PIPP: promotion/insertion pseudo-partitioning of multi-core shared caches

By Yuejian Xie, Gabriel H. Loh. International Symposium on Computer Architecture, 2009

340 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/1ae7be5d55833e6aa53d24f620be5df9006a3558

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In Computer Networks and Communications

In Hardware and Architecture

Citations in the corpus

The evicted-address filter: A unified mechanism to address both cache pollution and thrashing (2012, methodology): “Cache partitioning is one technique that has been eUectively used to improve shared-cache performance [37, 51, 52, 56] or provide QoS in multi-core systems with shared caches [7, 15, 24, 31].”
Bubble-up: Increasing utilization in modern warehouse scale computers via sensible co-locations (2011, background): “One direction that has attracted much research attention is the management of shared cache and bandwidth through techniques such as resource partitioning [4, 20, 27–34, 38] , throttling [ 7 ] and adaptive cache replacement policies [ 14 ].”
Heracles: Improving resource efficiency at scale (2015, background): “Isolation mechanisms: There is significant work on shared cache isolation, including soft partitioning based on replacement policies [77, 78], way-partitioning [65, 64], and finegrained partitioning [68, 49, 71].”
Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures (2018, background): “Finally, one can add security features to performance-oriented cache partitioning proposals [49],[50],[51],[52], to achieve better trade-offs between security and performance.”
SHiP: Signature-based Hit Predictor for high performance caching (2011, background): “SHiP is a more sophisticated cache insertion mechanism that makes more accurate re-reference predictions than recent cache insertion policy proposals [10, 27, 32].”
Q-clouds: managing performance interference effects for QoS-aware clouds (2010, methodology): “However, perfect resource partitioning can be difficult and costly to implement, and even if accomplished, may result in inefficient use of resources [ 36 ].”