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Lecture 11: Deadlock, Scheduling, & Synchronization October 3, 2019 Instructor: David E
CS 162: Operating Systems and System Programming Lecture 11: Deadlock, Scheduling, & Synchronization October 3, 2019 Instructor: David E. Culler & Sam Kumar https://cs162.eecs.berkeley.edu Read: A&D 6.5 Project 1 Code due TOMORROW! Midterm Exam next week Thursday Outline for Today • (Quickly) Recap and Finish Scheduling • Deadlock • Language Support for Concurrency 10/3/19 CS162 UCB Fa 19 Lec 11.2 Recall: CPU & I/O Bursts • Programs alternate between bursts of CPU, I/O activity • Scheduler: Which thread (CPU burst) to run next? • Interactive programs vs Compute Bound vs Streaming 10/3/19 CS162 UCB Fa 19 Lec 11.3 Recall: Evaluating Schedulers • Response Time (ideally low) – What user sees: from keypress to character on screen – Or completion time for non-interactive • Throughput (ideally high) – Total operations (jobs) per second – Overhead (e.g. context switching), artificial blocks • Fairness – Fraction of resources provided to each – May conflict with best avg. throughput, resp. time 10/3/19 CS162 UCB Fa 19 Lec 11.4 Recall: What if we knew the future? • Key Idea: remove convoy effect –Short jobs always stay ahead of long ones • Non-preemptive: Shortest Job First – Like FCFS where we always chose the best possible ordering • Preemptive Version: Shortest Remaining Time First – A newly ready process (e.g., just finished an I/O operation) with shorter time replaces the current one 10/3/19 CS162 UCB Fa 19 Lec 11.5 Recall: Multi-Level Feedback Scheduling Long-Running Compute Tasks Demoted to Low Priority • Intuition: Priority Level proportional -
Process Scheduling Ii
PROCESS SCHEDULING II CS124 – Operating Systems Spring 2021, Lecture 12 2 Real-Time Systems • Increasingly common to have systems with real-time scheduling requirements • Real-time systems are driven by specific events • Often a periodic hardware timer interrupt • Can also be other events, e.g. detecting a wheel slipping, or an optical sensor triggering, or a proximity sensor reaching a threshold • Event latency is the amount of time between an event occurring, and when it is actually serviced • Usually, real-time systems must keep event latency below a minimum required threshold • e.g. antilock braking system has 3-5 ms to respond to wheel-slide • The real-time system must try to meet its deadlines, regardless of system load • Of course, may not always be possible… 3 Real-Time Systems (2) • Hard real-time systems require tasks to be serviced before their deadlines, otherwise the system has failed • e.g. robotic assembly lines, antilock braking systems • Soft real-time systems do not guarantee tasks will be serviced before their deadlines • Typically only guarantee that real-time tasks will be higher priority than other non-real-time tasks • e.g. media players • Within the operating system, two latencies affect the event latency of the system’s response: • Interrupt latency is the time between an interrupt occurring, and the interrupt service routine beginning to execute • Dispatch latency is the time the scheduler dispatcher takes to switch from one process to another 4 Interrupt Latency • Interrupt latency in context: Interrupt! Task -
1999 Nendo Supercompiler Te
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Advanced Scheduling
Administrivia • Project 1 due Friday noon • If you need longer, email cs140-staff. - Put “extension” in the subject - Tell us where you are, and how much longer you need. - We will give short extensions to people who don’t abuse this • Section Friday to go over project 2 • Project 2 Due Friday, Feb. 7 at noon • Midterm following Monday, Feb. 10 • Midterm will be open book, open notes - Feel free to bring textbook, printouts of slides - Laptop computers or other electronic devices prohibited 1 / 38 Fair Queuing (FQ) [Demers] • Digression: packet scheduling problem - Which network packet should router send next over a link? - Problem inspired some algorithms we will see today - Plus good to reinforce concepts in a different domain. • For ideal fairness, would use bit-by-bit round-robin (BR) - Or send more bits from more important flows (flow importance can be expressed by assigning numeric weights) Flow 1 Flow 2 Round-robin service Flow 3 Flow 4 2 / 38 SJF • Recall limitations of SJF from last lecture: - Can’t see the future . solved by packet length - Optimizes response time, not turnaround time . but these are the same when sending whole packets - Not fair Packet scheduling • Differences from CPU scheduling - No preemption or yielding—must send whole packets . Thus, can’t send one bit at a time - But know how many bits are in each packet . Can see the future and know how long packet needs link • What scheduling algorithm does this suggest? 3 / 38 Packet scheduling • Differences from CPU scheduling - No preemption or yielding—must send whole packets . -
