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dc.contributor.authorWu, Meng-Ju
dc.contributor.authorYeung, Donald
dc.date.accessioned2009-11-25T17:17:30Z
dc.date.available2009-11-25T17:17:30Z
dc.date.issued2009-11-25
dc.identifier.urihttp://hdl.handle.net/1903/9739
dc.description.abstractDue to power constraints, computer architects will exploit TLP instead of ILP for future performance gains. Today, 4-8 state-of-the-art cores or 10s of smaller cores can fit on a single die. For the foreseeable future, the number of cores will likely double with each successive processor generation. Hence, CMPs with 100s of cores-so-called large-scale chip multiprocessors (LCMPs)-will become a reality after only 2 or 3 generations. Unfortunately, simply scaling the number of on-chip cores alone will not guarantee improved performance. In addition, effectively utilizing all of the cores is also necessary. Perhaps the greatest threat to processor utilization will be the overhead incurred waiting on the memory system, especially as on-chip concurrency scales to 100s of threads. In particular, remote cache bank access and off-chip bandwidth contention are likely to be the most significant obstacles to scaling memory performance. This paper conducts an in-depth study of CMP scalability for parallel programs. We assume a tiled CMP in which tiles contain a simple core along with a private L1 cache and a local slice of a shared L2 cache. Our study considers scaling from 1-256 cores and 4-128MB of total L2 cache, and addresses several issues related to the impact of scaling on off-chip bandwidth and on-chip communication. In particular, we find off-chip bandwidth increases linearly with core count, but the rate of increase reduces dramatically once enough L2 cache is provided to capture inter-thread sharing. Our results also show for the range 1-256 cores, there should be ample on-chip bandwidth to support the communication requirements of our benchmarks. Finally, we find that applications become off-chip limited when their L2 cache miss rates exceed some minimum threshold. Moreover, we expect off-chip overheads to dominate on-chip overheads for memory intensive programs and LCMPs with aggressive cores.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesUMIACS;UMIACS-TR-2009-16
dc.titleScaling Single-Program Performance on Large-Scale Chip Multiprocessorsen_US
dc.typeTechnical Reporten_US


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