• Title/Summary/Keyword: Memory usage

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Proposal of a Step-by-Step Optimized Campus Power Forecast Model using CNN-LSTM Deep Learning (CNN-LSTM 딥러닝 기반 캠퍼스 전력 예측 모델 최적화 단계 제시)

  • Kim, Yein;Lee, Seeun;Kwon, Youngsung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.10
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    • pp.8-15
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    • 2020
  • A forecasting method using deep learning does not have consistent results due to the differences in the characteristics of the dataset, even though they have the same forecasting models and parameters. For example, the forecasting model X optimized with dataset A would not produce the optimized result with another dataset B. The forecasting model with the characteristics of the dataset needs to be optimized to increase the accuracy of the forecasting model. Therefore, this paper proposes novel optimization steps for outlier removal, dataset classification, and a CNN-LSTM-based hyperparameter tuning process to forecast the daily power usage of a university campus based on the hourly interval. The proposing model produces high forecasting accuracy with a 2% of MAPE with a single power input variable. The proposing model can be used in EMS to suggest improved strategies to users and consequently to improve the power efficiency.

RSP-DS: Real Time Sequential Patterns Analysis in Data Streams (RSP-DS: 데이터 스트림에서의 실시간 순차 패턴 분석)

  • Shin Jae-Jyn;Kim Ho-Seok;Kim Kyoung-Bae;Bae Hae-Young
    • Journal of Korea Multimedia Society
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    • v.9 no.9
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    • pp.1118-1130
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    • 2006
  • Existed pattern analysis algorithms in data streams environment have researched performance improvement and effective memory usage. But when new data streams come, existed pattern analysis algorithms have to analyze patterns again and have to generate pattern tree again. This approach needs many calculations in real situation that needs real time pattern analysis. This paper proposes a method that continuously analyzes patterns of incoming data streams in real time. This method analyzes patterns fast, and thereafter obtains real time patterns by updating previously analyzed patterns. The incoming data streams are divided into several sequences based on time based window. Informations of the sequences are inputted into a hash table. When the number of the sequences are over predefined bound, patterns are analyzed from the hash table. The patterns form a pattern tree, and later created new patterns update the pattern tree. In this way, real time patterns are always maintained in the pattern tree. During pattern analysis, suffixes of both new pattern and existed pattern in the tree can be same. Then a pointer is created from the new pattern to the existed pattern. This method reduce calculation time during duplicated pattern analysis. And old patterns in the tree are deleted easily by FIFO method. The advantage of our algorithm is proved by performance comparison with existed method, MILE, in a condition that pattern is changed continuously. And we look around performance variation by changing several variable in the algorithm.

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Design and Implementation of High-dimensional Index Structure for the support of Concurrency Control (필터링에 기반한 고차원 색인구조의 동시성 제어기법의 설계 및 구현)

  • Lee, Yong-Ju;Chang, Jae-Woo;Kim, Hang-Young;Kim, Myung-Joon
    • The KIPS Transactions:PartD
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    • v.10D no.1
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    • pp.1-12
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    • 2003
  • Recently, there have been many indexing schemes for multimedia data such as image, video data. But recent database applications, for example data mining and multimedia database, are required to support multi-user environment. In order for indexing schemes to be useful in multi-user environment, a concurrency control algorithm is required to handle it. So we propose a concurrency control algorithm that can be applied to CBF (cell-based filtering method), which uses the signature of the cell for alleviating the dimensional curse problem. In addition, we extend the SHORE storage system of Wisconsin university in order to handle high-dimensional data. This extended SHORE storage system provides conventional storage manager functions, guarantees the integrity of high-dimensional data and is flexible to the large scale of feature vectors for preventing the usage of large main memory. Finally, we implement the web-based image retrieval system by using the extended SHORE storage system. The key feature of this system is platform-independent access to the high-dimensional data as well as functionality of efficient content-based queries. Lastly. We evaluate an average response time of point query, range query and k-nearest query in terms of the number of threads.

