In computer science, asynchronous I/O (also non-sequential I/O) is a form of input/output processing that permits other processing to continue before the transmission has finished. A name used for asynchronous I/O in the Windows API is overlapped I/O.
Input and output (I/O) operations on a computer can be extremely slow compared to the processing of data. An I/O device can incorporate mechanical devices that must physically move, such as a hard drive seeking a track to read or write; this is often orders of magnitude slower than the switching of electric current. For example, during a disk operation that takes ten milliseconds to perform, a processor that is clocked at one gigahertz could have performed ten million instruction-processing cycles.
A simple approach to I/O would be to start the access and then wait for it to complete. But such an approach, called synchronous I/O or blocking I/O, would block the progress of a program while the communication is in progress, leaving system resources idle. When a program makes many I/O operations (such as a program mainly or largely dependent on user input), this means that the processor can spend almost all of its time idle waiting for I/O operations to complete.
Alternatively, it is possible to start the communication and then perform processing that does not require that the I/O be completed. This approach is called asynchronous input/output. Any task that depends on the I/O having completed (this includes both using the input values and critical operations that claim to assure that a write operation has been completed) still needs to wait for the I/O operation to complete, and thus is still blocked, but other processing that does not have a dependency on the I/O operation can continue.
Many operating system functions exist to implement asynchronous I/O at many levels. In fact, one of the main functions of all but the most rudimentary of operating systems is to perform at least some form of basic asynchronous I/O, though this may not be particularly apparent to the user or the programmer. In the simplest software solution, the hardware device status is polled at intervals to detect whether the device is ready for its next operation. (For example, the CP/M operating system was built this way. Its system call semantics did not require any more elaborate I/O structure than this, though most implementations were more complex, and thereby more efficient.) Direct memory access (DMA) can greatly increase the efficiency of a polling-based system, and hardware interrupts can eliminate the need for polling entirely. Multitasking operating systems can exploit the functionality provided by hardware interrupts, whilst hiding the complexity of interrupt handling from the user. Spooling was one of the first forms of multitasking designed to exploit asynchronous I/O. Finally, multithreading and explicit asynchronous I/O APIs within user processes can exploit asynchronous I/O further, at the cost of extra software complexity.
Asynchronous I/O is used to improve energy efficiency, and in some cases, throughput. However, it can have negative effects on latency and throughput in some cases.
Forms
Forms of I/O and examples of POSIX functions:
All forms of asynchronous I/O open applications up to potential resource conflicts and associated failure. Careful programming (often using mutual exclusion, semaphores, etc.) is required to prevent this.
When exposing asynchronous I/O to applications there are a few broad classes of implementation. The form of the API provided to the application does not necessarily correspond with the mechanism actually provided by the operating system; emulations are possible. Furthermore, more than one method may be used by a single application, depending on its needs and the desires of its programmer(s). Many operating systems provide more than one of these mechanisms, it is possible that some may provide all of them.
Process
Available in early Unix. In a multitasking operating system, processing can be distributed across different processes, which run independently, have their own memory, and process their own I/O flows; these flows are typically connected in pipelines. Processes are fairly expensive to create and maintain, so this solution only works well if the set of processes is small and relatively stable. It also assumes that the individual processes can operate independently, apart from processing each other's I/O; if they need to communicate in other ways, coordinating them can become difficult.
An extension of this approach is dataflow programming, which allows more complicated networks than just the chains that pipes support.