Dynamic Memory Allocation for Scientific Workflows in Containers

Theodora Adufu, Jieun Choi, Yoonhee Kim

http://doi.org/

The workloads of large high-performance computing (HPC) scientific applications are steadily becoming “bursty” due to variable resource demands throughout their execution life-cycles. However, the over-provisioning of virtual resources for optimal performance during execution remains a key challenge in the scheduling of scientific HPC applications. While over-provisioning of virtual resources guarantees peak performance of scientific application in virtualized environments, it results in increased amounts of idle resources that are unavailable for use by other applications. Herein, we proposed a memory resource reconfiguration approach that allows the quick release of idle memory resources for new applications in OS-level virtualized systems, based on the applications resource-usage pattern profile data. We deployed a scientific workflow application in Docker, a light-weight OS-level virtualized system. In the proposed approach, memory allocation is fine-tuned to containers at each stage of the workflows execution life-cycle. Thus, overall memory resource utilization is improved.

Implementation and Performance Analysis of Event Processing and Buffer Managing Techniques for DDS

http://doi.org/

Data Distribution Service (DDS) is a communication middleware that supports a flexible, scalable and real-time communication capability. This paper describes several techniques to improve the performance of DDS middleware. Detailed events for the internal behavior of the middleware are defined. A DDS message is disassembled into several submessages of independent, meaningful units for event-driven structuring in order to reduce the processing complexity. The proposed technique of history cache management is also described. It utilizes the fact that status access and random access to the history cache occur more frequently in the DDS. These methods have been implemented in the EchoDDS, the DDS implementation developed by our team, and it showed improved performance.

Techniques to Guarantee Real-Time Fault Recovery in Spark Streaming Based Cloud System

Jungho Kim, Daedong Park, Sangwook Kim, Yongshik Moon, Seongsoo Hong

http://doi.org/

In a real-time cloud environment, the data analysis framework plays a pivotal role. Spark Streaming meets most real-time requirements among existing frameworks. However, the framework does not meet the second scale real-time fault recovery requirement. Spark Streaming fault recovery time increases in proportion to the transformation history length called lineage. This is because it recovers the last state data based on the cumulative lineage recorded during normal operation. Therefore, fault recovery time is not bounded within a limited time. In addition, it is impossible to achieve a second-scale fault recovery time because it costs tens of seconds to read initial state data from fault-tolerant storage. In this paper, we propose two techniques to solve the problems mentioned above. We apply the proposed techniques to Spark Streaming 1.6.2. Experimental results show that the fault recovery time is bounded and the average fault recovery time is reduced by up to 41.57%.

Multi-core Scalable Fair I/O Scheduling for Multi-queue SSDs

Minjung Cho, Hyeongseok Kang, Kanghee Kim

http://doi.org/

The emerging NVMe-based multi-queue SSDs provides a high bandwidth by parallel I/O, i.e., each core performs I/O through its dedicated queue in parallel with other cores. To provide a bandwidth share for each application with I/O, a fair-share scheduler that provides a bandwidth share to each core is required. In this study, we proposed a multi-core scalable fair-queuing algorithm for multi-queue SSDs. The algorithm adopts randomization to minimize the inter-core synchronization overheads and provides a weight-proportional bandwidth share to each core. The results of our experiments indicated that the proposed algorithm gives accurate bandwidth partitioning and outperforms the existing FlashFQ scheduler, regardless of the number of cores for a Linux kernel with block-mq.

