The Linux Kernel Scheduler (For Beginners) - SFO17-421Linaro
Session ID: SFO17-421
Session Name: The Linux Kernel Scheduler (For Beginners) - SFO17-421
Speaker: Viresh Kumar
Track: Power Management
★ Session Summary ★
This talk will take you through the internals of the Linux Kernel scheduler.
---------------------------------------------------
★ Resources ★
Event Page: http://connect.linaro.org/resource/sfo17/sfo17-421/
Presentation:
Video: https://www.youtube.com/watch?v=q283Wm__QQ0
---------------------------------------------------
★ Event Details ★
Linaro Connect San Francisco 2017 (SFO17)
25-29 September 2017
Hyatt Regency San Francisco Airport
---------------------------------------------------
Keyword:
'http://www.linaro.org'
'http://connect.linaro.org'
---------------------------------------------------
Follow us on Social Media
https://www.facebook.com/LinaroOrg
https://twitter.com/linaroorg
https://www.youtube.com/user/linaroorg?sub_confirmation=1
https://www.linkedin.com/company/1026961
This document provides an overview of real-time operating systems and VxWorks. It discusses key concepts such as real-time performance, deterministic execution, multitasking, task scheduling and inter-task communication methods. VxWorks is introduced as a real-time OS that supports multitasking, priorities, interrupts and inter-task communication using mechanisms like shared memory, semaphores and message queues. The document also covers task management functions and interrupt handling in VxWorks.
This document provides an overview of scheduling in Android. It discusses the architecture of Android and how it interacts with the Linux scheduler. It covers the history of Linux scheduling including the Completely Fair Scheduler (CFS) and scheduling classes. It also discusses how Android has had problems with the Linux scheduler responding quickly enough to changes, and the solutions developed to address this including new governors and control groups. Finally, it summarizes how the Android framework interacts with the Linux scheduler through system services and process scheduling policies.
The document discusses scheduling in Android. It provides an overview of the history of Linux scheduling including the Completely Fair Scheduler (CFS) and scheduling classes. It describes how CPU power management integrates with scheduling and discusses load tracking methods. The document outlines some problems Android has had with the Linux scheduler and solutions developed. It also summarizes how the Android framework interacts with and provides hints to the underlying Linux scheduler.
Process Scheduler and Balancer in Linux KernelHaifeng Li
The document discusses process scheduling in the Linux kernel. It begins with an introduction to schedulers and outlines Linux scheduler history, including round-robin, O(N), O(1), and Completely Fair schedulers. It then provides more details on the Completely Fair Scheduler's use of virtual runtime to determine process execution order and maintain fairness. The document also briefly discusses the real-time scheduler and key data structures used for scheduling like task_struct and sched_domain. It concludes with an overview of the CFS load balancer's hierarchical design and methods used to balance tasks among CPU cores.
The second part of Linux Internals covers system calls, process subsystem and inter process communication mechanisms. Understanding these services provided by Linux are essential for embedded systems engineer.
This document discusses the slides for Unit 2 of the Operating Systems course. It includes an index of lecture topics that will be covered, such as process concepts and threads, scheduling criteria and algorithms, thread scheduling, case studies of UNIX/Linux and Windows operating systems, and revision. Key concepts that will be covered include processes and threads, process state diagrams, process control blocks, CPU scheduling queues, producer-consumer problem solutions, scheduling criteria and algorithms like FCFS, SJF, priority and round robin, and thread scheduling models.
The Linux Kernel Scheduler (For Beginners) - SFO17-421Linaro
Session ID: SFO17-421
Session Name: The Linux Kernel Scheduler (For Beginners) - SFO17-421
Speaker: Viresh Kumar
Track: Power Management
★ Session Summary ★
This talk will take you through the internals of the Linux Kernel scheduler.
