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Operating System Design LINUX KERNEL DESIGN (2.6/3.X) Dr. C.C. Lee Ref: Linux Kernel Development by R. Love Ref: Operating System Concepts by Silberschatz…

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Presentation on theme: "Operating System Design LINUX KERNEL DESIGN (2.6/3.X) Dr. C.C. Lee Ref: Linux Kernel Development by R. Love Ref: Operating System Concepts by Silberschatz…"— Presentation transcript:

1 Operating System Design LINUX KERNEL DESIGN (2.6/3.X) Dr. C.C. Lee Ref: Linux Kernel Development by R. Love Ref: Operating System Concepts by Silberschatz…

2 Introduction Monolithic & dynamically loadable kernel module SMP support (run queue per CPU, load balance) Kernel preemptive, schedulable, thread support CPU (soft & hard) affinity Kernel memory not pageable Source in GNU C (not ANSI C) with extension, in- line for efficiency, Kernel source tree – architecture indep/dep. part Portable to different architecture

3 CPU Affinity CPU affinity: less overhead, in cache Soft affinity means that processes do not frequently migrate between processors. Hard affinity means that processes run on processors you specify Reason 1: You have a hunch – computations Reason 2: Testing complex applications – linear scalability? Reason 3: Running time-sensitive, deterministic processes sched_setaffinity (…) set CPU affinity mask

4 Process (Task) Basics Process States  TASK_RUNNING (run or ready)  TASK_INTERRUPTIBLE (sleeping or blocked, may be waken by signal)  TASK_UNTERRUPTIBLE (sleeping/blocked, only event can wake this task)  TASK_STOPPED (SIGSTOP, SIGTTIN, SIGTTOU signals)  TASK_ZOMBIE (pending for parent task to issue wait)

5 Process (Task) Basics - Continue Context  Process context – user code or kernel (from system calls)  Interrupt context – kernel interrupt handling Task (Process) Creation  Fork (may be implemented by: COW i.e.Copy On Write)  Vfork :same as fork ( but shared page table, parent wait for child )  Clone system call is used to implement fork and vfork  Threads are created the same as normal tasks except that the clone system call is passed with spec. resources shared Task (Process) Termination  Memory/files/timers/semaphores released, notify parent

6 Process (Task) Scheduling Preemptive Scheduler Classes (priority for classes) Real-time: FIFO and RR (timeslice), fixed priority Normal ( SCHED_NORMAL) SMP ( Run queue/structure per CPU, why? ) Processor Affinity ( Soft & Hard ) Load balancing

7 Process (Task) Scheduling Cont. Two process-scheduling Classes: Normal time-sharing (dynamic) (Nice value: 19 to -20, with default 0 = 120) Real-time algorithm ( FIFO/RR ) - Soft Absolute priorities (static): 0-99 FIFO run till Exit, Yield, or Block RR run with time slice Preemption possible with priority Normal Processes: to be studied here

8 Early Kernel 2.6 - O(1) Scheduler O(1) Scheduler (Early Kernel 2.6) Improved scheduler with O(1) operations using bit map operations to search highest priority queue Active and Expired Array (Run Queues per CPU) Scalable Heuristics for CPU/IO bound, Interactivities

9 21.9 Silberschatz, Galvin and Gagne ©2005 Operating System Concepts O(1) Scheduler Priority Array

10 O(1) Scheduler Summary n Implements a priority-based array of task entries that enables the highest-priority task to be found quickly (by using a priority bitmap with a fast instruction). n Recalculates the timeslice and priority of an expired task before it places it on the expired queue. When all the tasks expire, the scheduler simply needs to swap the active and expired queue pointers and schedule the next task. Long scans of runqueues are, thus, eliminated n This process takes the same amount of processing, irrespective of the number of tasks in the system. It no longer depends on the value of n, but is a fixed constant

11 O(1) Scheduler Problems Although O(1) scheduler performed well and scaled effortlessly for large systems with many tens or hundreds of processors, IT FAILS ON: Slow response to latency-sensitive applications i.e. interactive processes for typical desktop systems Not achieving Fair (Equal) CPU Allocation

12 Current: Completely Fair Scheduler (CFS) n Since Kernel 2.6.23 n CFS Aiming at n Giving each task a fair share (portion) of the processor time (Completely Fair) n Improving the interactive performance of O(1) scheduler for desktop. While O(1) scheduler is ideal for large server workloads n Introduces simple/efficient algorithmic approach (red- black tree) with O(log N). While O(1) scheduler uses heuristics and the code is large and lacks algorithm substance.