Development of Reconfigurable Tactical Operation Display Framework by Battery and Battalion

Sangtae Lee, Seungyoung Lee, SoungHyouk Wi, Kyutae Cho

http://doi.org/

The tactical operation centers of future anti-aircraft missile systems provide the environment for the research on future air threats, tactical information, integrated battlefield environment creation and management, engagement control and command and control algorithms. To develop the key functional elements of integrated battlefield situation creation and processing and tactical operation automation processing operations, battery/battalion tactical operation control and reconfiguration design software are required. Therefore, the algorithm software of each function and the tactical operation display software and link software for interworking between equipment were developed as reconfigurable through a data-centric design. In this paper, a tactical operation display framework that can be reconfigured on the operation display of the tactical operations according to the battery/battalion is introduced. This tactical operation display framework was used to develop a common data model design for the reconfigurable structure of multi-role tactical operations with battery / battalion and mission views, and a display configuration tool that provides a tactical operation display framework for view development was also developed using the MVC pattern. If the tactical operation display framework is used, it will be possible to reuse the view design through the common base structure, and a view that can be reconfigured easily and quickly will also be developed.

Bias-Based Predictor to Improve the Recommendation Performance of the Rating Frequency Weight-based Baseline Predictor

Tae-Gyu Hwang, Sung Kwon Kim

http://doi.org/

Collaborative Filtering is limited because of the cost that is required to perform the recommendation (such as the time complexity and space complexity). The RFWBP (Rating Frequency Weight-based Baseline Predictor) that approximates the precision of the existing methods is one of the efficiency methods to reduce the cost. But, the following issues need to be considered regarding the RFWBP: 1) It does not reduce the error because the RFWBP does not learn for the recommendation, and 2) it recommends all of the items because there is no condition for an appropriate recommendation list when only the RFWBP is used for the achievement of efficiency. In this paper, the BBP (Bias-Based Predictor) is proposed to solve these problems. The BBP reduces the error range, and it determines some of the cases to make an appropriate recommendation list, thereby forging a recommendation list for each case.

Coreference Resolution for Korean Pronouns using Pointer Networks

Cheoneum Park, Changki Lee

http://doi.org/

Pointer Networks is a deep-learning model for the attention-mechanism outputting of a list of elements that corresponds to the input sequence and is based on a recurrent neural network (RNN). The coreference resolution for pronouns is the natural language processing (NLP) task that defines a single entity to find the antecedents that correspond to the pronouns in a document. In this paper, a pronoun coreference-resolution method that finds the relation between the antecedents and the pronouns using the Pointer Networks is proposed; furthermore, the input methods of the Pointer Networks-that is, the chaining order between the words in an entity-are proposed. From among the methods that are proposed in this paper, the chaining order Coref2 showed the best performance with an F1 of MUC 81.40 %. The method showed performances that are 31.00 % and 19.28 % better than the rule-based (50.40 %) and statistics-based (62.12 %) coreference resolution systems, respectively, for the Korean pronouns.

End-to-end Korean Document Summarization using Copy Mechanism and Input-feeding

Kyoung-Ho Choi, Changki Lee

http://doi.org/

In this paper, the copy mechanism and input feeding are applied to recurrent neural network(RNN)-search model in a Korean-document summarization in an end-to-end manner. In addition, the performances of the document summarizations are compared according to the model and the tokenization format; accordingly, the syllable-unit, morpheme-unit, and hybrid-unit tokenization formats are compared. For the experiments, Internet newspaper articles were collected to construct a Korean-document summary data set (train set: 30291 documents; development set: 3786 documents; test set: 3705 documents). When the format was tokenized as the morpheme-unit, the models with the input feeding and the copy mechanism showed the highest performances of ROUGE-1 35.92, ROUGE-215.37, and ROUGE-L 29.45.

OOPT: An Object-Oriented Development Methodology for Software Engineering Education

Sejin Jung, Dong-Ah Lee, Eui-Sub Kim, Chun-Hyon Chang, Junbeom Yoo

http://doi.org/

The software development process (SDP) plays an important basic role in software engineering education. Every software is developed in accordance with a specific SDP which contains all phases of software development. SDP education helps students to understand the overall techniques and the process of software engineering. This paper introduces a software development methodology (i.e., process) - ‘OOPT (Object Oriented Process with Traceability),’ which was proposed for use in university software engineering classes. The OOPT is based on object-oriented software development, and it defines concrete requirements as well as outputs of each process/phases. It also contains the unit/system testing and a traceability analysis. We have used the OOPT in software engineering classes at Konkuk university for eight years. This paper conveys our experience as well as future extension and improvement plans.

