• Title/Summary/Keyword: high performance computing

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Meshfree/GFEM in hardware-efficiency prospective

  • Tian, Rong
    • Interaction and multiscale mechanics
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    • v.6 no.2
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    • pp.197-210
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    • 2013
  • A fundamental trend of processor architecture evolving towards exaflops is fast increasing floating point performance (so-called "free" flops) accompanied by much slowly increasing memory and network bandwidth. In order to fully enjoy the "free" flops, a numerical algorithm of PDEs should request more flops per byte or increase arithmetic intensity. A meshfree/GFEM approximation can be the class of the algorithm. It is shown in a GFEM without extra dof that the kind of approximation takes advantages of the high performance of manycore GPUs by a high accuracy of approximation; the "expensive" method is found to be reversely hardware-efficient on the emerging architecture of manycore.

Effects of elastic foundation on the dynamic stability of cylindrical shells

  • Ng, T.Y.;Lam, K.Y.
    • Structural Engineering and Mechanics
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    • v.8 no.2
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    • pp.193-205
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    • 1999
  • A formulation for the dynamic stability analysis of cylindrical shells resting on elastic foundations is presented. In this previously not studied problem, a normal-mode expansion of the partial differential equations of motion, which includes the effects of the foundation as well as a harmonic axial loading, yields a system of Mathieu-Hill equations the stability of which is analyzed using Bolotin's method. The present study examines the effects of the elastic foundation on the instability regions of the cylindrical shell for the transverse, longitudinal and circumferential modes.

MAHA-FS : A Distributed File System for High Performance Metadata Processing and Random IO (MAHA-FS : 고성능 메타데이터 처리 및 랜덤 입출력을 위한 분산 파일 시스템)

  • Kim, Young Chang;Kim, Dong Oh;Kim, Hong Yeon;Kim, Young Kyun;Choi, Wan
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.2
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    • pp.91-96
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    • 2013
  • The application field of supercomputing systems are changing to support into the field for both a large-volume data processing and high-performance computing at the same time such as bio-applications. These applications require high-performance distributed file system for storage management and efficient high-speed processing of large amounts of data that occurs. In this paper, we introduce MAHA-FS for supercomputing systems for processing large amounts of data and high-performance computing, providing excellent metadata operation performance and IO performance. It is shown through performance analysis that MAHA-FS provides excellent performance in terms of the metadata processing and random IO processing.

Prediction of fly ash concrete compressive strengths using soft computing techniques

  • Ramachandra, Rajeshwari;Mandal, Sukomal
    • Computers and Concrete
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    • v.25 no.1
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    • pp.83-94
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    • 2020
  • The use of fly ash in modern-day concrete technology aiming sustainable constructions is on rapid rise. Fly ash, a spinoff from coal calcined thermal power plants with pozzolanic properties is used for cement replacement in concrete. Fly ash concrete is cost effective, which modifies and improves the fresh and hardened properties of concrete and additionally addresses the disposal and storage issues of fly ash. Soft computing techniques have gained attention in the civil engineering field which addresses the drawbacks of classical experimental and computational methods of determining the concrete compressive strength with varying percentages of fly ash. In this study, models based on soft computing techniques employed for the prediction of the compressive strengths of fly ash concrete are collected from literature. They are classified in a categorical way of concrete strengths such as control concrete, high strength concrete, high performance concrete, self-compacting concrete, and other concretes pertaining to the soft computing techniques usage. The performance of models in terms of statistical measures such as mean square error, root mean square error, coefficient of correlation, etc. has shown that soft computing techniques have potential applications for predicting the fly ash concrete compressive strengths.

Global Internet Computing Environment based on Java (자바를 기반으로 한 글로벌 인터넷 컴퓨팅 환경)

  • Kim, Hui-Cheol;Sin, Pil-Seop;Park, Yeong-Jin;Lee, Yong-Du
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.9
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    • pp.2320-2331
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    • 1999
  • Over the Internet, in order to utilize a collection of idle computers as a parallel computing platform, we propose a new scheme called GICE(Global Internet Computing Environment). GICE is motivated to obtain high programmability, efficient support for heterogeneous computing resources, system scalability, and finally high performance. The programming model of GICE is based on a single address space. GICE is featured with a Java based programming environment, a dynamic resource management scheme, and efficient parallel task scheduling and execution mechanisms. Based on a prototype implementation of GICE, we address the concept, feasibility, complexity and performance of Internet computing.