(FCFS) Scheduling
Lecture 4: Uniprocessor Scheduling Prof. Seyed Majid Zahedi https://ece.uwaterloo.ca/~smzahedi Outline • History • Definitions • Response time, throughput, scheduling policy, … • Uniprocessor scheduling policies • FCFS, SJF/SRTF, RR, … A Bit of History on Scheduling • By year 2000, scheduling was considered a solved problem “And you have to realize that there are not very many things that have aged as well as the scheduler. Which is just another proof that scheduling is easy.” Linus Torvalds, 2001[1] • End to Dennard scaling in 2004, led to multiprocessor era • Designing new (multiprocessor) schedulers gained traction • Energy efficiency became top concern • In 2016, it was shown that bugs in Linux kernel scheduler could cause up to 138x slowdown in some workloads with proportional energy waist [2] [1] L. Torvalds. The Linux Kernel Mailing List. http://tech-insider.org/linux/research/2001/1215.html, Feb. 2001. [2] Lozi, Jean-Pierre, et al. "The Linux scheduler: a decade of wasted cores." Proceedings of the Eleventh European Conference on Computer Systems. 2016. Definitions • Task, thread, process, job: unit of work • E.g., mouse click, web request, shell command, etc.) • Workload: set of tasks • Scheduling algorithm: takes workload as input, decides which tasks to do first • Overhead: amount of extra work that is done by scheduler • Preemptive scheduler: CPU can be taken away from a running task • Work-conserving scheduler: CPUs won’t be left idle if there are ready tasks to run • For non-preemptive schedulers, work-conserving is not always -
Lottery Scheduler for the Linux Kernel Planificador Lotería Para El Núcleo
Lottery scheduler for the Linux kernel María Mejía a, Adriana Morales-Betancourt b & Tapasya Patki c a Universidad de Caldas and Universidad Nacional de Colombia, Manizales, Colombia, [email protected] b Departamento de Sistemas e Informática at Universidad de Caldas, Manizales, Colombia, [email protected] c Department of Computer Science, University of Arizona, Tucson, USA, [email protected] Received: April 17th, 2014. Received in revised form: September 30th, 2014. Accepted: October 20th, 2014 Abstract This paper describes the design and implementation of Lottery Scheduling, a proportional-share resource management algorithm, on the Linux kernel. A new lottery scheduling class was added to the kernel and was placed between the real-time and the fair scheduling class in the hierarchy of scheduler modules. This work evaluates the scheduler proposed on compute-intensive, I/O-intensive and mixed workloads. The results indicate that the process scheduler is probabilistically fair and prevents starvation. Another conclusion is that the overhead of the implementation is roughly linear in the number of runnable processes. Keywords: Lottery scheduling, Schedulers, Linux kernel, operating system. Planificador lotería para el núcleo de Linux Resumen Este artículo describe el diseño e implementación del planificador Lotería en el núcleo de Linux, este planificador es un algoritmo de administración de proporción igual de recursos, Una nueva clase, el planificador Lotería (Lottery scheduler), fue adicionado al núcleo y ubicado entre la clase de tiempo-real y la clase de planificador completamente equitativo (Complete Fair scheduler-CFS) en la jerarquía de los módulos planificadores. Este trabajo evalúa el planificador propuesto en computación intensiva, entrada-salida intensiva y cargas de trabajo mixtas. -
Thread Scheduling in Multi-Core Operating Systems Redha Gouicem
Thread Scheduling in Multi-core Operating Systems Redha Gouicem To cite this version: Redha Gouicem. Thread Scheduling in Multi-core Operating Systems. Computer Science [cs]. Sor- bonne Université, 2020. English. tel-02977242 HAL Id: tel-02977242 https://hal.archives-ouvertes.fr/tel-02977242 Submitted on 24 Oct 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Ph.D thesis in Computer Science Thread Scheduling in Multi-core Operating Systems How to Understand, Improve and Fix your Scheduler Redha GOUICEM Sorbonne Université Laboratoire d’Informatique de Paris 6 Inria Whisper Team PH.D.DEFENSE: 23 October 2020, Paris, France JURYMEMBERS: Mr. Pascal Felber, Full Professor, Université de Neuchâtel Reviewer Mr. Vivien Quéma, Full Professor, Grenoble INP (ENSIMAG) Reviewer Mr. Rachid Guerraoui, Full Professor, École Polytechnique Fédérale de Lausanne Examiner Ms. Karine Heydemann, Associate Professor, Sorbonne Université Examiner Mr. Etienne Rivière, Full Professor, University of Louvain Examiner Mr. Gilles Muller, Senior Research Scientist, Inria Advisor Mr. Julien Sopena, Associate Professor, Sorbonne Université Advisor ABSTRACT In this thesis, we address the problem of schedulers for multi-core architectures from several perspectives: design (simplicity and correct- ness), performance improvement and the development of application- specific schedulers. -
