Processes

Process
It is an instance of a computer program that is being executed. It contains the program code and its current activity. Depending on the operating system (OS), a process may be made up of multiple threads of execution that execute instructions concurrently. A computer program is a passive collection of instructions; a process is the actual execution of those instructions. Several processes may be associated with the same program; for example, opening up several instances of the same program often means more than one process is being executed.

Multitasking is a method to allow multiple processes to share processors (CPUs) and other system resources. Each CPU executes a single task at a time. However, multitasking allows each processor to switch between tasks that are being executed without having to wait for each task to finish. Depending on the operating system implementation, switches could be performed when tasks perform input/output operations, when a task indicates that it can be switched, or on hardware interrupts.

A common form of multitasking is time-sharing. Time-sharing is a method to allow fast response for interactive user applications. In time-sharing systems, context switches are performed rapidly. This makes it seem like multiple processes are being executed simultaneously on the same processor. The execution of multiple processes seemingly simultaneously is called concurrency. For security and reliability reasons most modern operating systems prevent direct communication between independent processes, providing strictly mediated and controlled inter-process communication functionality.

In general, a computer system process consists of the following resources: An image of the executable machine code associated with a program. Memory (typically some region of virtual memory); which includes the executable code, process-specific data (input and output), a call stack (to keep track of active subroutines and/or other events), and a heap to hold intermediate computation data generated during run time. Operating system descriptors of resources that are allocated to the process, such as file descriptors (Unix terminology) or handles (Windows), and data sources and sinks. Security attributes, such as the process owner and the process' set of permissions (allowable operations). Processor state (context), such as the content of registers, physical memory addressing, etc. The state is typically stored in computer registers when the process is executing, and in memory otherwise.

The operating system holds most of this information about active processes in data structures called process control blocks. Any subset of resource, but typically at least the processor state, may be associated with each of the process' threads in operating systems that support threads or 'daughter' processes.

The operating system keeps its processes separated and allocates the resources they need, so that they are less likely to interfere with each other and cause system failures (e.g., deadlock or thrashing). The operating system may also provide mechanisms for inter-process communication to enable processes to interact in safe and predictable ways.

A multitasking operating system may just switch between processes to give the appearance of many processes executing concurrently or simultaneously, though in fact only one process can be executing at any one time on a single-core CPU (unless using multithreading or other similar technology).

It is usual to associate a single process with a main program, and 'daughter' ('child') processes with any spin-off, parallel processes, which behave like asynchronous subroutines. A process is said to own resources, of which an image of its program (in memory) is one such resource. (Note, however, that in multiprocessing systems, many processes may run off of, or share, the same reentrant program at the same location in memory— but each process is said to own its own image of the program.) Processes are often called "tasks" in embedded operating systems. The sense of "process" (or task) is "something that takes up time", as opposed to 'memory', which is "something that takes up space".

The above description applies to both processes managed by an operating system, and processes as defined by process calculi. If a process requests something for which it must wait, it will be blocked. When the process is in the Blocked State, it is eligible for swapping to disk, but this is transparent in a virtual memory system, where blocks of memory values may be really on disk and not in main memory at any time. Note that even unused portions of active processes/tasks (executing programs) are eligible for swapping to disk. All parts of an executing program and its data do not have to be in physical memory for the associated process to be active.

Primary process states
The following typical process states are possible on computer systems of all kinds. In most of these states, processes are "stored" on main memory.

Created
(Also called New) When a process is first created, it occupies the "created" or "new" state. In this state, the process awaits admission to the "ready" state. This admission will be approved or delayed by a long-term, or admission, scheduler. Typically in most desktop computer systems, this admission will be approved automatically, however for real-time operating systems this admission may be delayed. In a real time system, admitting too many processes to the "ready" state may lead to oversaturation and overcontention for the systems resources, leading to an inability to meet process deadlines.

Ready or waiting
A "ready" or "waiting" process has been loaded into main memory and is awaiting execution on a CPU (to be context switched onto the CPU by the dispatcher, or short-term scheduler). There may be many "ready" processes at any one point of the system's execution—for example, in a one-processor system, only one process can be executing at any one time, and all other "concurrently executing" processes will be waiting for execution. A ready queue or run queue is used in computer scheduling. Modern computers are capable of running many different programs or processes at the same time. However, the CPU is only capable of handling one process at a time. Processes that are ready for the CPU are kept in a queue for "ready" processes. Other processes that are waiting for an event to occur, such as loading information from a hard drive or waiting on an internet connection, are not in the ready queue.

