Coordinated Management of Processor Configuration and Cache Partitioning to Optimize Energy under QoS Constraints
Paper i proceeding, 2020

An effective way to improve energy efficiency is to throttle hardware resources to meet a certain QoS target, specified as a performance constraint, associated with all applications running on a multicore system. Prior art has proposed resource management (RM) frameworks in which the share of the last-level cache (LLC) assigned to each processor core and the voltage-frequency (VF) setting for each core is managed in a coordinated fashion to reduce energy. A drawback of such a scheme is that, while one core gives up LLC resources for another core, the performance drop must be compensated by a higher VF setting which leads to a quadratic increase in energy consumption. By allowing each core to be adapted to exploit instruction and memory-level parallelism (ILP/MLP), substantially higher energy savings are enabled.This paper proposes a coordinated RM for LLC partitioning, processor adaptation, and per-core VF scaling. A first contribution is a systematic study of the resource trade-offs enabled when trading between the three classes of resources in a coordinated fashion. A second contribution is a new RM framework that utilizes these trade-offs to save more energy. Finally, a challenge to accurately model the impact of resource throttling on performance is to predict the amount of MLP with high accuracy. To this end, the paper contributes with a mechanism that estimates the effect of MLP over different processor configurations and LLC allocations. Overall, we show that up to 18% of energy, and on average 10%, can be saved using the proposed scheme.

Performance and energy modeling

Dynamic voltage-frequency scaling

Resource management

Reconfigurable architectures

Memory level parallelism

Multicore processor

Quality of service

Cache partitioning

Författare

Mehrzad Nejat

Chalmers, Data- och informationsteknik, Datorteknik, Computer Systems

Madhavan Manivannan

Chalmers, Data- och informationsteknik, Datorteknik, Computer Systems

Miquel Pericas

Chalmers, Data- och informationsteknik, Datorteknik, Computer Systems

Per Stenström

Chalmers, Data- och informationsteknik, Datorteknik

Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium, IPDPS 2020

590-601 9139837

34th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2020
New Orleans, USA,

Ämneskategorier

Datorteknik

Inbäddad systemteknik

Datorsystem

Drivkrafter

Hållbar utveckling

DOI

10.1109/IPDPS47924.2020.00067

Mer information

Senast uppdaterat

2020-09-01