Parallel and Distributed Computing

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Deadlock

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Parallel and Distributed Computing

Definition

Deadlock is a situation in computing where two or more processes are unable to proceed because each is waiting for the other to release a resource. It represents a major challenge in parallel computing as it can halt progress in systems that require synchronization and resource sharing.

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5 Must Know Facts For Your Next Test

  1. Deadlocks can occur in both shared memory and message passing programming models when multiple processes compete for limited resources.
  2. There are four necessary conditions for a deadlock to occur: mutual exclusion, hold and wait, no preemption, and circular wait.
  3. Deadlock detection algorithms can be implemented to identify deadlocks after they have occurred, allowing the system to recover by terminating or rolling back processes.
  4. Preventing deadlocks involves techniques such as resource ordering, which ensures that processes request resources in a predefined sequence.
  5. In distributed systems, deadlock detection becomes more complex due to the lack of centralized control, requiring more sophisticated approaches for resolution.

Review Questions

  • How does deadlock specifically impact the performance of parallel computing systems?
    • Deadlock significantly hampers the performance of parallel computing systems as it leads to a complete standstill of processes involved. When multiple processes enter a deadlock state, none can proceed or complete their tasks, effectively wasting system resources. This situation is particularly problematic in environments that rely on efficient resource sharing and synchronization among processes, making it crucial to implement effective deadlock prevention or detection mechanisms.
  • Compare and contrast how deadlock is handled in shared memory versus message passing programming models.
    • In shared memory programming models, deadlocks are often managed through synchronization primitives such as locks or semaphores, which can introduce the risk of deadlock if not used carefully. On the other hand, in message passing models, deadlock may occur during message exchanges when processes wait indefinitely for messages from each other. Each model requires different strategies for deadlock avoidance or detection due to their inherent differences in resource management and communication methods.
  • Evaluate the effectiveness of different strategies for preventing deadlocks in distributed systems and how they impact overall system reliability.
    • Strategies for preventing deadlocks in distributed systems include resource ordering, where resources are requested in a specific sequence, and timeout mechanisms that force processes to release resources after a set time. While these methods can significantly reduce the likelihood of deadlocks occurring, they may introduce complexity and overhead. Resource ordering can limit flexibility and increase contention, while timeouts may lead to premature resource release, affecting overall system reliability. Therefore, finding a balance between prevention measures and system efficiency is critical for maintaining robust distributed computing environments.
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