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Threads

Multithreaded programming entails running parts of a program simultaneously, increasing CPU utilization, improving responsiveness and enabling applications to handle concurrent input/output operations efficiently. Threads are light-weight processes with their own CPU state and stack but share common data across processes.

Threads begin their lives as newborns and remain so until initiated by a program, when they transition into runnable threads that exist until either terminated by the user or until their timed waiting state expires.

Multithreaded programs must be carefully synchronized, which can be difficult. Mismatched synchronization may lead to internal race conditions wherein one thread reads data written to by another thread and thus provides incorrect or inconsistent data. Although this lab does not address synchronization directly, you must be wary to avoid race conditions and deadlocks.

Concurrency

Contrasting Multitasking, which relies on sharing resources like memory and processors, concurrency allows multiple action sequences to take place simultaneously. They may execute simultaneously or take turns progressing, waiting for other threads to complete their tasks before continuing – however they will appear as though they happened simultaneously to end users.

Embedded systems can use concurrency to shorten the time it takes them to perform complex tasks, like monitoring temperature or showing messages. They do this by breaking up each part of their task into smaller parts known as threads – small sequences of programed instructions which run sequentially on embedded systems.

Priority determines the order of execution for threads. Higher-priority threads receive more processing time, and can acquire and release locks used to prevent lower-priority threads from accessing shared resources. But locking too long could result in deadlock, creating serious security risks.

Locks

Locks are an efficient way of establishing synchronization among concurrent modules. Used correctly, locks can prevent race conditions; however, misusing them could result in deadlocks – an endless cycle where two modules keep fighting over one lock without ever leaving its synchronized region.

So for instance, when two threads attempt to Simultaneously update a record, only one succeeds and locks it preventing its updating by another thread – with no other way for this thread to unlock it since its owner never releases their hold! In such an instance, both threads will wait forever before any progress can be made due to being stopped by this first one from updating their record again.

Multithreaded programs often utilize fine-grained locks and lock ordering techniques in order to avoid deadlocks, known as optimistic locking.

Inter-thread communication

Multithreaded programming enables multiple paths of execution within a program to interact. This requires careful consideration of thread interactions and potential concurrency issues, but can increase program efficiency and performance. Unfortunately, however, multithreading can introduce complexity into program design and debugging; to reduce this hassle use proper synchronization techniques.

Message queue and semaphore are inter-thread communication mechanisms. While both can convey the state of a thread to other threads, their functions and uses differ significantly; mailboxes act like soft interrupt mechanisms while semaphore locks can only be opened by threads with specific keys.

Inter-thread Communication can help avoid deadlocks, which occur when threads wait for each other to release resources. To do this, a thread should call wait() or notify() methods within a synchronized block to avoid deadlock.