Hardware Design for JBIG2 Encoder on Embedded System (임베디드용 JBIG2 부호화기의 하드웨어 설계)

  • Seo, Seok-Yong;Ko, Hyung-Hwa
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.2C
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    • pp.182-192
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    • 2010
  • This paper proposes the hardware IP design of JBIG2 encoder. In order to facilitate the next generation FAX after the standardization of JBIG2, major modules of JBIG2 encoder are designed and implemented, such as symbol extraction module, Huffman coder, MMR coder, and MQ coder. ImpulseC Codeveloper and Xilinx ISE/EDK program are used for the synthesis of VHDL code. To minimize the memory usage, 128 lines of input image are processed succesively instead of total image. The synthesized IPs are downloaded to Virtex-4 FX60 FPGA on ML410 development board. The four synthesized IPs utilize 36.7% of total slice of FPGA. Using Active-HDL tool, the generated IPs were verified showing normal operation. Compared with the software operation using microblaze cpu on ML410 board, the synthesized IPs are better in operation time. The improvement ratio of operation time between the synthesized IP and software is 17 times in case of symbol extraction IP, and 10 times in Huffman coder IP. MMR coder IP shows 6 times faster and MQ coder IP shows 2.2 times faster than software only operation. The synthesized H/W IP and S/W module cooperated to succeed in compressing the CCITT standard document.

Frequently Occurred Information Extraction from a Collection of Labeled Trees (라벨 트리 데이터의 빈번하게 발생하는 정보 추출)

  • Paik, Ju-Ryon;Nam, Jung-Hyun;Ahn, Sung-Joon;Kim, Ung-Mo
    • Journal of Internet Computing and Services
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    • v.10 no.5
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    • pp.65-78
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    • 2009
  • The most commonly adopted approach to find valuable information from tree data is to extract frequently occurring subtree patterns from them. Because mining frequent tree patterns has a wide range of applications such as xml mining, web usage mining, bioinformatics, and network multicast routing, many algorithms have been recently proposed to find the patterns. However, existing tree mining algorithms suffer from several serious pitfalls in finding frequent tree patterns from massive tree datasets. Some of the major problems are due to (1) modeling data as hierarchical tree structure, (2) the computationally high cost of the candidate maintenance, (3) the repetitious input dataset scans, and (4) the high memory dependency. These problems stem from that most of these algorithms are based on the well-known apriori algorithm and have used anti-monotone property for candidate generation and frequency counting in their algorithms. To solve the problems, we base a pattern-growth approach rather than the apriori approach, and choose to extract maximal frequent subtree patterns instead of frequent subtree patterns. The proposed method not only gets rid of the process for infrequent subtrees pruning, but also totally eliminates the problem of generating candidate subtrees. Hence, it significantly improves the whole mining process.

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The Sub-Peres Functions for Random Number Generation (무작위수생성을 위한 부 페레즈 함수)

  • Pae, Sung-Il
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.2
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    • pp.19-30
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    • 2013
  • We study sub-Peres functions that are defined recursively as Peres function for random number generation. Instead of using two parameter functions as in Peres function, the sub-Peres functions uses only one parameter function. Naturally, these functions produce less random bits, hence are not asymptotically optimal. However, the sub-Peres functions runs in linear time, i.e., in O(n) time rather than O(n logn) as in Peres's case. Moreover, the implementation is even simpler than Peres function not only because they use only one parameter function but because they are tail recursive, hence run in a simple iterative manner rather than by a recursion, eliminating the usage of stack and thus further reducing the memory requirement of Peres's method. And yet, the output rate of the sub-Peres function is more than twice as much as that of von Neumann's method which is widely known linear-time method. So, these methods can be used, instead of von Neumann's method, in an environment with limited computational resources like mobile devices. We report the analyses of the sub-Peres functions regarding their running time and the exact output rates in comparison with Peres function and other known methods for random number generation. Also, we discuss how these sub-Peres function can be implemented.

Reconfigurable SoC Design with Hierarchical FSM and Synchronous Dataflow Model (Hierarchical FSM과 Synchronous Dataflow Model을 이용한 재구성 가능한 SoC의 설계)

  • 이성현;유승주;최기영
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.40 no.8
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    • pp.619-630
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    • 2003
  • We present a method of runtime configuration scheduling in reconfigurable SoC design. As a model of computation, we use a popular formal model of computation, hierarchical FSM (HFSM) with synchronous dataflow (SDF) model, in short, HFSM-SDF model. In reconfigurable SoC design with HFSM-SDF model, the problem of configuration scheduling becomes challenging due to the dynamic behavior of the system such as concurrent execution of state transitions (by AND relation), complex control flow (HFSM), and complex schedules of SDF actor firing. This makes it hard to hide configuration latency efficiently with compile-time static configuration scheduling. To resolve the problem, it is necessary to know the exact order of required configurations during runtime and to perform runtime configuration scheduling. To obtain the exact order of configurations, we exploit the inherent property of HFSM-SDF that the execution order of SDF actors can be determined before executing the state transition of top FSM. After obtaining the order information and storing it in the ready configuration queue (ready CQ), we execute the state transition. During the execution, whenever there is FPGA resource available, a new configuration is selected from the ready CQ and fetched by the runtime configuration scheduler. We applied the method to an MPEG4 decoder and IS95 design and obtained up to 21.8% improvement in system runtime with a negligible overhead of memory usage.