Running
A process moves into the running state when it is chosen for execution. The process's instructions are executed by one of the CPUs (or cores) of the system. There is at most one running process per CPU or core.

Blocked
A process that is blocked on some event (such as I/O operation completion or a signal). A process may be blocked due to various reasons such as when a particular process has exhausted the CPU time allocated to it or it is waiting for an event to occur.

Terminated
A process may be terminated, either from the "running" state by completing its execution or by explicitly being killed. In either of these cases, the process moves to the "terminated" state. If a process is not removed from memory after entering this state, it may become a Zombie process.

Additional process states
Two additional states are available for processes in systems that support virtual memory. In both of these states, processes are "stored" on secondary memory (typically a hard disk).

Swapped out and waiting
(Also called suspended and waiting.) In systems that support virtual memory, a process may be swapped out, that is removed from main memory and placed in virtual memory by the mid-term scheduler. From here the process may be swapped back into the waiting state.

Swapped out and blocked
(Also called suspended and blocked.) Processes that are blocked may also be swapped out. In this event the process is both swapped out and blocked, and may be swapped back in again under the same circumstances as a swapped out and waiting process (although in this case, the process will move to the blocked state, and may still be waiting for a resource to become available).

Inter-process communication (IPC)
Is a set of methods for the exchange of data among multiple threads in one or more processes. Processes may be running on one or more computers connected by a network. IPC methods are divided into methods for message passing, synchronization, shared memory, and remote procedure calls (RPC). The method of IPC used may vary based on the bandwidth and latency of communication between the threads, and the type of data being communicated.

There are several reasons for providing an environment that allows process cooperation: Information session Computational Speedup Modularity Convenience Privilege separation IPC may also be referred to as inter-thread communication and inter-application communication. The combination of IPC with the address space concept is the foundation for address space independence/isolation.

Thread
It is the smallest sequence of programmed instructions that can be managed independently by an operating system scheduler. A thread is a light-weight process. The implementation of threads and processes differs from one operating system to another, but in most cases, a thread is contained inside a process. Multiple threads can exist within the same process and share resources such as memory, while different processes do not share these resources. In particular, the threads of a process share the latter's instructions (its code) and its context (the values that its variables reference at any given moment).

On a single processor, multithreading generally occurs by time-division multiplexing (as in multitasking): the processor switches between different threads. This context switching generally happens frequently enough that the user perceives the threads or tasks as running at the same time. On a multiprocessor (including multi-core system), the threads or tasks will actually run at the same time, with each processor or core running a particular thread or task.

Many modern operating systems directly support both time-sliced and multiprocessor threading with a process scheduler. The kernel of an operating system allows programmers to manipulate threads via the system call interface. Some implementations are called a kernel thread, whereas a lightweight process (LWP) is a specific type of kernel thread that shares the same state and information. Programs can have user-space threads when threading with timers, signals, or other methods to interrupt their own execution, performing a sort of ad-hoc time-slicing.

Threads differ from traditional multitasking operating system processes in that: processes are typically independent, while threads exist as subsets of a process processes carry considerably more state information than threads, whereas multiple threads within a process share process state as well as memory and other resources processes have separate address spaces, whereas threads share their address space processes interact only through system-provided inter-process communication mechanisms context switching between threads in the same process is typically faster than context switching between processes. Systems like Windows NT and OS/2 are said to have "cheap" threads and "expensive" processes; in other operating systems there is not so great a difference except the cost of address space switch which implies a TLB flush.

Multithreading
Multi-threading is a widespread programming and execution model that allows multiple threads to exist within the context of a single process. These threads share the process' resources, but are able to execute independently. The threaded programming model provides developers with a useful abstraction of concurrent execution. However, perhaps the most interesting application of the technology is when it is applied to a single process to enable parallel execution on a multiprocessing system.

This advantage of a multithreaded program allows it to operate faster on computer systems that have multiple CPUs, CPUs with multiple cores, or across a cluster of machines — because the threads of the program naturally lend themselves to truly concurrent execution. In such a case, the programmer needs to be careful to avoid race conditions, and other non-intuitive behaviors. In order for data to be correctly manipulated, threads will often need to rendezvous in time in order to process the data in the correct order. Threads may also require mutually exclusive operations (often implemented using semaphores) in order to prevent common data from being simultaneously modified, or read while in the process of being modified. Careless use of such primitives can lead to deadlocks.