2. Virtualizing CPU(2)
Operating Systems 2. Virtualizing CPU Pablo Prieto Torralbo DEPARTMENT OF COMPUTER ENGINEERING AND ELECTRONICS This material is published under: Creative Commons BY-NC-SA 4.0 2.1 Virtualizing the CPU -Process What is a process? } A running program. ◦ Program: Static code and static data sitting on the disk. ◦ Process: Dynamic instance of a program. ◦ You can have multiple instances (processes) of the same program (or none). ◦ Users usually run more than one program at a time. Web browser, mail program, music player, a game… } The process is the OS’s abstraction for execution ◦ often called a job, task... ◦ Is the unit of scheduling Program } A program consists of: ◦ Code: machine instructions. ◦ Data: variables stored and manipulated in memory. Initialized variables (global) Dynamically allocated (malloc, new) Stack variables (function arguments, C automatic variables) } What is added to a program to become a process? ◦ DLLs: Libraries not compiled or linked with the program (probably shared with other programs). ◦ OS resources: open files… Program } Preparing a program: Task Editor Source Code Source Code A B Compiler/Assembler Object Code Object Code Other A B Objects Linker Executable Dynamic Program File Libraries Loader Executable Process in Memory Process Creation Process Address space Code Static Data OS res/DLLs Heap CPU Memory Stack Loading: Code OS Reads on disk program Static Data and places it into the address space of the process Program Disk Eagerly/Lazily Process State } Each process has an execution state, which indicates what it is currently doing ps -l, top ◦ Running (R): executing on the CPU Is the process that currently controls the CPU How many processes can be running simultaneously? ◦ Ready/Runnable (R): Ready to run and waiting to be assigned by the OS Could run, but another process has the CPU Same state (TASK_RUNNING) in Linux. -
CPU Scheduling
CS 372: Operating Systems Mike Dahlin Lecture #3: CPU Scheduling ********************************* Review -- 1 min ********************************* Deadlock ♦ definition ♦ conditions for its occurrence ♦ solutions: breaking deadlocks, avoiding deadlocks ♦ efficiency v. complexity Other hard (liveness) problems priority inversion starvation denial of service ********************************* Outline - 1 min ********************************** CPU Scheduling • goals • algorithms and evaluation Goal of lecture: We will discuss a range of options. There are many more out there. The important thing is not to memorize the scheduling algorithms I describe. The important thing is to develop strategy for analyzing scheduling algorithms in general. ********************************* Preview - 1 min ********************************* File systems 1 02/24/11 CS 372: Operating Systems Mike Dahlin ********************************* Lecture - 20 min ********************************* 1. Scheduling problem definition Threads = concurrency abstraction Last several weeks: what threads are, how to build them, how to use them 3 main states: ready, running, waiting Running: TCB on CPU Waiting: TCB on a lock, semaphore, or condition variable queue Ready: TCB on ready queue Operating system can choose when to stop running one and when to start the next ready one. OS can choose which ready thread to start (ready “queue” doesn’t have to be FIFO) Key principle of OS design: separate mechanism from policy Mechanism – how to do something Policy – what to do, when to do it 2 02/24/11 CS 372: Operating Systems Mike Dahlin In this case, design our context switch mechanism and synchronization methodology allow OS to switch from any thread to any other one at any time (system will behave correctly) Thread/process scheduling policy decides when to switch in order to meet performance goals 1.1 Pre-emptive v. -
Linux CPU Schedulers: CFS and Muqss Comparison
