scholarly journals Analysis of the Linux Kernel Evolution Using Code Clone Coverage

2007 ◽  
Author(s):  
Simone Livieri ◽  
Yoshiki Higo ◽  
Makoto Matsushita ◽  
Katsuro Inoue
Keyword(s):  
Linux Kernel ◽  
Code Clone

CODE CLONE DETECTION USING OBJECT ORIENTED METRICS

2020 ◽  
Vol 9 (6) ◽  
pp. 3925-3931
Author(s):  
S. Sharma ◽  
D. Rattan ◽  
K. Singh
Keyword(s):  
Object Oriented ◽  
Clone Detection ◽  
Code Clone ◽  
Object Oriented Metrics

Machine learning for load balancing in the Linux kernel

2020 ◽  
Author(s):  
Jingde Chen ◽  
Subho S. Banerjee ◽  
Zbigniew T. Kalbarczyk ◽  
Ravishankar K. Iyer
Keyword(s):  
Machine Learning ◽  
Load Balancing ◽  
Linux Kernel

Open-source tools and benchmarks for code-clone detection

2020 ◽  
Vol 19 (4) ◽  
pp. 28-39 ◽  
Author(s):  
Andrew Walker ◽  
Tomas Cerny ◽  
Eungee Song
Keyword(s):  
Open Source ◽  
Clone Detection ◽  
Code Clone

RCU Usage In the Linux Kernel

2020 ◽  
Vol 54 (1) ◽  
pp. 47-63
Author(s):  
Paul E. McKenney ◽  
Joel Fernandes ◽  
Silas Boyd-Wickizer ◽  
Jonathan Walpole
Keyword(s):  
Linux Kernel

scholarly journals Thread-Aware Mechanism to Enhance Inter-Node Load Balancing for Multithreaded Applications on NUMA Systems

2021 ◽  
Vol 11 (14) ◽  
pp. 6486
Author(s):  
Mei-Ling Chiang ◽  
Wei-Lun Su
Keyword(s):  
Load Balancing ◽  
Critical Path ◽  
Selection Procedure ◽  
Remote Memory ◽  
Data Mapping ◽  
Linux Kernel ◽  
Access Memory ◽  
Selection Policy ◽  
Benchmark Suite ◽  
Thread Mapping

NUMA multi-core systems divide system resources into several nodes. When an imbalance in the load between cores occurs, the kernel scheduler’s load balancing mechanism then migrates threads between cores or across NUMA nodes. Remote memory access is required for a thread to access memory on the previous node, which degrades performance. Threads to be migrated must be selected effectively and efficiently since the related operations run in the critical path of the kernel scheduler. This study focuses on improving inter-node load balancing for multithreaded applications. We propose a thread-aware selection policy that considers the distribution of threads on nodes for each thread group while migrating one thread for inter-node load balancing. The thread is selected for which its thread group has the least exclusive thread distribution, and thread members are distributed more evenly on nodes. This has less influence on data mapping and thread mapping for the thread group. We further devise several enhancements to eliminate superfluous evaluations for multithreaded processes, so the selection procedure is more efficient. The experimental results for the commonly used PARSEC 3.0 benchmark suite show that the modified Linux kernel with the proposed selection policy increases performance by 10.7% compared with the unmodified Linux kernel.

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