Another use of multithreading, applicable even for single-CPU systems, is the ability for an application to remain responsive to input. In a single-threaded program, if the main execution thread blocks on a long-running task, the entire application can appear to freeze. By moving such long-running tasks to a worker thread that runs concurrently with the main execution thread, it is possible for the application to remain responsive to user input while executing tasks in the background. On the other hand, in most cases multithreading is not the only way to keep a program responsive, with non-blocking I/O and/or Unix signals being available for gaining similar results.

Operating systems schedule threads in one of two ways:


 * 1) Preemptive multitasking is generally considered the superior approach, as it allows the operating system to determine when a context switch should occur. The disadvantage to preemptive multithreading is that the system may make a context switch at an inappropriate time, causing lock convoy, priority inversion or other negative effects which may be avoided by cooperative multithreading.
 * 2) Cooperative multithreading, on the other hand, relies on the threads themselves to relinquish control once they are at a stopping point. This can create problems if a thread is waiting for a resource to become available.

Until the late 1990s, CPUs in desktop computers did not have much support for multithreading, although threads were still used on such computers because switching between threads was generally still quicker than full process context switches. Processors in embedded systems, which have higher requirements for real-time behaviors, might support multithreading by decreasing the thread-switch time, perhaps by allocating a dedicated register file for each thread instead of saving/restoring a common register file. In the late 1990s, the idea of executing instructions from multiple threads simultaneously, known as simultaneous multithreading, had reached desktops with Intel's Pentium 4 processor, under the name hyper threading. It has been dropped from Intel Core and Core 2 architectures, but later was re-instated in Core i3, Core i5 and Core i7 architectures.

Processes, kernel threads, user threads, and fibers
A process is the "heaviest" unit of kernel scheduling. Processes own resources allocated by the operating system. Resources include memory, file handles, sockets, device handles, and windows. Processes do not share address spaces or file resources except through explicit methods such as inheriting file handles or shared memory segments, or mapping the same file in a shared way. Processes are typically preemptively multitasked.

A kernel thread is the "lightest" unit of kernel scheduling. At least one kernel thread exists within each process. If multiple kernel threads can exist within a process, then they share the same memory and file resources. Kernel threads are preemptively multitasked if the operating system's process scheduler is preemptive. Kernel threads do not own resources except for a stack, a copy of the registers including the program counter, and thread-local storage (if any). The kernel can assign one thread to each logical core in a system (because each processor splits itself up into multiple logical cores if it supports multithreading, or only support one logical core per physical core if it does not support multithreading), and can swap out threads that get blocked. However, kernel threads take much longer than user threads to be swapped.

Threads are sometimes implemented in userspace libraries, thus called user threads. The kernel is not aware of them, so they are managed and scheduled in userspace. Some implementations base their user threads on top of several kernel threads to benefit from multi-processor machines (M:N model). In this article the term "thread" (without kernel or user qualifier) defaults to referring to kernel threads. User threads as implemented by virtual machines are also called green threads. User threads are generally fast to create and manage, but cannot take advantage of multithreading or multiprocessing and get blocked if all of their associated kernel threads get blocked even if there are some user threads that are ready to run.

Fibers are an even lighter unit of scheduling which are cooperatively scheduled: a running fiber must explicitly "yield" to allow another fiber to run, which makes their implementation much easier than kernel or user threads. A fiber can be scheduled to run in any thread in the same process. This permits applications to gain performance improvements by managing scheduling themselves, instead of relying on the kernel scheduler (which may not be tuned for the application). Parallel programming environments such as OpenMP typically implement their tasks through fibers. Closely related to fibers are coroutines, with the distinction being that coroutines are a language-level construct, while fibers are a system-level construct.

Concurrency and data structures
Threads in the same process share the same address space. This allows concurrently running code to couple tightly and conveniently exchange data without the overhead or complexity of an IPC. When shared between threads, however, even simple data structures become prone to race hazards if they require more than one CPU instruction to update: two threads may end up attempting to update the data structure at the same time and find it unexpectedly changing underfoot. Bugs caused by race hazards can be very difficult to reproduce and isolate.

To prevent this, threading APIs offer synchronization primitives such as mutexes to lock data structures against concurrent access. On uniprocessor systems, a thread running into a locked mutex must sleep and hence trigger a context switch. On multi-processor systems, the thread may instead poll the mutex in a spinlock. Both of these may sap performance and force processors in SMP systems to contend for the memory bus, especially if the granularity of the locking is fine.

