Access Pattern

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Abhik Roychoudhury - One of the best experts on this subject based on the ideXlab platform.

  • Scope-Aware Data Cache Analysis for WCET Estimation
    2011 17th IEEE Real-Time and Embedded Technology and Applications Symposium, 2011
    Co-Authors: Bach Khoa Huynh, Lei Ju, Abhik Roychoudhury
    Abstract:

    Caches are widely used in modern computer systems to bridge the increasing gap between processor speed and memory Access time. On the other hand, presence of caches, especially data caches, complicates the static worst case execution time (WCET) analysis. Access Pattern analysis (e.g., cache miss equations) are applicable to only a specific class of programs, where all array Accesses must have predictable Access Patterns. Abstract interpretation-based methods (must/persistence analysis) determines possible cache conflicts based on coarse-grained memory Access information from address analysis, which usually leads to significantly pessimistic estimation. In this paper, we first present a refined persistence analysis method which fixes the potential underestimation problem in the original persistence analysis. Based on our new persistence analysis, we propose a framework to combine Access Pattern analysis and abstract interpretation for accurate data cache analysis. We capture the dynamic behavior of a memory Access by computing its temporal scope (the loop iterations where a given memory block is Accessed for a given data reference) during address analysis. Temporal scopes as well as loop hierarchy structure (the static scopes) are integrated and utilized to achieve a more precise abstract cache state modeling. Experimental results shows that our proposed analysis obtains up to 74% reduction in the WCET estimates compared to existing data cache analysis.

  • IEEE Real-Time and Embedded Technology and Applications Symposium - Scope-Aware Data Cache Analysis for WCET Estimation
    2011 17th IEEE Real-Time and Embedded Technology and Applications Symposium, 2011
    Co-Authors: Bach Khoa Huynh, Lei Ju, Abhik Roychoudhury
    Abstract:

    Caches are widely used in modern computer systems to bridge the increasing gap between processor speed and memory Access time. On the other hand, presence of caches, especially data caches, complicates the static worst case execution time (WCET) analysis. Access Pattern analysis (e.g., cache miss equations) are applicable to only a specific class of programs, where all array Accesses must have predictable Access Patterns. Abstract interpretation-based methods (must/persistence analysis) determines possible cache conflicts based on coarse-grained memory Access information from address analysis, which usually leads to significantly pessimistic estimation. In this paper, we first present a refined persistence analysis method which fixes the potential underestimation problem in the original persistence analysis. Based on our new persistence analysis, we propose a framework to combine Access Pattern analysis and abstract interpretation for accurate data cache analysis. We capture the dynamic behavior of a memory Access by computing its temporal scope (the loop iterations where a given memory block is Accessed for a given data reference) during address analysis. Temporal scopes as well as loop hierarchy structure (the static scopes) are integrated and utilized to achieve a more precise abstract cache state modeling. Experimental results shows that our proposed analysis obtains up to 74% reduction in the WCET estimates compared to existing data cache analysis.

Bach Khoa Huynh - One of the best experts on this subject based on the ideXlab platform.

  • Scope-Aware Data Cache Analysis for WCET Estimation
    2011 17th IEEE Real-Time and Embedded Technology and Applications Symposium, 2011
    Co-Authors: Bach Khoa Huynh, Lei Ju, Abhik Roychoudhury
    Abstract:

    Caches are widely used in modern computer systems to bridge the increasing gap between processor speed and memory Access time. On the other hand, presence of caches, especially data caches, complicates the static worst case execution time (WCET) analysis. Access Pattern analysis (e.g., cache miss equations) are applicable to only a specific class of programs, where all array Accesses must have predictable Access Patterns. Abstract interpretation-based methods (must/persistence analysis) determines possible cache conflicts based on coarse-grained memory Access information from address analysis, which usually leads to significantly pessimistic estimation. In this paper, we first present a refined persistence analysis method which fixes the potential underestimation problem in the original persistence analysis. Based on our new persistence analysis, we propose a framework to combine Access Pattern analysis and abstract interpretation for accurate data cache analysis. We capture the dynamic behavior of a memory Access by computing its temporal scope (the loop iterations where a given memory block is Accessed for a given data reference) during address analysis. Temporal scopes as well as loop hierarchy structure (the static scopes) are integrated and utilized to achieve a more precise abstract cache state modeling. Experimental results shows that our proposed analysis obtains up to 74% reduction in the WCET estimates compared to existing data cache analysis.