---------------------------------------------------
★ Resources ★
Event Page: http://connect.linaro.org/resource/sfo17/sfo17-421/
Presentation:
Video: https://www.youtube.com/watch?v=q283Wm__QQ0
---------------------------------------------------
★ Event Details ★
Linaro Connect San Francisco 2017 (SFO17)
25-29 September 2017
Hyatt Regency San Francisco Airport
---------------------------------------------------
Keyword:
'http://www.linaro.org'
'http://connect.linaro.org'
---------------------------------------------------
Follow us on Social Media
https://www.facebook.com/LinaroOrg
https://twitter.com/linaroorg
https://www.youtube.com/user/linaroorg?sub_confirmation=1
https://www.linkedin.com/company/1026961
This document provides an overview of real-time operating systems and VxWorks. It discusses key concepts such as real-time performance, deterministic execution, multitasking, task scheduling and inter-task communication methods. VxWorks is introduced as a real-time OS that supports multitasking, priorities, interrupts and inter-task communication using mechanisms like shared memory, semaphores and message queues. The document also covers task management functions and interrupt handling in VxWorks.
This document provides an overview of scheduling in Android. It discusses the architecture of Android and how it interacts with the Linux scheduler. It covers the history of Linux scheduling including the Completely Fair Scheduler (CFS) and scheduling classes. It also discusses how Android has had problems with the Linux scheduler responding quickly enough to changes, and the solutions developed to address this including new governors and control groups. Finally, it summarizes how the Android framework interacts with the Linux scheduler through system services and process scheduling policies.
The document discusses scheduling in Android. It provides an overview of the history of Linux scheduling including the Completely Fair Scheduler (CFS) and scheduling classes. It describes how CPU power management integrates with scheduling and discusses load tracking methods. The document outlines some problems Android has had with the Linux scheduler and solutions developed. It also summarizes how the Android framework interacts with and provides hints to the underlying Linux scheduler.
Process Scheduler and Balancer in Linux KernelHaifeng Li
The document discusses process scheduling in the Linux kernel. It begins with an introduction to schedulers and outlines Linux scheduler history, including round-robin, O(N), O(1), and Completely Fair schedulers. It then provides more details on the Completely Fair Scheduler's use of virtual runtime to determine process execution order and maintain fairness. The document also briefly discusses the real-time scheduler and key data structures used for scheduling like task_struct and sched_domain. It concludes with an overview of the CFS load balancer's hierarchical design and methods used to balance tasks among CPU cores.
The second part of Linux Internals covers system calls, process subsystem and inter process communication mechanisms. Understanding these services provided by Linux are essential for embedded systems engineer.
This document discusses the slides for Unit 2 of the Operating Systems course. It includes an index of lecture topics that will be covered, such as process concepts and threads, scheduling criteria and algorithms, thread scheduling, case studies of UNIX/Linux and Windows operating systems, and revision. Key concepts that will be covered include processes and threads, process state diagrams, process control blocks, CPU scheduling queues, producer-consumer problem solutions, scheduling criteria and algorithms like FCFS, SJF, priority and round robin, and thread scheduling models.
The ppt contains detail about issues and scheduling technique of real-time systems. It includes scheduling both online and offline for uniprocessor system. The applications of real-time system is also there
Distributed Task Scheduling with Akka, Kafka and CassandraDavid van Geest
https://www.youtube.com/watch?v=s3GfXTnzG_Y
Dynamically scheduled tasks are at the heart of PagerDuty's microservices. They deliver incident alerts, on-call notifications, and manage myriad administrative chores. Historically, these tasks were scheduled and run using an in-house library built on Cassandra, but that solution had begun to show its age.
Early in 2016, the Core team at PagerDuty built a new Task Scheduler using Akka, Kafka, and Cassandra. After six weeks in development, the Scheduler is now running in production. This talk discusses how the strengths of the three technologies were leveraged to solve the challenges of resilient, distributed task scheduling.
This talk will present a number of distributed system concepts in the real-world context of the Scheduler project. How can you dynamically adjust for increased task load with zero downtime? Can you guarantee task ordering across many servers? Do your tasks still run when an entire datacenter goes down? What happens if your tasks are scheduled twice? Attendees can expect to see how all of these challenges were addressed.
Some familiarity with distributed queueing and actor systems will be helpful for attendees of this talk.
