When the currently executing process relinquishes the processor, either voluntarily or involuntarily, another process can execute its program code. This event is known as a context switch, which facilitates interleaved execution. Time-sliced, interleaved execution of program code within an address space is known as concurrency.
The Linux kernel is fully preemptive, which means that it can force a context switch for a higher priority process. When a context switch occurs, the state of a process is saved to its process control block, and another process resumes execution on the processor.
A UNIX process is considered heavyweight because it has its own address space, file descriptors, register state, and program counter. In Linux, this information is stored in the task_struct. However, when a process context switch occurs, this information must be saved, which is a computationally expensive operation.
Concurrency applies to both threads and processes. A thread is an independent sequence of execution within a UNIX process, and it is also considered a schedulable entity. Both threads and processes are scheduled for execution on a processor core, but thread context switching is lighter in weight than process context switching.
In UNIX, processes often have multiple threads of execution that share the process's memory space. When multiple threads of execution are running inside a process, they typically perform related tasks. The Linux user-space APIs for process and thread management abstract many details. However, the concurrency level can be adjusted to influence the time quantum so that the system throughput is affected by shorter and longer durations of schedulable entity execution time.
In the 1:1 model, one user-space thread is mapped to one kernel thread. This allows for true parallelism, as each thread can run on a separate processor core. However, creating and managing a large number of kernel threads can be expensive.
In the 1:N model, multiple user-space threads are mapped to a single kernel thread. This is more lightweight, as there are fewer kernel threads to create and manage. However, it does not allow for true parallelism, as only one thread can execute on a processor core at a time.
In the M:N model, N user-space threads are mapped to M kernel threads. This provides a balance between the 1:1 and 1:N models, as it allows for both true parallelism and lightweight thread creation and management. However, it can be complex to implement and can lead to issues with load balancing and resource allocation.
Parallelism on a time-sliced, preemptive operating system means the simultaneous execution of multiple schedulable entities over a time quantum. Both processes and threads can execute in parallel across multiple cores or processors. Concurrency and parallelism are at play on a multi-user system with preemptive time-slicing and multiple processor cores. Affinity scheduling refers to scheduling processes and threads across multiple cores so that their concurrent and parallel execution is close to optimal.It's worth noting that affinity scheduling refers to the practice of assigning processes or threads to specific processors or cores to optimize their execution and minimize unnecessary context switching. This can improve overall system performance by reducing cache misses and increasing cache hits, among other benefits. In contrast, non-affinity scheduling allows processes and threads to be executed on any available processor or core, which can result in more frequent context switching and lower performance.