  • IEEE Real-Time and Embedded Technology and Applications Symposium - Scope-Aware Data Cache Analysis for WCET Estimation
    2011 17th IEEE Real-Time and Embedded Technology and Applications Symposium, 2011
    Co-Authors: Bach Khoa Huynh, Lei Ju, Abhik Roychoudhury
    Abstract:

    Caches are widely used in modern computer systems to bridge the increasing gap between processor speed and memory Access time. On the other hand, presence of caches, especially data caches, complicates the static worst case execution time (WCET) analysis. Access Pattern analysis (e.g., cache miss equations) are applicable to only a specific class of programs, where all array Accesses must have predictable Access Patterns. Abstract interpretation-based methods (must/persistence analysis) determines possible cache conflicts based on coarse-grained memory Access information from address analysis, which usually leads to significantly pessimistic estimation. In this paper, we first present a refined persistence analysis method which fixes the potential underestimation problem in the original persistence analysis. Based on our new persistence analysis, we propose a framework to combine Access Pattern analysis and abstract interpretation for accurate data cache analysis. We capture the dynamic behavior of a memory Access by computing its temporal scope (the loop iterations where a given memory block is Accessed for a given data reference) during address analysis. Temporal scopes as well as loop hierarchy structure (the static scopes) are integrated and utilized to achieve a more precise abstract cache state modeling. Experimental results shows that our proposed analysis obtains up to 74% reduction in the WCET estimates compared to existing data cache analysis.

Guntur Ravindra - One of the best experts on this subject based on the ideXlab platform.

  • adaptive encoding of zoomable video streams based on user Access Pattern
    Signal Processing-image Communication, 2012
    Co-Authors: Ngo Quang Minh Khiem, Guntur Ravindra
    Abstract:

    Zoomable video allows users to selectively zoom and pan into regions of interest within the video for viewing at higher resolutions. Such interaction requires dynamic cropping of RoIs on the source video. We have previously explored two different ways of encoding and transmitting video to support dynamic RoI cropping: (i) Monolithic streaming uses a standard video encoder to encode the video. When an RoI is requested, the bits belonging to the RoI along with other bits required to decode the RoIs (due to encoding dependencies) are transmitted. (ii) Tile streaming divides regions in the standard video into rectangular tiles that are encoded independently. The tiles that intersect with a requested RoI are transmitted. In this paper, we consider how the bandwidth needed to transmit the RoIs can be reduced by carefully encoding the source video for each of the two encoding schemes. The goal is to support bandwidth efficient compressed domain RoI cropping in the context of virtual zoom and pan by tuning encoder parameters. Our key idea is to exploit user Access Patterns to the RoIs, and encode different regions of the video with different encoding parameters based on the popularity of the region. We show that our encoding method can reduce the expected bandwidth by up to 43% in the test video sequence which we have used.

  • Adaptive encoding of zoomable video streams based on user Access Pattern
    Signal Processing: Image Communication, 2012
    Co-Authors: Ngo Quang Minh Khiem, Guntur Ravindra, Wei Tsang Ooi
    Abstract:

    Zoomable video allows users to selectively zoom and pan into regions of interest within the video for viewing at higher resolutions. Such interaction requires dynamic cropping of RoIs on the source video. We have previously explored two different ways of encoding and transmitting video to support dynamic RoI cropping: (i) Monolithic streaming uses a standard video encoder to encode the video. When an RoI is requested, the bits belonging to the RoI along with other bits required to decode the RoIs (due to encoding dependencies) are transmitted. (ii) Tile streaming divides regions in the standard video into rectangular tiles that are encoded independently. The tiles that intersect with a requested RoI are transmitted. In this paper, we consider how the bandwidth needed to transmit the RoIs can be reduced by carefully encoding the source video for each of the two encoding schemes. The goal is to support bandwidth efficient compressed domain RoI cropping in the context of virtual zoom and pan by tuning encoder parameters. Our key idea is to exploit user Access Patterns to the RoIs, and encode different regions of the video with different encoding parameters based on the popularity of the region. We show that our encoding method can reduce the expected bandwidth by up to 43% in the test video sequence which we have used. © 2011 Elsevier B.V. All rights reserved.

G. Raju - One of the best experts on this subject based on the ideXlab platform.

  • A Novel Weighted Support Method for Access Pattern Mining
    2020
    Co-Authors: G. Raju, Achuthan Nair Rajimol
    Abstract:

    Sequential Pattern Mining is an important data mining technique that finds out all frequent sequential Patterns in a sequence database. Applications in wide range of important domains make Sequential Pattern Mining an interesting area of research. Conventional approach for sequential Pattern mining treats each and every item in the sequence with equal importance and thus fails to reflect the individual significance of items. Weighted Sequential Pattern Mining is an approach that treats different items in the sequences with different weights so as to reflect the importance of each item. Thus, weighted method models real life sequence database in a better manner and more efficient than the conventional sequential Pattern mining. Weighted sequential Pattern mining can be used to mine web Access Patterns more efficiently from web log data. This paper proposes a new weighted Access Pattern mining algorithm to mine weighted Access Patterns in a web log database. The proposed method uses frequency of user visit to give weights to web pages during the mining process. Through extensive experimental evaluation the algorithm is proved to be promising.

