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  2. Thread safety - Wikipedia

    en.wikipedia.org/wiki/Thread_safety

    Thread safe, MT-safe: Use a mutex for every single resource to guarantee the thread to be free of race conditions when those resources are accessed by multiple threads simultaneously. Thread safety guarantees usually also include design steps to prevent or limit the risk of different forms of deadlocks , as well as optimizations to maximize ...

  3. Double-ended queue - Wikipedia

    en.wikipedia.org/wiki/Double-ended_queue

    A separate deque with threads to be executed is maintained for each processor. To execute the next thread, the processor gets the first element from the deque (using the "remove first element" deque operation). If the current thread forks, it is put back to the front of the deque ("insert element at front") and a new thread is executed.

  4. ThreadSafe - Wikipedia

    en.wikipedia.org/wiki/ThreadSafe

    ThreadSafe is a source code analysis tool that identifies application risks and security vulnerabilities associated with concurrency in Java code bases, using whole-program interprocedural analysis.

  5. Reentrancy (computing) - Wikipedia

    en.wikipedia.org/wiki/Reentrancy_(computing)

    A function can be thread-safe and still not reentrant. For example, a function could be wrapped all around with a mutex (which avoids problems in multithreading environments), but, if that function were used in an interrupt service routine, it could starve waiting for the first execution to release the mutex.

  6. Work stealing - Wikipedia

    en.wikipedia.org/wiki/Work_stealing

    The processor pops a thread off the bottom of its deque and starts executing that thread. If its deque is empty, it starts work stealing, explained below. An instruction may cause a thread to die. The behavior in this case is the same as for an instruction that stalls. An instruction may enable another thread. The other thread is pushed onto ...

  7. Concurrent data structure - Wikipedia

    en.wikipedia.org/wiki/Concurrent_data_structure

    Concurrent data structures are significantly more difficult to design and to verify as being correct than their sequential counterparts. The primary source of this additional difficulty is concurrency, exacerbated by the fact that threads must be thought of as being completely asynchronous: they are subject to operating system preemption, page faults, interrupts, and so on.

  8. Non-blocking algorithm - Wikipedia

    en.wikipedia.org/wiki/Non-blocking_algorithm

    In particular, if one thread is suspended, then a lock-free algorithm guarantees that the remaining threads can still make progress. Hence, if two threads can contend for the same mutex lock or spinlock, then the algorithm is not lock-free. (If we suspend one thread that holds the lock, then the second thread will block.)

  9. Concurrent hash table - Wikipedia

    en.wikipedia.org/wiki/Concurrent_hash_table

    This entails modifying the used hash function to reflect the new key-space of the resized table. A concurrent growing algorithm is described by Maier et al. [ 1 ] Mega-KV [ 7 ] is a high performance key-value store system, where the cuckoo hashing is used and the KV indexing is massively parallelized in batch mode by GPU.