• Title/Summary/Keyword: 성능최적화 기법

Search Result 1,338, Processing Time 0.032 seconds

Scheduling of Artificial Intelligence Workloads in Could Environments Using Genetic Algorithms (유전 알고리즘을 이용한 클라우드 환경의 인공지능 워크로드 스케줄링)

  • Seokmin Kwon;Hyokyung Bahn
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.24 no.3
    • /
    • pp.63-67
    • /
    • 2024
  • Recently, artificial intelligence (AI) workloads encompassing various industries such as smart logistics, FinTech, and entertainment are being executed on the cloud. In this paper, we address the scheduling issues of various AI workloads on a multi-tenant cloud system composed of heterogeneous GPU clusters. Traditional scheduling decreases GPU utilization in such environments, degrading system performance significantly. To resolve these issues, we present a new scheduling approach utilizing genetic algorithm-based optimization techniques, implemented within a process-based event simulation framework. Trace driven simulations with diverse AI workload traces collected from Alibaba's MLaaS cluster demonstrate that the proposed scheduling improves GPU utilization compared to conventional scheduling significantly.

Side-Channel Attack Trends of Code-based PQC Algorithm for Hardware Acceleration of MEDS (코드 기반 양자 내성 암호 MEDS 알고리즘의 하드웨어 가속을 위한 부채널 공격 연구 동향 분석)

  • Yunji Lee;Yongseok Lee;Yunheung Paek
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2024.05a
    • /
    • pp.367-370
    • /
    • 2024
  • 양자컴퓨터 시대가 눈앞에 도래한 지금 차세대 암호로 주목받고 있는 양자 내성 암호는 다양한 수학적 알고리즘에 안전성을 기반하고 있으나 이 안전성을 위협하는 대표적인 공격 기법 중 하나인 부채널 분석 공격에 대응하기 위한 노력들이 계속되어 왔다. 이 논문에서는 코드 기반 양자 내성 암호를 중심으로 알고리즘에 위협적인 부채널 분석 공격에 대한 연구 동향을 분석하였다. 그리고 NIST 에서 PQC 표준화를 위해 Round 를 진행 중인 후보 중 하나인 코드 기반 알고리즘 MEDS 에 대해 소개하고, MEDS 알고리즘의 최적화를 위해 기존에 연구되었던 코드 기반 암호에 대한 부채널 분석 공격 대응 측면에서의 알고리즘의 안전성 확보라는 보안 비용과 하드웨어 가속 등을 통한 성능 향상이 적절한 조화를 이룰 수 있도록 설계하기 위한 방안에 대해 알아보았다.

Selectivity Estimation using the Generalized Cumulative Density Histogram (일반화된 누적밀도 히스토그램을 이용한 공간 선택율 추정)

  • Chi, Jeong-Hee;Kim, Sang-Ho;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
    • /
    • v.11D no.4
    • /
    • pp.983-990
    • /
    • 2004
  • Multiple-count problem is occurred when rectangle objects span across several buckets. The CD histogram is a technique which selves this problem by keeping four sub-histograms corresponding to the four points of rectangle. Although It provides exact results with constant response time, there is still a considerable issue. Since it is based on a query window which aligns with a given grid, a number of errors nay be occurred when it is applied to real applications. In this paper, we propose selectivity estimation techniques using the generalized cumulative density histogram based on two probabilistic models : \circled1 probabilistic model which considers the query window area ratio, \circled2 probabilistic model which considers intersection area between a given grid and objects. Our method has the capability of eliminating an impact of the restriction on query window which the existing cumulative density histogram has. We experimented with real datasets to evaluate the proposed methods. Experimental results show that the proposed technique is superior to the existing selectivity estimation techniques. Furthermore, selectivity estimation technique based on probabilistic model considering the intersection area is very accurate(less than 5% errors) at 20% query window. The proposed techniques can be used to accurately quantify the selectivity of the spatial range query on rectangle objects.

Optimum conditions for artificial neural networks to simulate indicator bacteria concentrations for river system (하천의 지표 미생물 모의를 위한 인공신경망 최적화)

  • Bae, Hun Kyun
    • Journal of Korea Water Resources Association
    • /
    • v.54 no.spc1
    • /
    • pp.1053-1060
    • /
    • 2021
  • Current water quality monitoring systems in Korea carried based on in-situ grab sample analysis. It is difficult to improve the current water quality monitoring system, i.e. shorter sampling period or increasing sampling points, because the current systems are both cost- and labor-intensive. One possible way to improve the current water quality monitoring system is to adopt a modeling approach. In this study, a modeling technique was introduced to support the current water quality monitoring system, and an artificial neural network model, the computational tool which mimics the biological processes of human brain, was applied to predict water quality of the river. The approach tried to predict concentrations of Total coliform at the outlet of the river and this showed, somewhat, poor estimations since concentrations of Total coliform were rapidly fluctuated. The approach, however, could forecast whether concentrations of Total coliform would exceed the water quality standard or not. As results, modeling approaches is expected to assist the current water quality monitoring system if the approach is applied to judge whether water quality factors could exceed the water quality standards or not and this would help proper water resource managements.