Automatic Keyword Extraction using Hierarchical Graph Model Based on Word Co-occurrences

KwangHo Song, Yoo-Sung Kim

http://doi.org/

Keyword extraction can be utilized in text mining of massive documents for efficient extraction of subject or related words from the document. In this study, we proposed a hierarchical graph model based on the co-occurrence relationship, the intrinsic dependency relationship between words, and common sub-word in a single document. In addition, the enhanced TextRank algorithm that can reflect the influences of outgoing edges as well as those of incoming edges is proposed. Subsequently a novel keyword extraction scheme using the proposed hierarchical graph model and the enhanced TextRank algorithm is proposed to extract representative keywords from a single document. In the experiments, various evaluation methods were applied to the various subject documents in order to verify the accuracy and adaptability of the proposed scheme. As the results, the proposed scheme showed better performance than the previous schemes.

Fast Non-Adjacent Form (NAF) Conversion through a Bit-Stream Scan

Doo-Hee Hwang, Jin-Myeong Shin, Yoon-Ho Choi

http://doi.org/

As a special form of the signed-digit representation, the NAF(non-adjacent form) minimizes the hamming weight by reducing the average density of the non-zero bits from the binary representation of the positive integer k. Due to this advantage, the NAF is used in various fields; in particular, it is actively used in cryptology. The existing NAF-conversion algorithm, however, is problematic because the conversion speed decreases when the LSB(least significant bit) frequently becomes "1" during the binary positive integer conversion process. This paper suggests a method for the improvement of the NAF-conversion speed for which the problems that occur in the existing NAF-conversion process are solved. To verify the performance improvement of the algorithm, the CPU cycle for the various inputs were measured on the ATmega128, a low-performance 8-bit microprocessor. The results of this study show that, compared with the existing algorithm, the suggested algorithm not only improved the processing speed of the major patterns by 20% or more on average, but it also reduced the NAF-conversion time by 13% or more.

A Seamless Adaptive Streaming Scheme for Interactive Multimedia Service in HTTP Adaptive Streaming

Heekwang Kim, Kwangsue Chung

http://doi.org/

Because of the explosive growth of mobile devices and development of network technologies, HTTP (Hypertext Transfer Protocol) adaptive streaming has become a new trend in video delivery to provide efficient multimedia streaming services. As interest in personalized broadcasting grows, the study of interactive multimedia has been actively pursued. The interactive multimedia service is a method of playing media according to a scenario selected by the user. Providing the interactive multimedia service with the existing HTTP adaptive streaming causes switching delay and buffer underflow according to the point in time when the user selects the scenario while the client streams the interactive multimedia and therefore decreases the user QoE (Quality of Experience). In this paper, we propose an adaptive streaming scheme for interactive multimedia service in HTTP adaptive streaming to provide seamless playback. We design the architecture and prefetching scheme for interactive multimedia streaming.

Impact of Diverse Document-evaluation Measure-based Searching Methods in Big Data Search Accuracy

Ji young Kim, DaHyeon Han, Jongkwon Kim

http://doi.org/

With the rapid growth of Big Data, research on extracting meaningful information is being pursued by both academia and industry. Especially, data characteristics derived from analysis, and researcher intention are key factors for search algorithms to obtain accurate output. Therefore, reflecting both data characteristics and researcher intention properly is the final goal of data analysis research. The data analyzed properly can help users to increase loyalty to the service provided by company, and to utilize information more effectively and efficiently. In this paper, we explore various methods of document-evaluation, so that we can improve the accuracy of searching article one of the most frequently searches used in real life. We also analyze the experiment result, and suggest the proper manners to use various methods.