Dynamic multicore resource management: A machine learning approach
JF Martinez, E Ipek - IEEE micro, 2009 - ieeexplore.ieee.org
A machine learning approach to multicore resource management produces self-optimizing
on-chip hardware agents capable of learning, planning, and continuously adapting to …
on-chip hardware agents capable of learning, planning, and continuously adapting to …
Sosa: Self-optimizing learning with self-adaptive control for hierarchical system-on-chip management
Resource management strategies for many-core systems dictate the sharing of resources
among applications such as power, processing cores, and memory bandwidth in order to …
among applications such as power, processing cores, and memory bandwidth in order to …
A survey of prediction and classification techniques in multicore processor systems
C Ababei, MG Moghaddam - IEEE Transactions on Parallel …, 2018 - ieeexplore.ieee.org
In multicore processor systems, being able to accurately predict the future provides new
optimization opportunities, which otherwise could not be exploited. For example, an oracle …
optimization opportunities, which otherwise could not be exploited. For example, an oracle …
A case for machine learning to optimize multicore performance
A Ganapathi, K Datta, A Fox, D Patterson - First USENIX Workshop on …, 2009 - usenix.org
Multicore architectures have become so complex and diverse that there is no obvious path
to achieving good performance. Hundreds of code transformations, compiler flags …
to achieving good performance. Hundreds of code transformations, compiler flags …
Predictive coordination of multiple on-chip resources for chip multiprocessors
Efficient on-chip resource management is crucial for Chip Multiprocessors (CMP) to achieve
high resource utilization and enforce system-level performance objectives. Existing multiple …
high resource utilization and enforce system-level performance objectives. Existing multiple …
Using OS observations to improve performance in multicore systems
Today's operating systems don't adequately handle the complexities of Multicore
processors. Architectural features confound existing OS techniques for task scheduling, load …
processors. Architectural features confound existing OS techniques for task scheduling, load …
Coordinated management of multiple interacting resources in chip multiprocessors: A machine learning approach
R Bitirgen, E Ipek, JF Martinez - 2008 41st IEEE/ACM …, 2008 - ieeexplore.ieee.org
Efficient sharing of system resources is critical to obtaining high utilization and enforcing
system-level performance objectives on chip multiprocessors (CMPs). Although several …
system-level performance objectives on chip multiprocessors (CMPs). Although several …
Machine learning for power, energy, and thermal management on multicore processors: A survey
Due to the high integration density and roadblock of voltage scaling, modern multicore
processors experience higher power densities than previous technology scaling nodes …
processors experience higher power densities than previous technology scaling nodes …
Machine learned machines: Adaptive co-optimization of caches, cores, and on-chip network
Modern multicore architectures require runtime optimization techniques to address the
problem of mismatches between the dynamic resource requirements of different processes …
problem of mismatches between the dynamic resource requirements of different processes …
Runtime task scheduling using imitation learning for heterogeneous many-core systems
Domain-specific systems-on-chip, a class of heterogeneous many-core systems, is
recognized as a key approach to narrow down the performance and energy-efficiency gap …
recognized as a key approach to narrow down the performance and energy-efficiency gap …