Development of hierarchical analytical scheduling (HAS) - a conceptual framework.

With the rapid growth of multicore processors, memory optimisation is necessary in improving the usage of cache memories. This includes efforts in improving the performance of data fetching from memory. Current prefetching algorithms depend on usage, such that items, which are not frequently us...

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Main Authors: Harun, Harlisya, Mohd. Sharif, M. F., Mariun, N., Chulan, Ungku, Khazani, Khamizon
Format: Conference or Workshop Item
Language:English
Published: 2012
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author Harun, Harlisya
Mohd. Sharif, M. F.
Mariun, N.
Chulan, Ungku
Khazani, Khamizon
author_facet Harun, Harlisya
Mohd. Sharif, M. F.
Mariun, N.
Chulan, Ungku
Khazani, Khamizon
author_sort Harun, Harlisya
collection UPM
description With the rapid growth of multicore processors, memory optimisation is necessary in improving the usage of cache memories. This includes efforts in improving the performance of data fetching from memory. Current prefetching algorithms depend on usage, such that items, which are not frequently used, will be removed. This can cause potential delay when infrequent items are removed, even when they are needed by many other processors in the near future. To alleviate this limitation, the hierarchical analytical scheduling (HAS) model is proposed in this paper. The model works by determining the relative importance of data during cache replacement policy. HAS is based on the concept of hierarchical temporal memory (HTM), in which the scheduling is derived on the priority and similarity of data from the aspect of space and time. Implemented with OCTAVE, a simulation of the model is implemented to analyse its behaviour in a hypothetical cache management scenario.
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spelling upm.eprints-322252014-10-15T07:21:57Z http://psasir.upm.edu.my/id/eprint/32225/ Development of hierarchical analytical scheduling (HAS) - a conceptual framework. Harun, Harlisya Mohd. Sharif, M. F. Mariun, N. Chulan, Ungku Khazani, Khamizon With the rapid growth of multicore processors, memory optimisation is necessary in improving the usage of cache memories. This includes efforts in improving the performance of data fetching from memory. Current prefetching algorithms depend on usage, such that items, which are not frequently used, will be removed. This can cause potential delay when infrequent items are removed, even when they are needed by many other processors in the near future. To alleviate this limitation, the hierarchical analytical scheduling (HAS) model is proposed in this paper. The model works by determining the relative importance of data during cache replacement policy. HAS is based on the concept of hierarchical temporal memory (HTM), in which the scheduling is derived on the priority and similarity of data from the aspect of space and time. Implemented with OCTAVE, a simulation of the model is implemented to analyse its behaviour in a hypothetical cache management scenario. 2012 Conference or Workshop Item NonPeerReviewed Harun, Harlisya and Mohd. Sharif, M. F. and Mariun, N. and Chulan, Ungku and Khazani, Khamizon (2012) Development of hierarchical analytical scheduling (HAS) - a conceptual framework. In: 2012 UKSim-AMSS 6th European Modelling Symposium, 19-21 Nov. 2012, Parahyangan Catholic University, Bandung, Indonesia. (pp. 448-452). 10.1109/EMS.2012.76 English
spellingShingle Harun, Harlisya
Mohd. Sharif, M. F.
Mariun, N.
Chulan, Ungku
Khazani, Khamizon
Development of hierarchical analytical scheduling (HAS) - a conceptual framework.
title Development of hierarchical analytical scheduling (HAS) - a conceptual framework.
title_full Development of hierarchical analytical scheduling (HAS) - a conceptual framework.
title_fullStr Development of hierarchical analytical scheduling (HAS) - a conceptual framework.
title_full_unstemmed Development of hierarchical analytical scheduling (HAS) - a conceptual framework.
title_short Development of hierarchical analytical scheduling (HAS) - a conceptual framework.
title_sort development of hierarchical analytical scheduling has a conceptual framework
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