I used these slides last year to introduce RTAI and Earliest Deadline First for the course "Real-Time Operating Systems" (in English), here at University of Bologna. They include an architectural overview of RTAI, some scheduling algorithms including EDF, and instructions to install and use RTAI.
Scheduling Task-parallel Applications in Dynamically Asymmetric EnvironmentsLEGATO project
Presentation by Jing Chen and Pirah Noor Soomro (Chalmers University of Technology) at the 16th International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems (SRMPDS 2020) on 17 August 2020.
SRMPDS was a virtual event and collocated with ICPP’20 - 2020 International Conference on Parallel Processing.
This lecture covers process and thread concepts in operating systems including scheduling criteria and algorithms. It discusses key process concepts like process state, process control block and CPU scheduling. Common scheduling algorithms like FCFS, SJF, priority and round robin are explained. Process scheduling queues and the producer-consumer problem are also summarized. Evaluation methods for scheduling algorithms like deterministic modeling, queueing models and simulation are briefly covered.
multiprocessor real_ time scheduling.pptnaghamallella
This document discusses different scheduling models for multiprocessor real-time systems, including global scheduling, partitioned scheduling, and semi-partitioned scheduling. Global scheduling uses a shared ready queue and allows tasks to migrate between processors, but can cause overhead from migration and scheduling anomalies. Partitioned scheduling assigns each task to a dedicated processor to avoid migration, but may underutilize processors. Semi-partitioned scheduling first partitions tasks then allows some to migrate to improve utilization.
Modern operating systems are complex beasts, responsible for sharing hardware resources between many competing programs. For low-latency systems, sometimes it's necessary to subvert the OS to grab back the resources your program needs. In this talk, we will explore what is actually going on when you run a program, how much time it actually gets on CPU, and strategies to help make your code run as fast as possible. By the end of this talk, you will know how to tune your software and the linux kernel to get the most from your hardware, and more importantly, how to validate that your changes have worked.
Understanding of linux kernel memory modelSeongJae Park
SeongJae Park introduces himself and his work contributing to the Linux kernel memory model documentation. He developed a guaranteed contiguous memory allocator and maintains the Korean translation of the kernel's memory barrier documentation. The document discusses how the increasing prevalence of multi-core processors requires careful programming to ensure correct parallel execution given relaxed memory ordering. It notes that compilers and CPUs optimize for instruction throughput over programmer goals, and memory accesses can be reordered in ways that affect correctness on multi-processors. Understanding the memory model is important for writing high-performance parallel code.
Celery is a really good framework for doing background task processing in Python (and other languages). While it is ridiculously easy to use celery, doing complex task flow has been a challenge in celery. (w.r.t task trees/graphs/dependecies etc.)
This talk introduces the audience to these challenges in celery and also explains how these can be fixed programmatically and by using latest features in Celery (3+)
This document contains information about real-time operating systems and scheduling algorithms. It discusses the architecture of real-time systems, including hard and soft real-time systems. It also covers common task categories and why scheduling is needed. The document then summarizes several important scheduling algorithms for real-time systems, including rate monotonic, deadline monotonic, earliest deadline first, least laxity first, and maximum urgency first. It provides examples and explanations of how each algorithm works.
The document discusses Windows XP's scheduling algorithm. It uses a priority-based, preemptive approach with 32 priority levels divided into variable and real-time classes. The scheduler ensures the highest priority thread runs by maintaining queues for each priority level and traversing from highest to lowest. Threads start at the process' base priority and may have their priority lowered after time quantums expire to limit CPU consumption of compute-intensive threads.
Modeling the Behavior of Threads in the PREEMPT_RT Linux Kernel Using AutomataDaniel Bristot de Oliveira
This document discusses modeling the behavior of threads in the PREEMPT RT Linux kernel using automata. It proposes an automata-based model to describe and verify thread management code using a modular approach with generators and specifications. The model was integrated with Linux's tracing features, which helped catch an inefficiency bug in the scheduler code and lead to a kernel improvement. Future work includes expanding the model to support interrupts, locks, and multi-core behavior.
