and double buffering for parallel and/or distributed tasks. Using the optimizing techniques both individually and combined, several heterogeneous computing structures were implemented and their effectiveness were analyzed. The experimental results show that the heterogeneous computing facilitates executions up to 3.5 times faster than CPU-only processing.

Development of the Dynamic Host Management Scheme for Parallel/Distributed Processing on the Web (웹 환경에서의 병렬/분산 처리를 위한 동적 호스트 관리 기법의 개발)

  • Song, Eun-Ha;Jeong, Young-Sik
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.3
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    • pp.251-260
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    • 2002
  • The parallel/distributed processing with a lot of the idle hosts on the web has the high coot-performance ratio for large-scale applications. It's processing has to show the solutions for unpredictable status such as heterogeneity of hosts, variability of hosts, autonomy of hosts, the supporting performance continuously, and the number of hosts which are participated in computation and so on. In this paper, we propose the strategy of adaptive tack reallocation based on performance the host job processing, spread out geographically Also, It shows the scheme of dynamic host management with dynamic environment, which is changed by lots of hosts on the web during parallel processing for large-scale applications. This paper implements the PDSWeb (Parallel/Distributed Scheme on Web) system, evaluates and applies It to the generation of rendering image with highly intensive computation. The results are showed that the adaptive task reallocation with the variation of hosts has been increased up to maximum 90% and the improvement in performance according to add/delete of hosts.

A Reconfigurable Load and Performance Balancing Scheme for Parallel Loops in a Clustered Computing Environment (클러스터 컴퓨팅 환경에서 병렬루프 처리를 위한 재구성 가능한 부하 및 성능 균형 방법)

  • 김태형
    • Journal of KIISE:Computing Practices and Letters
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    • v.10 no.1
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    • pp.49-56
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    • 2004
  • Load imbalance is a serious impediment to achieving good performance in parallel processing. Global load balancing schemes cannot adequately manage to balance parallel tasks generated from a single application. Dynamic loop scheduling methods are known to be useful in balancing parallel loops on shared-memory multiprocessor machines. However, their centralized nature causes a bottleneck for the relatively small number of processors in a network of workstations because of order-of-magniture differences in communication overheads. Moreover, improvements of basis loops scheduling methods have not effectively dealt with irregularly distributed workloads in parallel loops, which commonly occur in applications for a network of workstation. In this paper, we present a new reconfigurable and decentralized balancing method for parallel loops on a network of workstations. Since our method supplements performance balancing with those tranditional load balancing methods, it minimizes the overall execution time.

Distributed Parallel Computing Environment for Java (자바를 위한 분산된 병렬 컴퓨팅 환경)

  • 이상윤;김승호
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.6
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    • pp.23-37
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    • 2004
  • Since java thread is an object which is treated as independent process within one execution space in the multiprocessing environment, we can use it for independent process of parallel processing. Using thread and synchronization mechanism of java enables us to write parallel application program easily. Therefore, a lot of results are exist which is apply the feature of java that support parallel processing to the distributed computing environment. In this paper, we introduce a system of environment that support parallel execution of thread which is included in legacy java program. The system named TORB(Transparent Object Request Broker) enables us parallel execution of legacy java program after simple converting process, since it support the feature of programming transparency. TORB is extended version of distributed programming tool that is published by our research team. And it had only typical distributed processing feature that is execute a specified function at the specified computer.