Performance and Memory Optimization

Learn performance and memory optimization through an executable example, then connect the small demonstration to production code.

Performance tuning starts with measurements: go test -bench . -benchmem, CPU profiles and allocation profiles. Use simple optimizations after identifying a bottleneck.

Preallocating known slice capacity can avoid repeated growth allocations, but it consumes memory up front. Benchmark realistic workloads before committing an optimization.

Follow this diagram before executing the example. Check where a value or decision changes what runs next.

Useful tools: go test -bench . -benchmem, go test -cpuprofile cpu.out, go test -memprofile mem.out, and go tool pprof.

This example is a complete program. Save it as main.go or paste it into the Go Playground.

Go code

package main

import "fmt"

func squares(n int) []int {
	values := make([]int, 0, n)
	for i := 1; i <= n; i++ {
		values = append(values, i*i)
	}
	return values
}
func main() {
	nums := squares(4)
	fmt.Println("Values:", nums, "Length:", len(nums), "Capacity:", cap(nums))
}

Output

Values: [1 4 9 16] Length: 4 Capacity: 4

The slice begins with length zero and capacity four. Four appended squares fill its reserved storage without requiring capacity growth.

• Allocations and escape decisions depend on compiler optimization; do not claim a fixed heap layout.
• A benchmark must avoid accidental dead-code elimination or unrepresentative workloads.

Benchmark this implementation against a nil-slice version using go test -benchmem.

Tip: Edit the example above, predict the output, and run the modified code to test your reasoning.

You have practiced Performance and Memory Optimization in a small, self-contained program. The important habit is to predict what runs, inspect the actual output and distinguish the language rule from the particular example.

Before continuing, make sure you can explain the program to someone who has not seen it, including the line that changes its result.