TY - GEN
T1 - Enabling software management for multicore caches with a lightweight hardware support
AU - Lin, Jiang
AU - Lu, Qingda
AU - Ding, Xiaoning
AU - Zhang, Zhao
AU - Zhang, Xiaodong
AU - Sadayappan, P.
PY - 2009
Y1 - 2009
N2 - The management of shared caches in multicore processors is a critical and challenging task. Many hardware and OS-based methods have been proposed. However, they may be hardly adopted in practice due to their non-trivial overheads, high complexities, and/or limited abilities to handle increasingly complicated scenarios of cache contention caused by many-cores. In order to turn cache partitioning methods into reality in the management of multicore processors, we propose to provide an affordable and lightweight hardware support to coordinate with OS-based cache management policies. The proposed methods are scalable to many-cores, and perform comparably with other proposed hardware solutions, but have much lower overheads, therefore can be easily adopted in commodity processors. Having conducted extensive experiments with 37 multi-programming workloads, we show the effectiveness and scalability of the proposed methods. For example on 8-core systems, one of our proposed policies improves performance over LRU-based hardware cache management by 14.5% on average.
AB - The management of shared caches in multicore processors is a critical and challenging task. Many hardware and OS-based methods have been proposed. However, they may be hardly adopted in practice due to their non-trivial overheads, high complexities, and/or limited abilities to handle increasingly complicated scenarios of cache contention caused by many-cores. In order to turn cache partitioning methods into reality in the management of multicore processors, we propose to provide an affordable and lightweight hardware support to coordinate with OS-based cache management policies. The proposed methods are scalable to many-cores, and perform comparably with other proposed hardware solutions, but have much lower overheads, therefore can be easily adopted in commodity processors. Having conducted extensive experiments with 37 multi-programming workloads, we show the effectiveness and scalability of the proposed methods. For example on 8-core systems, one of our proposed policies improves performance over LRU-based hardware cache management by 14.5% on average.
KW - Cache management
KW - Multicore
KW - Shared cache
UR - http://www.scopus.com/inward/record.url?scp=74049158610&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=74049158610&partnerID=8YFLogxK
U2 - 10.1145/1654059.1654074
DO - 10.1145/1654059.1654074
M3 - Conference contribution
AN - SCOPUS:74049158610
SN - 9781605587448
T3 - Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis, SC '09
BT - Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis, SC '09
T2 - Conference on High Performance Computing Networking, Storage and Analysis, SC '09
Y2 - 14 November 2009 through 20 November 2009
ER -