Implementation of a Static Analyzer for Detecting the PHP File Inclusion Vulnerabilities (PHP 파일 삽입 취약성 검사를 위한 정적 분석기의 구현)

  • Ahn, Joon-Seon;Lim, Seong-Chae
    • The KIPS Transactions:PartA
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    • v.18A no.5
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    • pp.193-204
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    • 2011
  • Since web applications are accessed by anonymous users via web, more security risks are imposed on those applications. In particular, because security vulnerabilities caused by insecure source codes cannot be properly handled by the system-level security system such as the intrusion detection system, it is necessary to eliminate such problems in advance. In this paper, to enhance the security of web applications, we develop a static analyzer for detecting the well-known security vulnerability of PHP file inclusion vulnerability. Using a semantic based static analysis, our vulnerability analyzer guarantees the soundness of the vulnerability detection and imposes no runtime overhead, differently from the other approaches such as the penetration test method and the application firewall method. For this end, our analyzer adopts abstract interpretation framework and uses an abstract analysis domain designed for the detection of the target vulnerability in PHP programs. Thus, our analyzer can efficiently analyze complicated data-flow relations in PHP programs caused by extensive usage of string data. The analysis results can be browsed using a JAVA GUI tool and the memory states and variable values at vulnerable program points can also be checked. To show the correctness and practicability of our analyzer, we analyzed the source codes of open PHP applications using the analyzer. Our experimental results show that our analyzer has practical performance in analysis capability and execution time.

An Improved Estimation Model of Server Power Consumption for Saving Energy in a Server Cluster Environment (서버 클러스터 환경에서 에너지 절약을 위한 향상된 서버 전력 소비 추정 모델)

  • Kim, Dong-Jun;Kwak, Hu-Keun;Kwon, Hui-Ung;Kim, Young-Jong;Chung, Kyu-Sik
    • The KIPS Transactions:PartA
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    • v.19A no.3
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    • pp.139-146
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    • 2012
  • In the server cluster environment, one of the ways saving energy is to control server's power according to traffic conditions. This is to determine the ON/OFF state of servers according to energy usage of data center and each server. To do this, we need a way to estimate each server's energy. In this paper, we use a software-based power consumption estimation model because it is more efficient than the hardware model using power meter in terms of energy and cost. The traditional software-based power consumption estimation model has a drawback in that it doesn't know well the computing status of servers because it uses only the idle status field of CPU. Therefore it doesn't estimate consumption power effectively. In this paper, we present a CPU field based power consumption estimation model to estimate more accurate than the two traditional models (CPU/Disk/Memory utilization based power consumption estimation model and CPU idle utilization based power consumption estimation model) by using the various status fields of CPU to get the CPU status of servers and the overall status of system. We performed experiments using 2 PCs and compared the power consumption estimated by the power consumption model (software) with that measured by the power meter (hardware). The experimental results show that the traditional model has about 8-15% average error rate but our proposed model has about 2% average error rate.

Design and Verification of PCI 2.2 Target Controller to support Prefetch Request (프리페치 요구를 지원하는 PCI 2.2 타겟 컨트롤러 설계 및 검증)

  • Hyun Eugin;Seong Kwang-Su
    • The KIPS Transactions:PartA
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    • v.12A no.6 s.96
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    • pp.523-530
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    • 2005
  • When a PCI 2.2 bus master requests data using Memory Read command, a target device may hold PCI bus without data to be transferred for long time because a target device needs time to prepare data infernally. Because the usage efficiency of the PCI bus and the data transfer efficiency are decreased due to this situation, the PCI specification recommends to use the Delayed Transaction mechanism to improve the system performance. But the mechanism cann't fully improve performance because a target device doesn't know the exact size of prefetched data. In the previous work, we propose a new method called Prefetch Request when a bus master intends to read data from the target device. In this paper, we design PCI 2.2 controller and local device that support the proposed method. The designed PCI 2.2 controller has simple local interface and it is used to convert the PCI protocol into the local protocol. So the typical users, who don't know the PCI protocol, can easily design the PCI target device using the proposed PCI controller. We propose the basic behavioral verification, hardware design verification, and random test verification to verify the designed hardware. We also build the test bench and define assembler instructions. And we propose random testing environment, which consist of reference model, random generator ,and compare engine, to efficiently verify corner case. This verification environment is excellent to find error which is not detected by general test vector. Also, the simulation under the proposed test environment shows that the proposed method has the higher data transfer efficiency than the Delayed Transaction about $9\%$.