I/O and scheduling
User thread or fiber implementations are typically entirely in userspace. As a result, context switching between user threads or fibers within the same process is extremely efficient because it does not require any interaction with the kernel at all: a context switch can be performed by locally saving the CPU registers used by the currently executing user thread or fiber and then loading the registers required by the user thread or fiber to be executed. Since scheduling occurs in userspace, the scheduling policy can be more easily tailored to the requirements of the program's workload.

However, the use of blocking system calls in user threads (as opposed to kernel threads) or fibers can be problematic. If a user thread or a fiber performs a system call that blocks, the other user threads and fibers in the process are unable to run until the system call returns. A typical example of this problem is when performing I/O: most programs are written to perform I/O synchronously. When an I/O operation is initiated, a system call is made, and does not return until the I/O operation has been completed. In the intervening period, the entire process is "blocked" by the kernel and cannot run, which starves other user threads and fibers in the same process from executing.

A common solution to this problem is providing an I/O API that implements a synchronous interface by using non-blocking I/O internally, and scheduling another user thread or fiber while the I/O operation is in progress. Similar solutions can be provided for other blocking system calls. Alternatively, the program can be written to avoid the use of synchronous I/O or other blocking system calls.

SunOS 4.x implemented "light-weight processes" or LWPs. NetBSD 2.x+, and DragonFly BSD implement LWPs as kernel threads (1:1 model). SunOS 5.2 through SunOS 5.8 as well as NetBSD 2 to NetBSD 4 implemented a two level model, multiplexing one or more user level threads on each kernel thread (M:N model). SunOS 5.9 and later, as well as NetBSD 5 eliminated user threads support, returning to a 1:1 model. FreeBSD 5 implemented M:N model. FreeBSD 6 supported both 1:1 and M:N, user could choose which one should be used with a given program using /etc/libmap.conf. Starting with FreeBSD 7, the 1:1 became the default. FreeBSD 8 no longer supports the M:N model.

The use of kernel threads simplifies user code by moving some of the most complex aspects of threading into the kernel. The program doesn't need to schedule threads or explicitly yield the processor. User code can be written in a familiar procedural style, including calls to blocking APIs, without starving other threads. However, kernel threading may force a context switch between threads at any time, and thus expose race hazards and concurrency bugs that would otherwise lie latent. On SMP systems, this is further exacerbated because kernel threads may literally execute concurrently on separate processors.

1:1 (Kernel-level threading)
Threads created by the user are in 1-1 correspondence with schedulable entities in the kernel. This is the simplest possible threading implementation. Win32 used this approach from the start. On Linux, the usual C library implements this approach (via the NPTL or older LinuxThreads). The same approach is used by Solaris, NetBSD and FreeBSD.

N:1 (User-level threading)
An N:1 model implies that all application-level threads map to a single kernel-level scheduled entity; the kernel has no knowledge of the application threads. With this approach, context switching can be done very quickly and, in addition, it can be implemented even on simple kernels which do not support threading. One of the major drawbacks however is that it cannot benefit from the hardware acceleration on multi-threaded processors or multi-processor computers: there is never more than one thread being scheduled at the same time. For example: If one of the threads needs to execute an I/O request, the whole process is blocked and the threading advantage cannot be utilized. The GNU Portable Threads uses User-level threading.

M:N (Hybrid threading)
M:N maps some M number of application threads onto some N number of kernel entities, or "virtual processors." This is a compromise between kernel-level ("1:1") and user-level ("N:1") threading. In general, "M:N" threading systems are more complex to implement than either kernel or user threads, because changes to both kernel and user-space code are required. In the M:N implementation, the threading library is responsible for scheduling user threads on the available schedulable entities; this makes context switching of threads very fast, as it avoids system calls. However, this increases complexity and the likelihood of priority inversion, as well as suboptimal scheduling without extensive (and expensive) coordination between the userland scheduler and the kernel scheduler.

Hybrid implementation examples

 * Scheduler activations used by the NetBSD native POSIX threads library implementation (an M:N model as opposed to a 1:1 kernel or userspace implementation model)
 * Marcel from the PM2 project.
 * The OS for the Tera/Cray MTA
 * Microsoft Windows 7

Fiber implementation examples
Fibers can be implemented without operating system support, although some operating systems or libraries provide explicit support for them.
 * Win32 supplies a fiber API CreateFiber, MSDN (Windows NT 3.51 SP3 and later)
 * Ruby as Green threads
 * Netscape Portable Runtime (includes a user-space fibers implementation)

Process Control Block (PCB, also called Task Controlling Block, Task Struct, or Switchframe) is a data structure in the operating system kernel containing the information needed to manage a particular process. The PCB is "the manifestation of a process in an operating system". pages 57-58

