Multi-threaded programming is emerging very fast and memory-hungry programs need more resources so chip multiprocessorsare widely used . Accessing L1 caches beside the cores are the fastest after registers but the size of private caches cannot increase because of design, cost and technology issues . Then split I-cache and D-cache are used with shared LLC (last level cache). For a unified shared LLC, bus interface is not scalable, and it seems that distributed shared LLC (DSLLC) is a better choice , so most of papers assume a distributed shared LLC beside each core in on-chip network. Many works assume that DSLLCs are placed in all cores; however we show that this design ignores the effect of traffic congestion in the on-chip network. In fact the problem is finding optimal placement of cores, DSLLCs and even memory controllers to minimize the expected latency based on traffic load in a mesh on-chip network with fixed number of cores and total cache capacity. We try to do some analytical modeling to derive the intended cost function and then optimize it for minimum mean delay . This work is supposed to be verified using some traffic patterns that are run on CSIM simulator.
Parallel programming is emerging fast and intensive applications need more resources , so there is a huge demand for on-chip multiprocessors . Accessing L1 caches beside the cores are the fastest after registers but the size of private caches cannot increase because of design, cost and technology limits . Then split I-cache and D-cache are used with shared LLC (last level cache). For a unified shared LLC, bus interface is not scalable, and it seems that distributed shared LLC (DSLLC) is a better choice . Most of papers assume a distributed shared LLC beside each core in on-chip network. Many works assume that DSLLCs are placed in all cores; however , we will show that this design ignores the effect of traffic congestion in on-chip network. In fact , our work focuses on optimal placement of cores, DSLLCs and even memory controllers to minimize the expected latency based on traffic load in a mesh on-chip network with fixed number of cores and total cache capacity. We try to do some analytical modeling deriving intended cost function and then optimize the mean delay of the on-chip network communication . This work is supposed to be verified using some traffic patterns that are run on CSIM simulator.
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very fast and memory-hungry programs
fast and intensive applications
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so chip multiprocessorsare widely used
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issues
limits
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the problem is finding
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to derive the
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it for minimum mean delay
the mean delay of the on-chip network communication