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: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2012
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| Online Access: | http://psasir.upm.edu.my/id/eprint/32225/ |
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| Summary: | 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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