If the mission of the operating system is to manage computing resources on behalf of processes, then it must be continuously informed about the status of each process and resource. The approach commonly followed to represent this information is to create and update status tables for each relevant entity, like memory, I/O devices, files and processes. Memory tables, for example, may contain information about the allocation of main and secondary (virtual) memory for each process, authorization attributes for accessing memory areas shared among different processes, etc. I/O tables may have entries stating the availability of a device or its assignment to a process, the status of I/O operations being executed, the location of memory buffers used for them, etc. File tables provide info about location and status of files (of course, what else? more on this later). Finally, process tables store the data the OS needs to manage processes. At least part of the process control data structure is always maintained in main memory, though its exact location and configuration varies with the OS and the memory management technique it uses. In the following we'll refer by process image to the complete physical manifestation of a process, which includes instructions, program data areas (both static and dynamic - e.g. at least a stack for procedure calls and parameter passing) and the process management information. We'll call this last set the process control block (PCB).

The role of the PCBs is central in process management: they are accessed and/or modified by most OS utilities, including those involved with scheduling, memory and I/O resource access and performance monitoring. It can be said that the set of the PCBs defines the current state of the operating system. Data structuring for processes is often done in terms of PCBs. For example, pointers to other PCBs inside a PCB allow the creation of those queues of processes in various scheduling states ("ready", "blocked", etc.) that we previously mentioned.

In modern sophisticated multitasking systems the PCB stores many different items of data, all needed for correct and efficient process management. Though the details of these structures are obviously system-dependent, we can identify some very common parts, and classify them in three main categories:

Process identification data; Processor state data; Process control data; Process identification data always include a unique identifier for the process (almost invariably an integer number) and, in a multiuser-multitasking system, data like the identifier of the parent process, user identifier, user group identifier, etc. The process id is particularly relevant, since it's often used to cross-reference the OS tables defined above, e.g. allowing to identify which process is using which I/O devices, or memory areas.

Processor state data are those pieces of information that define the status of a process when it's suspended, allowing the OS to restart it later and still execute correctly. This always include the content of the CPU general-purpose registers, the CPU process status word, stack and frame pointers etc.

Process control information is used by the OS to manage the process itself. This includes:

The process scheduling state (different from the task state above discussed), e.g. in terms of "ready", "suspended", etc., and other scheduling information as well, like a priority value, the amount of time elapsed since the process gained control of the CPU or since it was suspended. Also, in case of a suspended process, event identification data must be recorded for the event the process is waiting for. Process structuring information:process's children id's, or the id's of other processes related to the current one in some functional way, which may be represented as a queue, a ring or other data structures. Interprocess communication information: various flags, signals and messages associated with the communication among independent processes may be stored in the PCB. Process privileges, in terms of allowed/unallowed access to system resources.

Accounting information.

Included information
Implementations differ, but in general a PCB will include, directly or indirectly:


 * The identifier of the process (a process identifier, or PID)
 * Register values for the process including, notably, the program counter and stack pointer values for the process.
 * The address space for the process
 * Priority (in which higher priority process gets first preference. e.g., nice value on Unix operating systems)
 * Process accounting information, such as when the process was last run, how much CPU time it has accumulated, etc.
 * Pointer to the next PCB i.e. pointer to the PCB of the next process to run
 * I/O Information (i.e. I/O devices allocated to this process, list of opened files, etc.)

During context switch, the running process is stopped and another process is given a chance to run. The kernel must stop the execution of the running process, copy out the values in hardware registers to its PCB, and update the hardware registers with the values from the PCB of the new process.

A process in an operating system is represented by a data structure known as a process control block (PCB) or process descriptor. The PCB contains important information about the specific process including


 * The current state of the process i.e., whether it is ready, running, waiting etc.
 * Unique identification of the process in order to track "which is which" information.
 * A pointer to parent process.
 * Similarly, a pointer to child process (if it exists).
 * The priority of process (a part of CPU scheduling information).
 * Pointers to locate memory of processes.
 * A register save area.
 * The processor it is running on.

The PCB is a certain store that allows the operating systems to locate key information about a process. Thus, the PCB is the data structure that defines a process to the operating systems.

Location of the PCB
Since PCB contains the critical information for the process, it must be kept in an area of memory protected from normal user access. In some operating systems the PCB is placed in the beginning of the kernel stack of the process since that is a convenient protected location.Yong, Zhang, "Breaking through the Maximum Process Number", Linux Journal, 1 Jan 2004,.