13 Completely Fair Scheduler (CFS)

14 CFS – Processor Time Allocation n Select next that has run the least. Rather than assign each process a time slice, CFS calculates how long a process should run as a function of the total number of runnable processes and its niceness (default: 1 ms as minimum granularity) Nice values are used to weight the portion of processor a process is to receive (not by additive increases, but by geometric differences). Each process will run for a “ timeslice ” proportional to its weight divided by total weight of all runnable processes. Assume TARGETED_LANTENCY = 20ms: Two threads: the niceness are 0(10), and 5(15), CFS assigns relative weight 3 : 1 (approx.) – * particular algorithm Niceness 0(10) receives 15ms and Niceness 5(15) receives 5ms Here, CPU portion is determined only by the relative value.

15 CFS – The Virtual Runtime (vruntime) The virtual runtime (vruntime) is the actual runtime (the amount of time spent) weighted by its niceness nice=0, factor=1; vruntime is same as real run time spent by task nice<0, factor< 1; vruntime is less than real run time spent. vruntime grows slower than real run time used. nice>0, factor> 1; vruntime is more than real run time spent. vruntime grows faster than real run time used. (The virtual runtime is measured in nano seconds) Every time a thread runs for t ns, vruntime += t (weighted by task niceness i.e. priority) The virtual runtime (vruntime) is used to account for how long a process has run. CFS will then pick up the process with the smallest vruntime.

16 CFS – Process Selection CFS select the process with the minimum virtual runtime i.e. vruntime CFS use a red-black tree (rbtree – a type of self-balancing binary search tree) to manage the list of runnable processes and efficiently (algorithm) find the process with the smallest vruntime The selected process with the smallest vruntime is the leftmost node in the (rbtree) tree.

17 CFS – Process just Created or Awaken A new process is created The new process is assigned the current Minimum Virtual Runtime (adjusted) and inserted into the rbtree A process is awakened from blocking vruntime = Maximum (old vruntime, current Min_vruntime substracted by adjusted TARGETED_LANTENCY ) This can prevent a process that blocked for a long time from monopolizing the CPU

18 CFS – Group Scheduling In plain CFS, if there are 25 runnable processes, CFS will allocate 4% to each (assume same). If 20 belong to user A, and 5 belong to user B, then user B is at an inherent disadvantage. Group scheduling will first try to be fair to the group and then individual in the group, i.e. 50% to user A and 50% to user B. Thus for A, the allocated 50% of A will be divided fairly among A’s 20 tasks. For B, the allocated 50% will be divided fairly among B’s 5 tasks.

19 CFS – Run Queue (Red-Black Tree) Tasks are maintained in a time-ordered (i.e. vruntime) red-black tree for each CPU Red-Black Tree: Self-balancing binary search tree Balancing is preserved by painting each node with one of two colors in a way to satisfy certain properties. When the tree is modified, the new tree is rearranged and repainted to restore the coloring properties. The balancing of the tree can guarantee that no leaf can be more than twice as deep as others and the tree operations (searching/insertion/deletion/recoloring) can be performed in O(log N) time CFS will switch to the leftmost task in the tree, that is, the one with the lowest virtual runtime (most need for CPU) to maintain fairness.

20 CFS – Red-Black Tree (

21 Interrupt Handling Interrupts (Hardware) Asynchronous Dev.->Interrupt Controller->CPU-->Interrupt Handlers Device has unique value for each interrupt line: IRQ (Interrupt ReQuest number) On PC, IRQ 0 = timer interrupt, IRQ 1 is keyboard interrupt Exceptions (Soft Interrupt) Synchronous Fault (segment fault, page fault,…) Trap (system call) Programming exception

22 Top Halves and Bottom Halves Top Half Interrupts disabled (Line, local) Run (immediately) ACK & reset hardware, copy data from hardware buffer Bottom Half Interrupt enabled Run (deferred) Detailed work processing Example of Network Card Top half: alert the kernel to optimize network throughput, copy packets to memory, ACK network hardware and ready network card for more packets The rest will be left to bottom half

23 Top-Half Writing an Interrupt Handlers (for vectored interrupt table) Registering an Interrupt Handler int request_irq (irq#, *handler, irqflags, *devname, *dev_id) When kernel receives interrupt From interrupt table ( IRQ number) invokes sequentially each registered handler on the line (till device is found)

24 Bottom Halves and Deferring Work  Softirqs – interrupt context routine(can not block) Handling those with time-critical and high concurrency. Handling routines run right after top-half that raised softirq. Tasklets: Special softirqs, intended for those with less time-critical/concurrency/locking requirements It has simpler interface and implementation  Work Queues – A different form of deferring work Work queues run by kernel threads in process context – thus schedulable. Therefore, If the deferred work needs to sleep (allocate a lot of memory, obtain semaphores…), work queues should be used. Otherwise, softirqs/tasklets are used.

