Overlapping computation and communication

Definition

Overlapping computation and communication refers to the ability to perform calculations while simultaneously sending or receiving data in a parallel computing environment. This technique is crucial for optimizing performance, as it allows systems to make better use of their resources and minimize idle time, leading to faster overall execution. Efficiently overlapping these two processes can significantly enhance the throughput of parallel programs by keeping all parts of the system busy.

5 Must Know Facts For Your Next Test

1. Overlapping computation and communication is often achieved using non-blocking communication methods, which allow processes to send and receive messages without halting their computations.
2. Effective use of this technique can lead to improved application scalability, as it reduces the time processes spend waiting for data transfers to complete.
3. By carefully structuring algorithms and using optimized libraries, developers can maximize the amount of computation performed while data is being communicated.
4. It’s essential to analyze the specific architecture and network characteristics to effectively overlap these operations, as different systems may have varying capabilities.
5. Achieving optimal overlap requires an understanding of both the computational workload and the communication patterns within the application to prevent bottlenecks.

Review Questions

• How does overlapping computation and communication improve performance in parallel applications?
  • Overlapping computation and communication enhances performance by ensuring that processes remain active instead of idling during data transfers. When calculations are conducted while data is sent or received, it maximizes resource utilization. This concurrent execution reduces the overall runtime of applications, especially in environments where latency and bandwidth can limit efficiency.
• Discuss how non-blocking communication plays a role in achieving effective overlapping of computation and communication.
  • Non-blocking communication allows processes to initiate data transfers without waiting for them to complete, enabling them to continue executing other computations concurrently. This characteristic is crucial for achieving effective overlap because it prevents delays caused by waiting for messages. By using non-blocking calls, developers can structure their algorithms so that they perform useful work while data is being communicated, leading to higher throughput and reduced execution time.
• Evaluate the impact of architecture-specific factors on the implementation of overlapping computation and communication in parallel systems.
  • The effectiveness of overlapping computation and communication can vary significantly based on architecture-specific factors such as network latency, bandwidth capabilities, and memory access patterns. Systems with low latency and high bandwidth will benefit more from overlapping since they allow quicker data exchanges during computations. Conversely, architectures with high latency or limited bandwidth may face challenges that hinder effective overlap, necessitating adjustments in algorithm design or communication strategies to optimize performance.

Related terms

Latency:

The time delay between initiating a request for data and receiving that data, which can impact the efficiency of communication in parallel computing.

Bandwidth: The maximum rate at which data can be transferred over a communication channel, influencing how quickly data can be sent or received during operations.

Non-blocking Communication:

A communication method that allows a process to continue executing while the communication operation is being completed, facilitating better overlap of computation and communication.