This document discusses scheduling in distributed systems. It covers:
1) Common scheduling techniques like min-min, max-min, and sufferage for scheduling independent tasks on dedicated systems.
2) Scheduling dependent tasks modeled as directed acyclic graphs (DAGs) using techniques like critical path on a processor (CPOP) and heterogeneous earliest finish time (HEFT).
3) The need for scheduling algorithms to adapt to dynamic grid environments where tasks may have dependencies on shared files and network transfer times vary.
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Academic project based on developing a LSTM distributing it on Spark and using Tensorflow for numerical operations.
Source code: https://github.com/EmanuelOverflow/LSTM-TensorSpark
The document discusses how parallelism exists even on single-core processors through techniques like out-of-order execution, where the execution order is determined by efficiency rather than program order. It also discusses how simultaneous multithreading allows multiple threads to share execution resources within a single core. The challenges of parallel programming are that it is an unpredictable high-dimensional problem space, and performance analysis can be expensive as it may require modeling the entire system.
The RTX kernel is a royalty-free real-time operating system designed for ARM and Cortex-M devices. It allows programs to perform multiple functions simultaneously using parallel tasks. The RTX kernel provides functions to create and manage concurrent tasks, prioritize tasks, and initialize the kernel. Some basic RTX kernel functions include os_sys_init to initialize the kernel, os_tsk_create to create tasks, and os_tsk_delete to terminate tasks.
The document discusses CPU scheduling in Windows operating systems. It covers scheduling algorithms used in different versions of Windows like Windows 3.1x, 95, NT, XP, 7, and 8. The key points discussed are:
- Windows uses a pre-emptive, priority-based scheduler with 32 priority levels and multi-level queues.
- The dispatcher determines thread execution order based on priority class and relative priority within class.
- Interactive threads get priority boosts after waits to improve response time.
- The foreground process in Windows XP gets preferential treatment over background processes.
- Later versions introduced improvements like user-mode scheduling and CPU cycle-based scheduling.
Real-Time Operating System (RTOS) Vs. General Purpose OS (GPOS)
Can Linux provide real-time guarantees?
Commercial RTOSs
RTLinux Vs. Linux: Architectural comparison
RTLinux Vs. Linux: Code perspective
Get the RTLinux setup ready
Things to Issue and Handling the hard disk
Lab #1: Detailed discussion
The document discusses real-time embedded systems and real-time operating system (RTOS) scheduling. It introduces key concepts like hard and soft real-time systems, embedded systems, and RTOS scheduling techniques including round robin, function pointer based, and priority-based preemptive scheduling. The document also covers rate monotonic scheduling and static priority driven preemptive scheduling assumptions and theorems.
Measures in SQL (SIGMOD 2024, Santiago, Chile)Julian Hyde
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
Using Query Store in Azure PostgreSQL to Understand Query PerformanceGrant Fritchey
Microsoft has added an excellent new extension in PostgreSQL on their Azure Platform. This session, presented at Posette 2024, covers what Query Store is and the types of information you can get out of it.
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Similar to Linux Scheduler Latest_ viresh Kumar.pdf
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https://www.youtube.com/watch?v=s3GfXTnzG_Y
Dynamically scheduled tasks are at the heart of PagerDuty's microservices. They deliver incident alerts, on-call notifications, and manage myriad administrative chores. Historically, these tasks were scheduled and run using an in-house library built on Cassandra, but that solution had begun to show its age.
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This talk will present a number of distributed system concepts in the real-world context of the Scheduler project. How can you dynamically adjust for increased task load with zero downtime? Can you guarantee task ordering across many servers? Do your tasks still run when an entire datacenter goes down? What happens if your tasks are scheduled twice? Attendees can expect to see how all of these challenges were addressed.
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SRMPDS was a virtual event and collocated with ICPP’20 - 2020 International Conference on Parallel Processing.
This lecture covers process and thread concepts in operating systems including scheduling criteria and algorithms. It discusses key process concepts like process state, process control block and CPU scheduling. Common scheduling algorithms like FCFS, SJF, priority and round robin are explained. Process scheduling queues and the producer-consumer problem are also summarized. Evaluation methods for scheduling algorithms like deterministic modeling, queueing models and simulation are briefly covered.
