RADAR: Runtime-assisted dead region management for last-level caches
Paper in proceedings, 2016

Last-level caches (LLCs) bridge the processor/memory speed gap and reduce energy consumed per access. Unfortunately, LLCs are poorly utilized because of the relatively large occurrence of dead blocks. We propose RADAR, a hybrid static/dynamic dead-block management technique that can accurately predict and evict dead blocks in LLCs. RADAR does dead-block prediction and eviction at the granularity of address regions supported in many of today's task-parallel programming models. The runtime system utilizes static control-flow information about future region accesses in conjunction with past region access patterns to make accurate predictions about dead regions. The runtime system instructs the cache to demote and eventually evict blocks belonging to such dead regions. This paper considers three RADAR schemes to predict dead regions: a scheme that uses control-flow information provided by the programming model (Look-ahead), a history-based scheme (Look-back) and a combined scheme (Look-ahead and Look-back). Our evaluation shows that, on average, all RADAR schemes outperform state-of-the-art hardware dead-block prediction techniques, whereas the combined scheme always performs best.

Author

Madhavan Manivannan

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Vasileios Papaefstathiou

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Miquel Pericas

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Per Stenström

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

22nd IEEE International Symposium on High Performance Computer Architecture, HPCA 2016, Barcelona, Spain, 12-16 March 2016

1530-0897 (ISSN)

644-656

Subject Categories

Computer Engineering

Areas of Advance

Information and Communication Technology

DOI

10.1109/HPCA.2016.7446101

ISBN

978-1-4673-9211-2

More information

Created

10/8/2017