Umeå University 2021-06-14 Bachelor’s Thesis In Computing Science Linux CPU Schedulers: CFS and MuQSS Comparison Name David Shakoori Gustafsson Supervisor Anna Jonsson Examinator Ola Ringdahl CFS and MuQSS Comparison Abstract The goal of this thesis is to compare two process schedulers for the Linux operating system. In order to provide a responsive and interactive user ex- perience, an efficient process scheduling algorithm is important. This thesis seeks to explain the potential performance differences by analysing the sched- ulers’ respective designs. The two schedulers that are tested and compared are Con Kolivas’s MuQSS and Linux’s default scheduler, CFS. They are tested with respect to three main aspects: latency, turn-around time and interactivity. Latency is tested by using benchmarking software, the turn- around time by timing software compilation, and interactivity by measuring video frame drop percentages under various background loads. These tests are performed on a desktop PC running Linux OpenSUSE Leap 15.2, using kernel version 5.11.18. The test results show that CFS manages to keep a generally lower latency, while turn-around times differs little between the two. Running the turn-around time test’s compilation using a single process gives MuQSS a small advantage, while dividing the compilation evenly among the available logical cores yields little difference. However, CFS clearly outper- forms MuQSS in the interactivity test, where it manages to keep frame drop percentages considerably lower under each tested background load. As is apparent by the results, Linux’s current default scheduler provides a more responsive and interactive experience within the testing conditions, than the alternative MuQSS. -
Cross-Layer Resource Control and Scheduling for Improving Interactivity in Android
SOFTWARE—PRACTICE AND EXPERIENCE Softw. Pract. Exper. 2014; 00:1–22 Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/spe Cross-Layer Resource Control and Scheduling for Improving Interactivity in Android ∗ † Sungju Huh1, Jonghun Yoo2 and Seongsoo Hong1,2,3, , 1Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Suwon-si, Gyeonggi-do, Republic of Korea 2Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea 3Advanced Institutes of Convergence Technology, Suwon-si, Gyeonggi-do, Republic of Korea SUMMARY Android smartphones are often reported to suffer from sluggish user interactions due to poor interactivity. This is partly because Android and its task scheduler, the completely fair scheduler (CFS), may incur perceptibly long response time to user-interactive tasks. Particularly, the Android framework cannot systemically favor user-interactive tasks over other background tasks since it does not distinguish between them. Furthermore, user-interactive tasks can suffer from high dispatch latency due to the non-preemptive nature of CFS. To address these problems, this paper presents framework-assisted task characterization and virtual time-based CFS. The former is a cross-layer resource control mechanism between the Android framework and the underlying Linux kernel. It identifies user-interactive tasks at the framework-level, by using the notion of a user-interactive task chain. It then enables the kernel scheduler to selectively promote the priorities of worker tasks appearing in the task chain to reduce the preemption latency. The latter is a cross-layer refinement of CFS in terms of interactivity. It allows a task to be preempted at every predefined period. -
Abkürzungs-Liste ABKLEX
Abkürzungs-Liste ABKLEX (Informatik, Telekommunikation) W. Alex 1. Juli 2021 Karlsruhe Copyright W. Alex, Karlsruhe, 1994 – 2018. Die Liste darf unentgeltlich benutzt und weitergegeben werden. The list may be used or copied free of any charge. Original Point of Distribution: http://www.abklex.de/abklex/ An authorized Czechian version is published on: http://www.sochorek.cz/archiv/slovniky/abklex.htm Author’s Email address: [email protected] 2 Kapitel 1 Abkürzungen Gehen wir von 30 Zeichen aus, aus denen Abkürzungen gebildet werden, und nehmen wir eine größte Länge von 5 Zeichen an, so lassen sich 25.137.930 verschiedene Abkür- zungen bilden (Kombinationen mit Wiederholung und Berücksichtigung der Reihenfol- ge). Es folgt eine Auswahl von rund 16000 Abkürzungen aus den Bereichen Informatik und Telekommunikation. Die Abkürzungen werden hier durchgehend groß geschrieben, Akzente, Bindestriche und dergleichen wurden weggelassen. Einige Abkürzungen sind geschützte Namen; diese sind nicht gekennzeichnet. Die Liste beschreibt nur den Ge- brauch, sie legt nicht eine Definition fest. 100GE 100 GBit/s Ethernet 16CIF 16 times Common Intermediate Format (Picture Format) 16QAM 16-state Quadrature Amplitude Modulation 1GFC 1 Gigabaud Fiber Channel (2, 4, 8, 10, 20GFC) 1GL 1st Generation Language (Maschinencode) 1TBS One True Brace Style (C) 1TR6 (ISDN-Protokoll D-Kanal, national) 247 24/7: 24 hours per day, 7 days per week 2D 2-dimensional 2FA Zwei-Faktor-Authentifizierung 2GL 2nd Generation Language (Assembler) 2L8 Too Late (Slang) 2MS Strukturierte