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MLB: A Memory-aware Load Balancing Method for Mitigating Memory Contention : 메모리 경쟁을 완화 시킬 수 있는 메모리 인지 로드 밸런스 기법
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- Authors
- Advisor
- 엄현상
- Major
- 공과대학 전기·컴퓨터공학부
- Issue Date
- 2014-02
- Publisher
- 서울대학교 대학원
- Keywords
- Multicore processors ; shared resource contention ; load balancing ; dynamicity ; SMP platform
- Description
- 학위논문 (석사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 엄현상.
- Abstract
- Most of the current CPUs have not single cores, but multicores integrated in
the Symmetric MultiProcessing (SMP) architecture, which share the resources
such as Last Level Cache (LLC) and Integrated Memory Controller (IMC).
On the SMP platforms, the contention for the resources may lead to huge
performance degradation. To mitigate the contention, various methods were
developed
most of these methods focus on finding which tasks share the same
resource assuming that a task is the sole owner of a CPU core. However, task
arrival patterns and the demand for resources in the current server environment
are highly dynamic
hence, tasks, the number of which is larger than
that of CPU cores, can be executed simultaneously on a CPU. In order to
mitigate contention for memory subsystems in such multitasking cases, dealing
with the dynamicity of resource demand, we have devised a Memory-aware
Load Balancing (MLB) method. MLB dynamically recogrnizes contention by
using simple contention models and performs inter-core task migration to mitigate
the contention. We have evaluated MLB on an Intel i7-2600 (desktop-level
CPU) and a Xeon E5-2690 (server-level CPU), and found that our approach
can be effectively taken in an adaptive manner, leading to noticeable performance
improvements of memory intensive tasks (about 15% in best case) on the
different CPU platforms. Also, MLB can achieve performance improvements in
CPU-GPU communication in discrete GPU systems.
- Language
- English
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