Computation/communication pipelining

Definition

Computation/communication pipelining is a parallel computing technique where multiple stages of computation and communication are overlapped to improve performance and efficiency. This method allows different parts of a program to execute concurrently, reducing idle time and increasing throughput by ensuring that while one task is being processed, another can be communicating or in a different stage of execution.

5 Must Know Facts For Your Next Test

1. Computation/communication pipelining can significantly reduce the overall execution time of a program by minimizing the time that processors remain idle.
2. This technique works well in environments where data can be processed in stages, allowing for seamless handoff between different computations and communications.
3. Effective pipelining requires careful scheduling of tasks to avoid bottlenecks, ensuring that each stage has enough data to work with as soon as it's ready.
4. Pipelining can lead to increased complexity in program design, as developers must consider how to manage dependencies and synchronize tasks effectively.
5. In distributed systems, computation/communication pipelining can enhance performance by allowing nodes to share results while continuing their computations.

Review Questions

• How does computation/communication pipelining improve overall system performance?
  • Computation/communication pipelining improves overall system performance by overlapping different stages of computation and communication. By executing tasks concurrently, it minimizes idle time where processors are waiting for data or instructions. This means while one computation is being processed, another can handle communication or transition to another stage, which ultimately increases throughput and reduces execution time.
• Discuss the challenges associated with implementing computation/communication pipelining in a distributed system.
  • Implementing computation/communication pipelining in a distributed system presents several challenges, including managing data dependencies between tasks and ensuring synchronization. If one stage of the pipeline is delayed, it can create bottlenecks that disrupt the flow of data. Additionally, network latency can affect communication between nodes, making it crucial to design systems that can handle these delays while maximizing throughput.
• Evaluate the impact of computation/communication pipelining on program design and architecture.
  • The impact of computation/communication pipelining on program design and architecture is significant, as it requires a shift in how developers approach task management. Programs must be structured to allow for concurrent execution, which can increase complexity but also lead to greater efficiency. This architectural shift necessitates careful consideration of task dependencies and scheduling to ensure that the pipeline operates smoothly, ultimately enhancing performance while adding layers of design complexity.

Related terms

Latency:

The time delay between the initiation of a request for data and the moment the data is available.

Throughput: The amount of work or data processed in a given amount of time, often used as a measure of system performance.

Parallelism: The simultaneous execution of multiple computations or processes to increase computational speed and efficiency.