2007Unpublished venueRequires access

An Adaptive Shared/Private NUCA Cache Partitioning Scheme for Chip Multiprocessors

Haakon Dybdahl, Per Stenström

Open publisher page 141 citations

Abstract

The significant speed-gap between processor and memory and the limited chip memory bandwidth make last-level cache performance crucial for future chip multiprocessors. To use the capacity of shared last-level caches efficiently and to allow for a short access time, proposed non-uniform cache architectures (NUCAs) are organized into per-core partitions. If a core runs out of cache space, blocks are typically relocated to nearby partitions, thus managing the cache as a shared cache. This uncontrolled sharing of all resources may unfortunately result in pollution that degrades performance. We propose a novel non-uniform cache architecture in which the amount of cache space that can be shared among the cores is controlled dynamically. The adaptive scheme estimates, continuously, the effect of increasing/decreasing the shared partition size on the overall performance. We show that our scheme outperforms a private and shared cache organization as well as a hybrid NUCA organization in which blocks in a local partition can spill over to neighbor core partitions

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What this paper is about

The significant speed-gap between processor and memory and the limited chip memory bandwidth make last-level cache performance crucial for future chip multiprocessors. To use the capacity of shared last-level caches efficiently and to allow for a short access time, proposed non-uniform cache architectures (NUCAs) are organized into per-core partitions. If a core runs out of cache space, blocks are typically relocated to nearby partitions, thus managing the cache as a shared cache. This uncontrolled sharing of all resources may unfortunately result in pollution that degrades performance. We propose a novel non-uniform cache architecture in which the amount of cache space that can be shared among the cores is controlled dynamically. The adaptive scheme estimates, continuously, the effect of increasing/decreasing the shared partition size on the overall performance. We show that our scheme outperforms a private and shared cache organization as well as a hybrid NUCA organization in which blocks in a local partition can spill over to neighbor core partitions

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Available abstract

The significant speed-gap between processor and memory and the limited chip memory bandwidth make last-level cache performance crucial for future chip multiprocessors. To use the capacity of shared last-level caches efficiently and to allow for a short access time, proposed non-uniform cache architectures (NUCAs) are organized into per-core partitions. If a core runs out of cache space, blocks are typically relocated to nearby partitions, thus managing the cache as a shared cache. This uncontrolled sharing of all resources may unfortunately result in pollution that degrades performance. We propose a novel non-uniform cache architecture in which the amount of cache space that can be shared among the cores is controlled dynamically. The adaptive scheme estimates, continuously, the effect of increasing/decreasing the shared partition size on the overall performance. We show that our scheme outperforms a private and shared cache organization as well as a hybrid NUCA organization in which blocks in a local partition can spill over to neighbor core partitions

Key concepts: Computer science, Cache, Cache pollution, Smart Cache, Cache invalidation, Cache coloring, Parallel computing, Cache algorithms

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