Home Backend Development Golang Arrays vs. Slices in Go: Which Offers Faster Element Access?

Arrays vs. Slices in Go: Which Offers Faster Element Access?

Dec 02, 2024 pm 01:52 PM

Arrays vs. Slices in Go: Which Offers Faster Element Access?

Array vs Slice: Accessing Speed

Performance Comparison between Arrays and Slices

This post investigates the accessing speed of arrays and slices in Go. A benchmark test was conducted to compare the performance of global and local arrays with global and local slices.

Benchmark Results

The typical benchmark results show that accessing global slices (4210 ns/op) is slightly slower than accessing global arrays (4123 ns/op). However, accessing local slices (3090 ns/op) is significantly faster than accessing local arrays (3768 ns/op).

Explanation of Results

The variance in accessing speed can be attributed to differences in memory handling and data locality. Arrays are allocated as contiguous memory blocks, while slices consist of pointers to array elements. Hence, accessing an element in a slice involves additional operations compared to an array.

Local Array vs Local Slice

The striking performance difference between local arrays and slices is caused by the fact that local arrays require multiple memory loads to access their elements. This is evident from the generated assembly code, which shows that the array version loads the address of the array into memory several times during accessing operations.

In contrast, accessing elements in local slices involves performing operations exclusively on registers after loading the slice header once from memory. This optimized approach eliminates the need for multiple memory loads, resulting in faster execution.

Conclusion

Although arrays may have certain advantages, the benchmark results demonstrate that slices offer significant speed benefits when accessing elements, especially in the case of local variables. This performance difference is due to the slices' efficient memory management and data locality, which optimize element access operations by reducing the need for memory loads.

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