Go Performance: Slice Parameters or Global Variables – Which is Faster?

Function Slice Parameter vs Global Variable Performance in Go

When designing functions, the debate between parameter passing and global variable utilization often arises. This article will delve into the performance aspects of these two approaches in the context of slice parameters in Go.

Slice Parameters

Slices in Go are lightweight, dynamic data structures that represent a portion of an array. When passing a slice as a function parameter, a copy of its header (i.e., length and capacity) is created and passed, while the underlying array remains unchanged. This copy-on-write mechanism ensures that the original slice remains unaffected by any modifications within the function.

Global Variables

Global variables are accessible throughout the program's scope. In the scenario described, if the slice is rarely modified, making it a global variable might seem like an optimization. However, this approach introduces a few drawbacks:

• Reduced Cache Locality: Global variables may reside in distant memory locations, leading to potential cache misses and performance degradation.
• Concurrency Issues: In concurrent Go programs, accessing shared global variables can introduce race conditions and data corruption.

Performance Evaluation

Benchmarking experiments have shown that the performance difference between using slice parameters and global variables is negligible. Slice passing involves a small cost of copying the header, but the benefits of preserving cache locality and avoiding concurrency issues often outweigh this overhead.

Conclusion

For performance-sensitive scenarios, passing slices as parameters is generally recommended over using global variables. It provides improved cache locality, eliminates concurrency concerns, and allows for flexibility in passing modified slices to other functions without affecting the original data. However, global variables may be considered when slice arguments are massive and rarely change, as they can potentially save memory by reusing the same backing array. Ultimately, careful consideration of the specific requirements of the program is crucial when making this decision.

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