We are proud to say that a Linaro developer - Krzysztof Kozlowski - is the most active developer by changesets for 2022. In LWN’s latest development statistics, they also look at who has been most active throughout the year. In this blog we have asked Linaro developers to talk about the work they have done which is featured in this release. 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.The 6.1 Linux Kernel was released last week and featured Linaro yet again in LWN’s lists for most active developers and most active employers. We further devise several enhancements to eliminate superfluous evaluations for multithreaded processes, so the selection procedure is more efficient. This has less influence on data mapping and thread mapping for the thread group. The thread is selected for which its thread group has the least exclusive thread distribution, and thread members are distributed more evenly on nodes. 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. This study focuses on improving inter-node load balancing for multithreaded applications. Threads to be migrated must be selected effectively and efficiently since the related operations run in the critical path of the kernel scheduler. Remote memory access is required for a thread to access memory on the previous node, which degrades performance. 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. NUMA multi-core systems divide system resources into several nodes. The VNF and NFVI architecture model with performance prediction is successfully validated against the measurement results obtained in emulated environment and used to predict optimal system configurations and maximal throughput results for different CPUs. The modeling parameters are derived from the cumulative packet processing cost obtained by measurements for collocated EAs on the CPU core hosting the bottleneck EA. Performing measurements and observing linearity of the measured results open the possibility to apply model calibration technique to achieve general VNF and NFVI architecture model with performance prediction and environment setup optimization. EAs are derived from the elements and packet processing principles in NFVIs and VNFs based on Linux kernel. EA is defined as a software execution unit that can run isolated on a compute resource (CPU core). The model arises from the methodology for performance evaluation and modeling based on execution area (EA) distribution by CPU core pinning. This study introduces empirical throughput prediction model for the virtual network function (VNF) and network function virtualization infrastructure (NFVI) architectures based on Linux kernel. Network function virtualization (NFV) is a concept aimed at achieving telecom grade cloud ecosystem for new-generation networks focusing on capital and operational expenditure (CAPEX and OPEX) savings. The frameworks chosen to be used in these experiments are Linux Text Project (LTP), KEDR, Linux Fault-Injection (LFI), and SCSI. The following paper highlights the comparison of different approaches and techniques used for such fault injection to test Linux kernel modules that include simulating low resource conditions and detecting memory leaks. Various fault injection frameworks have been analyzed over the Linux kernel to simulate such detection. A standard method for performing such experiments is to generate synthetic faults and study the effects. ‘Artificial introduction of some random faults during normal tests’ is the only known approach to such mystifying problems. Since the rarity and unpredictability of such events are pretty high, thus the localization and detection of Linux kernel, device drivers, file system modules errors become unfathomable. To test the behavior of the Linux kernel module, device drivers and file system in a faulty situation, scientists tried to inject faults in different artificial environments.
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