  • Web Access Pattern mining – a new method
    International Journal of Web Science, 2014
    Co-Authors: Achuthan Nair Rajimol, G. Raju
    Abstract:

    An efficient web Access Pattern mining algorithm, FOL-mine is presented in this paper. The FOL-mine algorithm is based on the projected database of each frequent event and eliminates the need for construction of Pattern tree. A data structure, first occurrence list (FOL), is introduced in the proposed algorithm for efficient handling of suffix building. Rebuilding of projection databases is completely eliminated in the new method. Experimental analysis of the algorithms reveals significant performance gain over other web Access Pattern mining algorithms.

  • ICDEM - Web Access Pattern mining --- a survey
    Lecture Notes in Computer Science, 2010
    Co-Authors: Achuthan Nair Rajimol, G. Raju
    Abstract:

    This article provides a survey of different Web Access Pattern Tree (WAP-tree) based methods for Web Access Pattern Mining. Web Access Pattern Mining mines complete set of Patterns that satisfy the given support threshold from a given Web Access Sequence Database. A brief discussion of basic theory and terminologies related to web Access Pattern mining are Presented. A comparison of the different methods is also given.

Lei Ju - One of the best experts on this subject based on the ideXlab platform.

  • Scope-Aware Data Cache Analysis for WCET Estimation
    2011 17th IEEE Real-Time and Embedded Technology and Applications Symposium, 2011
    Co-Authors: Bach Khoa Huynh, Lei Ju, Abhik Roychoudhury
    Abstract:

    Caches are widely used in modern computer systems to bridge the increasing gap between processor speed and memory Access time. On the other hand, presence of caches, especially data caches, complicates the static worst case execution time (WCET) analysis. Access Pattern analysis (e.g., cache miss equations) are applicable to only a specific class of programs, where all array Accesses must have predictable Access Patterns. Abstract interpretation-based methods (must/persistence analysis) determines possible cache conflicts based on coarse-grained memory Access information from address analysis, which usually leads to significantly pessimistic estimation. In this paper, we first present a refined persistence analysis method which fixes the potential underestimation problem in the original persistence analysis. Based on our new persistence analysis, we propose a framework to combine Access Pattern analysis and abstract interpretation for accurate data cache analysis. We capture the dynamic behavior of a memory Access by computing its temporal scope (the loop iterations where a given memory block is Accessed for a given data reference) during address analysis. Temporal scopes as well as loop hierarchy structure (the static scopes) are integrated and utilized to achieve a more precise abstract cache state modeling. Experimental results shows that our proposed analysis obtains up to 74% reduction in the WCET estimates compared to existing data cache analysis.

  • IEEE Real-Time and Embedded Technology and Applications Symposium - Scope-Aware Data Cache Analysis for WCET Estimation
    2011 17th IEEE Real-Time and Embedded Technology and Applications Symposium, 2011
    Co-Authors: Bach Khoa Huynh, Lei Ju, Abhik Roychoudhury
    Abstract:

    Caches are widely used in modern computer systems to bridge the increasing gap between processor speed and memory Access time. On the other hand, presence of caches, especially data caches, complicates the static worst case execution time (WCET) analysis. Access Pattern analysis (e.g., cache miss equations) are applicable to only a specific class of programs, where all array Accesses must have predictable Access Patterns. Abstract interpretation-based methods (must/persistence analysis) determines possible cache conflicts based on coarse-grained memory Access information from address analysis, which usually leads to significantly pessimistic estimation. In this paper, we first present a refined persistence analysis method which fixes the potential underestimation problem in the original persistence analysis. Based on our new persistence analysis, we propose a framework to combine Access Pattern analysis and abstract interpretation for accurate data cache analysis. We capture the dynamic behavior of a memory Access by computing its temporal scope (the loop iterations where a given memory block is Accessed for a given data reference) during address analysis. Temporal scopes as well as loop hierarchy structure (the static scopes) are integrated and utilized to achieve a more precise abstract cache state modeling. Experimental results shows that our proposed analysis obtains up to 74% reduction in the WCET estimates compared to existing data cache analysis.