XML View Indexing Using an RDBMS based XML Storage System (관계 DBMS 기반 XML 저장시스템 상에서의 XML 뷰 인덱싱)

  • Park Dae-Sung;Kim Young-Sung;Kang Hyunchul
    • Journal of Internet Computing and Services
    • /
    • v.6 no.4
    • /
    • pp.59-73
    • /
    • 2005
  • Caching query results and reusing them in processing of subsequent queries is an important query optimization technique. Materialized view and view indexing are the representative examples of such a technique. The two schemes had received much attention for relational databases, and have been investigated for XML data since XML emerged as the standard for data exchange on the Web. In XML view indexing, XML view xv which is the result of an XML query is represented as an XML view index(XVI), a structure containing the identifiers of xv's underlying XML elements as well as the information on xv. Since XVI for xv stores just the identifiers of the XML elements not the elements themselves, when xv is requested, its XVI should be materialized against xv's underlying XML documents. In this paper, we address the problem of integrating an XML view index management system with an RDBMS based XML storage system. The proposed system was implemented in Java on Windows 2000 Server with each of two different commercial RDBMSs, and used in evaluating performance improvement through XML view indexing as well as its overheads. The experimental results revealed that XML view indexing was very effective with an RDBMS based XML storage system while its overhead was negligible.

  • PDF

A3V 10b 33 MHz Low Power CMOS A/D Converter for HDTV Applications (HDTV 응용을 위한 3V 10b 33MHz 저전력 CMOS A/D 변환기)

  • Lee, Kang-Jin;Lee, Seung-Hoon
    • Journal of IKEEE
    • /
    • v.2 no.2 s.3
    • /
    • pp.278-284
    • /
    • 1998
  • This paper describes a l0b CMOS A/D converter (ADC) for HDTV applications. The proposed ADC adopts a typical multi-step pipelined architecture. The proposed circuit design techniques are as fo1lows: A selective channel-length adjustment technique for a bias circuit minimizes the mismatch of the bias current due to the short channel effect by supply voltage variations. A power reduction technique for a high-speed two-stage operational amplifier decreases the power consumption of amplifiers with wide bandwidths by turning on and off bias currents in the suggested sequence. A typical capacitor scaling technique optimizes the chip area and power dissipation of the ADC. The proposed ADC is designed and fabricated in s 0.8 um double-poly double-metal n-well CMOS technology. The measured differential and integral nonlinearities of the prototype ADC show less than ${\pm}0.6LSB\;and\;{\pm}2.0LSB$, respectively. The typical ADC power consumption is 119 mW at 3 V with a 40 MHz sampling rate, and 320 mW at 5 V with a 50 MHz sampling rate.

  • PDF

Total Degradation Performance Evaluation of the Time- and Frequency-Domain Clipping in OFDM Systems (OFDM 시스템에서 시간 및 주파수 영역 클리핑의 Total Degradation 성능평가)

  • Han, Chang-Sik;Seo, Man-Jung;Im, Sung-Bin
    • Journal of the Institute of Electronics Engineers of Korea TC
    • /
    • v.44 no.7 s.361
    • /
    • pp.17-22
    • /
    • 2007
  • OFDM (Orthogonal Frequency Division Multiplexing) is a special case of multicarrier transmission, where a single data stream is transmitted over a number of lower-rate subcarrier. One of the main reasons to use OFDM is to increase robustness against frequency-selective fading or narrowband interference. Unfortunately, an OFDM signal consists of a number of independently modulated subcarriers, which can give a large PAPR (Peak-to-Average Power Ratio) when added up coherently. In this paper, we investigate the performance of a simple PAPR reduction scheme, which requires no change of a receiver structure or no additional information transmission. The approach we employed is clipping in the time and frequency domains. The time-domain clipping is carried out with a predetermined clipping level while the frequency-domain clipping is done within EVM (Error Vector Magnitude). This approach is suboptimal with lower computational complexity compared to the optimal method. This evaluation is carried out on the OFDM system with an nonlinear amplifier. The simulation results demonstrated that the PAPR reduction algorithm is one of ways to reduce the effects of the nonlinear distortion of an HPA (High Power Amplifier).