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This document discusses different scheduling models for multiprocessor real-time systems, including global scheduling, partitioned scheduling, and semi-partitioned scheduling. Global scheduling uses a shared ready queue and allows tasks to migrate between processors, but can cause overhead from migration and scheduling anomalies. Partitioned scheduling assigns each task to a dedicated processor to avoid migration, but may underutilize processors. Semi-partitioned scheduling first partitions tasks then allows some to migrate to improve utilization.
Modern operating systems are complex beasts, responsible for sharing hardware resources between many competing programs. For low-latency systems, sometimes it's necessary to subvert the OS to grab back the resources your program needs. In this talk, we will explore what is actually going on when you run a program, how much time it actually gets on CPU, and strategies to help make your code run as fast as possible. By the end of this talk, you will know how to tune your software and the linux kernel to get the most from your hardware, and more importantly, how to validate that your changes have worked.
Understanding of linux kernel memory modelSeongJae Park
SeongJae Park introduces himself and his work contributing to the Linux kernel memory model documentation. He developed a guaranteed contiguous memory allocator and maintains the Korean translation of the kernel's memory barrier documentation. The document discusses how the increasing prevalence of multi-core processors requires careful programming to ensure correct parallel execution given relaxed memory ordering. It notes that compilers and CPUs optimize for instruction throughput over programmer goals, and memory accesses can be reordered in ways that affect correctness on multi-processors. Understanding the memory model is important for writing high-performance parallel code.
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This document contains information about real-time operating systems and scheduling algorithms. It discusses the architecture of real-time systems, including hard and soft real-time systems. It also covers common task categories and why scheduling is needed. The document then summarizes several important scheduling algorithms for real-time systems, including rate monotonic, deadline monotonic, earliest deadline first, least laxity first, and maximum urgency first. It provides examples and explanations of how each algorithm works.
The document discusses Windows XP's scheduling algorithm. It uses a priority-based, preemptive approach with 32 priority levels divided into variable and real-time classes. The scheduler ensures the highest priority thread runs by maintaining queues for each priority level and traversing from highest to lowest. Threads start at the process' base priority and may have their priority lowered after time quantums expire to limit CPU consumption of compute-intensive threads.
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This document discusses scheduling in distributed systems. It covers:
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- Windows uses a pre-emptive, priority-based scheduler with 32 priority levels and multi-level queues.
- The dispatcher determines thread execution order based on priority class and relative priority within class.
- Interactive threads get priority boosts after waits to improve response time.
- The foreground process in Windows XP gets preferential treatment over background processes.
- Later versions introduced improvements like user-mode scheduling and CPU cycle-based scheduling.
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Can Linux provide real-time guarantees?
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SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
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3. CPU Scheduler
● Shares CPU between tasks.
● Selects next task to run (on each CPU) when:
○ Running task terminates
○ Running task sleeps (waiting for an event)
○ A new task created or sleeping task wakes up
○ Running task’s timeslice is over
● Goals:
○ Be *fair*
○ Timeslice based on task priority
○ Low task response time
○ High (task completion) throughput
○ Balance load among CPUs
○ Power efficient
○ Low overhead of running scheduler’s code
● Work with mainframes, servers, desktops/laptops, embedded/phones.
4. The O(1) scheduler
● 140 priorities. 0-99: RT tasks and 100-139: User tasks.
● Each CPU’s runqueue had 2 arrays: Active and Expired.
● Each arrays had 140 entries, one per priority level.
● Each entry was a linked list serviced in FIFO order.
● Bitmap (of 140 bits) used to find which priority lists aren’t empty.
● Timeslices were assigned to tasks based on these priorities.
● Expired tasks moved from Active to Expired array.
● Once Active array was empty, the arrays were swapped.
● Enqueue and dequeue of tasks and next task selection done in constant time.
● Replaced by CFS in Linux 2.6.23 (2007).
5. The O(1) scheduler (Cont..)
Priority 0
Priority 1
Priority 139
...
Priority 99
...