25 Bottom Halves - Ksoftirqd n When the system is overwhelmed with softirqs activities, low-priority user processes can not run and may become starved. Thus A per-CPU kernel thread Ksoftirqd (run with the lowest priority i.e. nice value=19) will be awakened. n With this low-level priority Ksoftirqd to handle softirqs under the busy situation, user processes can be relieved from starvation.

26 Which Bottom Half to Use n Bottom Half ContextInherent Serialization Softirq InterruptNone Tasklet InterruptAgainst the same tasklet Work Queues ProcessNone n If the deferred work needs to run in process context: work queue n The highest overhead: work queue (kernel thread, context switch) n Ease of use: work queue n The fastest, highly threaded, timing critical use: softirq n Same as softirq, but simple interface and ease of use: tasklets n Normal driver writers have two choices: Need a schedulable entity to perform the work (sleep for events?) If so, work queue is the only choice. Otherwise, tasklets are preferred, unless scalability is a concern which will use softirq (highly threaded)

27 Kernel Synchronization Kernel has concurrency (threads) and need synchronization Code safe from concurrent access - Terminology Interrupt safe (from interrupt handler) SMP safe Preempt safe (kernel preemption) Spinlock, R/W spinlock, semaphore, R/W semaphore, sequential lock, completion variables

28 Spin Locks Spin locks: Lightweight For short durations to save context switch overhead Spin Locks and Top-Half Kernel must disable local interrupts before obtaining the spin locks. Ot herwise the Interrupt Handler (IH) may interrupt kernel and attempts to acquire the same lock while the lock is held by the kernel – spin? Spin Locks and Bottom Halves Kernel must disable bottom-half before obtaining the spin locks. Otherwise, the bottom-half may preempt kernel code and attempts to acquire this same lock while the lock is held by the kernel – spin?

29 Reader-Writer Spin Locks Shared/Exclusive Locks Reader and Writer Path read_lock(&my_rwlock)write_lock(…) CR CR read_unlock(…)write_unlock(…) Linux 2.6 favors readers over writers (starvation of writers) for Reader-Writer Spin Locks

30 Semaphores n Semaphores for long wait n Semaphores are for process context (can sleep) n Can not hold a spin lock while acquiring a semaphore (may sleep) n Kernel code holding semaphore can be interrupted or preempted n Using Semaphores: down, up

31 Reader-Writer Semaphore Reader-Writer flavor of semaphores Reader-Writer Semaphores are mutexes Reader-Writer Semaphores : locks use uninterruptible sleep As with semaphores, the following are provided: down_read_trylock(), down_write_trylock() down_read, down_write, up_read, up_write

32 Completion variables A task signals other task for an event One task waits on the completion variable while other task performs work. When it completes, it uses a completion variable to wake up the other task init_completion(struct completion *) or DECLARE_COMPLETION (mr_comp) wait_for_completion (struct completion *) complete (struct completion *)

33 Sequential Locks Simple mechanism for reading and writing shared data by maintaining a sequence counter write  lock obtained  seq# incr; unlock -> seq# incr. Prior to and after read: the sequence number is read The sequence number must be even (prior read) and equal at end Writer always succeed (if no other writers), Readers never block Favors writers over readers Readers does not affect writer’s locking Seq locks provide very light weight and scalable lock for use with many readers and a few writers

34 Sequential Locks (Cont.) Example: seqlock_t mr_seq_lock *s1 WRITE: write_seq_lock (s1 ); {spin_lock(s1->lock); ++s1->sequence; SMP_wmb();} /* Write Data */ write_sequnlock (s1 ); {SMP_wmb(); s1->sequence++; spin_unlock(s1-> lock);} READ: do { seq = read_seqbegin (s1); {ret = s1->sequence; SMP_rmb(); return ret;} /* read data */ } while (read_seqretry (s1, seq)); {SMP_rmb(); return (seq&1) | s1->sequence^seq) } Pending writers continually cause read loop to repeat until writers are done.

