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Why Doesn't My Go Code Scale with Increased Goroutines?

Patricia Arquette
Patricia ArquetteOriginal
2024-12-27 22:48:18504browse

Why Doesn't My Go Code Scale with Increased Goroutines?

Sure, I can provide an alternative answer to the question, focusing on the crux of the scalability issue in the provided code:

Why do these goroutines not scale their performance from more concurrent executions?

The issue with the scalability of the moving_avg_concurrent2 function lies in its approach to parallelizing the computation. It divides the input slice into smaller pieces and assigns them to separate goroutines. While this approach works for a small number of goroutines, it becomes less efficient as the number of goroutines increases. As you increase the number of goroutines, the overhead of creating and managing these goroutines outweighs the benefits of parallelization.

This behavior can be attributed to two main factors:

  1. Contention for shared resources: Specifically, the buffer used to store the moving average values becomes a shared resource that multiple goroutines need to access concurrently. This contention can lead to performance degradation as the goroutines compete for access to the buffer and can also result in incorrect calculations.
  2. Increased garbage collection: As you create more goroutines, they allocate memory for their stacks. Managing these memory allocations can lead to increased garbage collection, which further impacts performance.

To effectively parallelize this function, a different approach is necessary, one that minimizes the contention for shared resources and reduces the overhead of goroutine management.

There are various strategies for improving the scalability of the code. One possible approach is to use channels to communicate between goroutines and avoid contention for shared resources, but that's a matter of code restructuring that may or may not be suitable for the specific context and requirements.

In summary, the scalability issue in moving_avg_concurrent2 arises from the increased overhead associated with managing a large number of goroutines and contention for shared resources. Addressing these issues will help improve the scalability of the code.

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