CPU Active array
Priority 0
Priority 1
Priority 139
...
Priority 99
...
CPU Expired array
Real Time task priorities
User task priorities
6. Current scheduler design
● Introduced by Ingo Molnar in 2.6.23 (2007).
● Scheduling policies within scheduling classes.
● Scheduling class with higher priority served first.
● Task can migrate between CPUs, scheduling policies and scheduling classes.
7. Scheduling Classes
● Represented by following structure:
struct sched_class {
const struct sched_class *next;
void (*enqueue_task) (struct rq *rq, struct task_struct *p, int flags);
void (*dequeue_task) (struct rq *rq, struct task_struct *p, int flags);
struct task_struct * (*pick_next_task) (struct rq *rq, struct task_struct *prev, struct rq_flags *rf);
…
};
STOP
next
DL RT CFS IDLE
null
next next next next
8. Schedule()
● Picks the next runnable task to run on a CPU.
● Searches for a task starting from the highest priority class (stop).
● Helper: for_each_class().
● pick_next_task():
again:
for_each_class(class) {
p = class->pick_next_task(rq, prev, rf);
if (p) {
if (unlikely(p == RETRY_TASK))
goto again;
return p;
}
}
/* The idle class should always have a runnable task: */
BUG();
9. Scheduling classes and policies
● Stop
○ No policy
● Deadline
○ SCHED_DEADLINE
● Real Time
○ SCHED_FIFO
○ SCHED_RR
● Fair
○ SCHED_NORMAL
○ SCHED_BATCH
○ SCHED_IDLE
● Idle
○ No policy
10. Sched class: STOP
● Highest priority class.
● Only available for SMP (stop_machine() isn’t used in UP).
● Can preempt everything and is preempted by nothing.
● Mechanism to stop running everything else and run a specific function on CPU(s).
● No scheduling policies.
● One kernel thread per CPU: “migration/N”.
● Used by task migration, CPU hotplug, RCU, ftrace, clockevents, etc.
11. Sched class: Deadline (DL)
● Introduced by Dario Faggioli & Juri Lelli, v3.14 (2013).
● Highest priority tasks in the system.
● Scheduling policy: SCHED_DEADLINE.
● Implemented with red-black tree (self balancing).
● Used for periodic real time tasks, eg. Video encoding/decoding.
12. Sched class: Real-time (RT)
● POSIX “real-time” tasks.
● Task priorities: 0 - 99.
● Inverted priorities: 0 highest in kernel, lowest in user space.
● Scheduling policies for tasks at same priority:
○ SCHED_FIFO
○ SCHED_RR, 100ms timeslice by default.
● Implemented with Linked lists.
● Used for short latency sensitive tasks, eg. IRQ threads.
13. Sched class: CFS (Completely fair scheduler)
● Introduced by Ingo Molnar (motivated by Rotating Staircase Deadline Scheduler
by Con Kolivas).
● Scheduling policies:
○ SCHED_NORMAL: Normal Unix tasks
○ SCHED_BATCH: Batch (non-interactive) tasks
○ SCHED_IDLE: Low priority tasks
● Implemented with red-black tree (self balancing).
● Tracks Virtual runtime of tasks (amount of time task has run).
● Tasks with shortest vruntime runs first.
● Priority is used to set task’s weight, that affects vruntime.
● Higher the weight, slower will vruntime increase.
● Task’s priority is calculated by 120 + nice (-20 to +19).
● Used for all other system tasks, eg: shell.
14. Sched class: Idle
● Lowest priority scheduling class.
● No scheduling policies.
● One kernel thread (idle) per CPU: “swapper/N”.
● Idle thread runs only when nothing else is runnable on a CPU.
● Idle thread may take the CPU to low power state.
15. Runqueue
● Each CPU has an instance of “struct rq”.
● Each “rq” has DL, RT and CFS runqueues within it.
● Runnable tasks are enqueued on those runqueues.
● Lots of other information, stats are available in struct rq.
struct rq {
…
struct cfs_rq cfs;
struct rt_rq rt;
struct dl_rq dl;
...
}