RFID Tag Identification with Scalability Using SP-Division Algorithm on the Grid Environment (그리드 환경에서 SP분할 알고리즘을 이용한 확장성 있는 RFID 태그 판별)

  • Shin, Myeong-Sook;Ahn, Seong-Soo;Lee, Joon
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.13 no.10
    • /
    • pp.2105-2112
    • /
    • 2009
  • Recently RFID system has been adopted in various fields rapidly. However, we ought to solve the problem of privacy invasion that can be occurred by obtaining information of RFID Tag without any permission for popularization of RFID system To solve the problems, it is Ohkubo et al.'s Hash-Chain Scheme which is the safest method. However, this method has a problem that requesting lots of computing process because of increasing numbers of Tag. Therefore, We suggest the way (process) satisfied with all necessary security of Privacy Protection Shreme and decreased in Tag Identification Time in this paper. First, We'll suggest the SP-Division Algorithm seperating SPs using the Performance Measurement consequence of each node after framing the program to create Hash-Chain Calculated table to get optimized performance because of character of the grid environment comprised of heterogeneous system. If we compare consequence fixed the number of nodes to 4 with a single node, equal partition, and SP partition, when the total number of SPs is 1000, 40%, 49%, when the total number of SPs is 2000, 42%, 51%, when the total number of SPs is 3000, 39%, 49%, and when the total number of SPs is 4000, 46%, 56% is improved.

Adaptive Beamwidth Control Technique for Low-orbit Satellites for QoS Performance improvement based on Next Generation Military Mobile Satellite Networks (차세대 군 모바일 위성 네트워크 QoS 성능 향상을 위한 저궤도 위성 빔폭 적응적 제어 기법)

  • Jang, Dae-Hee;Hwang, Yoon-Ha;Chung, Jong-Moon
    • Journal of Internet Computing and Services
    • /
    • v.21 no.6
    • /
    • pp.1-12
    • /
    • 2020
  • Low-Orbit satellite mobile networks can provide services through miniaturized terminals with low transmission power, which can be used as reliable means of communication in the national public disaster network and defense sector. However, the high traffic environment in the emergency preparedness situation increases the new call blocking probability and the handover failure probability of the satellite network, and the increase of the handover failure probability affects the QoS because low orbit satellites move in orbit at a very high speed. Among the channel allocation methods of satellite communication, the FCA shows relatively better performance in a high traffic environment than DCA and is suitable for emergency preparedness situations, but in order to optimize QoS when traffic increases, the new call blocking and the handover failure must be minimized. In this paper, we propose LEO-DBC (LEO satellite dynamic beam width control) technique, which improves QoS by adaptive adjustment of beam width of low-orbit satellites and call time of terminals by improving FCA-QH method. Through the LEO-DBC technique, it is expected that the QoS of the mobile satellite communication network can be optimally maintained in high traffic environments in emergency preparedness situations.

Semantic Segmentation of the Submerged Marine Debris in Undersea Images Using HRNet Model (HRNet 기반 해양침적쓰레기 수중영상의 의미론적 분할)

  • Kim, Daesun;Kim, Jinsoo;Jang, Seonwoong;Bak, Suho;Gong, Shinwoo;Kwak, Jiwoo;Bae, Jaegu
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.6_1
    • /
    • pp.1329-1341
    • /
    • 2022
  • Destroying the marine environment and marine ecosystem and causing marine accidents, marine debris is generated every year, and among them, submerged marine debris is difficult to identify and collect because it is on the seabed. Therefore, deep-learning-based semantic segmentation was experimented on waste fish nets and waste ropes using underwater images to identify efficient collection and distribution. For segmentation, a high-resolution network (HRNet), a state-of-the-art deep learning technique, was used, and the performance of each optimizer was compared. In the segmentation result fish net, F1 score=(86.46%, 86.20%, 85.29%), IoU=(76.15%, 75.74%, 74.36%), For the rope F1 score=(80.49%, 80.48%, 77.86%), IoU=(67.35%, 67.33%, 63.75%) in the order of adaptive moment estimation (Adam), Momentum, and stochastic gradient descent (SGD). Adam's results were the highest in both fish net and rope. Through the research results, the evaluation of segmentation performance for each optimizer and the possibility of segmentation of marine debris in the latest deep learning technique were confirmed. Accordingly, it is judged that by applying the latest deep learning technique to the identification of submerged marine debris through underwater images, it will be helpful in estimating the distribution of marine sedimentation debris through more accurate and efficient identification than identification through the naked eye.