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Analysis of the GPGPU Performance for Various Combinations of Workloads Executed Concurrently (동시에 실행되는 워크로드 조합에 따른 GPGPU 성능 분석)

  • Kim, Dongwhan;Eom, Hyeonsang
    • KIISE Transactions on Computing Practices
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    • v.23 no.3
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    • pp.165-170
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    • 2017
  • Many studies have utilized GPGPU (General-Purpose Graphic Processing Unit) and its high computing power to compute complex tasks. The characteristics of GPGPU programs necessitate the operations of memory copy between the host and device. A high latency period can affect the performance of the program. Thus, it is required to significantly improve the performance of GPGPU programs by optimizations. By executing multiple GPGPU programs simultaneously, the latency hiding effect of memory copy is achieved by overlapping the memory copy and computing operations in GPGPU. This paper presents the results of analyzing the latency hiding effect for memory copy operations. Furthermore, we propose a performance anticipation model and an algorithm for the limitations of using pinned memory, and show that the use of the proposed algorithm results in a 41% performance increase.

Reconfigurable Multi-Array Architecture for Low-Power and High-Speed Embedded Systems

  • Kim, Yoon-Jin
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.11 no.3
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    • pp.207-220
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    • 2011
  • Coarse-grained reconfigurable architecture (CGRA) based embedded systems aims to achieve high system performance with sufficient flexibility to map a variety of applications. However, the CGRA has been considered as prohibitive one due to its significant area/power overhead and performance bottleneck. In this work, I propose reconfigurable multi-array architecture to reduce power/area and enhance performance in configurable embedded systems. The CGRA-based embedded systems that consist of hierarchical configurable computing arrays with varying size and communication speed were examined for multimedia and other applications. Experimental results show that the proposed approach reduces on-chip area by 22%, execution time by up to 72% and reduces power consumption by up to 55% when compared with the conventional CGRA-based architectures.

Performance Evaluation and Optimization of NoSQL Databases with High-Performance Flash SSDs (고성능 플래시 SSD 환경에서 NoSQL 데이터베이스의 성능 평가 및 최적화)

  • Han, Hyuck
    • The Journal of the Korea Contents Association
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    • v.17 no.7
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    • pp.93-100
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    • 2017
  • Recently, demands for high-performance flash-based storage devices (i.e., flash SSD) have rapidly grown in social network services, cloud computing, super-computing, and enterprise storage systems. The industry and academic communities made the NVMe specification for high-performance storage devices, and NVMe-based flash SSDs can be now obtained in the market. In this article, we evaluate performance of NoSQL databases that social network services and cloud computing services heavily adopt by using NVMe-based flash SSDs. To this end, we use NVMe SSD that Samsung Electronics recently developed, and the SSD used in this study has performance up to 3.5GB/s for sequential read/write operations. We use WiredTiger for NoSQL databases, and it is a default storage engine for MongoDB. Our experimental results show that log processing in NoSQL databases is a major overhead when high-performance NVMe-based flash SSDs are used. Furthermore, we optimize components of log processing and optimized WiredTiger show up to 15 times better performance than original WiredTiger.

Implementation of Access Control System Suitable for Meteorological Tasks in Grid Computing Environment (그리드 컴퓨팅 환경에서 기상업무에 적합한 접근 제어 시스템 구현)

  • Na, Seung-kwon;Ju, Jae-han
    • Journal of Advanced Navigation Technology
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    • v.21 no.2
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    • pp.206-211
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    • 2017
  • Recently computing devices by connecting to a network, grid computing, the next generation of digital neural networks that provide maximum service will connect all of the computer such as a PC or server, PDA into one giant network makes the virtual machine. Therefore, we propose the grid computing implementation model to be applied to meteorological business field as follows. First, grid computing will be used for tasks such as the development of numerical models below the mid-scale or test operations, and the final backup of the weather supercomputer. Second, the resources that will constitute grid computing are limited to business PCs and Linux servers operated by the central government considering operational efficiency. Third, the network is restricted to the LAN section, which suggests the implementation of high performance computing.

Spark Framework Based on a Heterogenous Pipeline Computing with OpenCL (OpenCL을 활용한 이기종 파이프라인 컴퓨팅 기반 Spark 프레임워크)

  • Kim, Daehee;Park, Neungsoo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.2
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    • pp.270-276
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    • 2018
  • Apache Spark is one of the high performance in-memory computing frameworks for big-data processing. Recently, to improve the performance, general-purpose computing on graphics processing unit(GPGPU) is adapted to Apache Spark framework. Previous Spark-GPGPU frameworks focus on overcoming the difficulty of an implementation resulting from the difference between the computation environment of GPGPU and Spark framework. In this paper, we propose a Spark framework based on a heterogenous pipeline computing with OpenCL to further improve the performance. The proposed framework overlaps the Java-to-Native memory copies of CPU with CPU-GPU communications(DMA) and GPU kernel computations to hide the CPU idle time. Also, CPU-GPU communication buffers are implemented with switching dual buffers, which reduce the mapped memory region resulting in decreasing memory mapping overhead. Experimental results showed that the proposed Spark framework based on a heterogenous pipeline computing with OpenCL had up to 2.13 times faster than the previous Spark framework using OpenCL.