35 Ordering and Barriers Both compiler and CPU can reorder reads/writes: Compiler: optimization, CPU: performance i.e. pipeline Instruct CPU not to reorder R/W Barrier() call to instruct compiler not to reorder R/W Memory Barrier and Compiler Barrier Methods barrier()// compiler barrier - load/store smp_rmb(), wmb(), mb() Intel X86 processors: do not ever reorder writes

36 Memory Management Main Memory : Three (3) parts kernel memory (never paged out), kernel memory for memory map (never paged out) pageable page frames (user pages, paging cache, etc.) Memory Map : mem_map Array of page descriptor for each page frame in system with pointers to address space they belong to (if not free) or with linked list for free frames

37 Memory Management Physical Memory For kernel (never paged out) For memory map table (never paged out) For page frame to virtual page mapping For maintaining free page list For pageable page frames User pages and paging caches Arbitrary size, contiguous kernel memory Kmalloc(…)

38 Memory Allocation Mechanisms Page allocator - buddy algorithm (2**i split or combined) 65 page chunk->ask for 128 page chunk Slab allocator : carves chunk (from buddy algorithm) into slabs - one or more physically contiguous pages A cache (for each kernel data structure): one or more slabs and is populated with kernel objects (TCBs, semaphores) Example: To allocate a new task_struct, Kernel looks in the object cache. Try: partially full slab?, empty slab?, then a new slab? kmalloc() : Similar to user-space malloc. It returns a pointer to a region of (physically contiguous) memory that is at least requested ‘size’ bytes in length. Vmalloc(): allocates chunk of physical memory (that may not be contiguous) and fix up the page tables to map the memory into a contiguous chunk of logical address space.

39 Virtual Memory Virtual Address Space Homogeneous, contiguous, page-aligned areas ( text, mapped files) Page size: 4KB (Pentium), 8KB (Alpha) – Linux also support 4MB Memory Descriptor A process address space is represented by mm_struct (pointed to by mm field of task_struct) struct mm_struct { struct vm_area_struct *mmap; // list of memory areas – text, data,… pgd_t *pgd; // page global directory atomic_t mm_users // addr. space users – 2 for 2 threads atomic_t mm_count; // primary reference count struct list_head mmlist; // list of all mm_struct … // lock, semaphore… …. // start/end addr. Of code, data, heap, stack }

40 Virtual Memory - Paging Four-level paging (for 64 bit architectures) global/upper/middle directory, and page table Pentium using two-level paging (global directory points to page table) Demand paging (no pre-paging) With only user structure (PCB), and page tables need to be in memory Page daemon (process 2): awaken (periodically or demand) – check ‘free’

41 Page Replacement Modified Version of LRU Scheme One particular failure of the LRU strategy (besides its cost of implementation) is that many files are accessed once and then never again. Putting them at the top of the LRU list is thus not optimal. In general, the kernel has no way of knowing that a file is going to be accessed only once. However, it does know how many times it has been accessed in the past. This leads to a modified version of LRU i.e. Two-List Strategy as follows:

42 Page Replacement (Cont.) Two-list strategy (modified version of LRU) Active list (hot) and Inactive list (reclaim candidate) Pages when first allocated are placed on inactive list If referenced while on that list, it will be placed on active list Both lists are maintained in a pseudo-LRU manner: items are added to the tail and remove from the head as a queue. Lists balanced: if active list becomes larger, items will be moved from the active list back to the inactive list for potential eviction. The action starts from the head item: The reference bit is checked. If it was set, it will be reset, the item is moved back to the list, and the next page is checked. Otherwise it will be moved to the inactive list (resembles a Clock algorithm)

43 Page Replacement (Cont.) A Global Policy All reclaimable pages are contained in just two lists and pages belonging to any process may be reclaimed, rather than just those belonging to a faulting process The two-list strategy enables simpler, pseudo-LRU semantics to perform well Solves the only-used-once failure in a classical LRU scheme

44 The Filesystem To the user, Linux’s file system appears as a hierarchical directory tree obeying UNIX semantics Internally, the kernel hides implementation details and manages the multiple different file systems via an abstraction layer, that is, the virtual file system (VFS) The Linux VFS is designed around object-oriented principles: Write -> sys_write() // VFS Then --> filesystem’s write method --> physical media VFS Objects Primary: superblock, inode(cached), dentry (cached), and file objects An operation object is contained within each primary object: super_operations, inode_operation, dentry_operation, file_operations Other VFS Objects: file_system_type, vfsmount, and three per-process structures such as file_struct, fs_struct and namespace structures

45 File System and Device Drivers User mode Kernel mode Libraries User applications File subsystem Buffer/page cache Hardware control Block device driverCharacter device driver

46 Virtual File System

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