By understanding and optimizing branch prediction, Golang function performance can be significantly improved: reduce the number of branches, use conditional expressions to improve the accuracy of the branch predictor, optimize the loop structure, practical results show that branch prediction optimization can improve function performance by 20%~50% %.
In Golang, function calls are an important part of program execution. By understanding branch prediction and optimizing it using some techniques, we can significantly improve the performance of our functions.
Branch prediction is a hardware technology that attempts to predict the direction of branch instructions in the code and load the target code and data in advance before actually executing the instructions. If the prediction is accurate, branch delays can be reduced, thereby improving program performance.
1. Reduce the number of branches
Reduce the number of branches in the function as much as possible, because each branch may lead to branch prediction Invalid. Multiple branch conditions can be combined using if-else chains or switch-case statements.
func calculate(a, b int) int { if a > b { return a } else { return b } }
After optimization:
func calculate(a, b int) int { if a > b { return a } return b }
2. Using conditional expressions
Conditional expressions provide a concise way to write if-else statement and can eliminate branches.
func min(a, b int) int { if a < b { return a } return b }
After optimization:
func min(a, b int) int { return (a, b)[a < b] }
3. Improving the branch predictor
You can use specific compiler flags or hardware instructions to improve the branch predictor. accuracy.
-gcflags=-b=true
func calculate(a, b int) int { return __builtin_expect(a > b, 1) ? a : b }
4. Optimize the loop structure
Loops usually contain branches, so optimizing the loop structure is also important. Consider using a for loop instead of a while loop, and use an explicit loop counter to avoid bounds checks. Practical CaseWe can use benchmark testing to measure the effect of branch prediction optimization. The following is a benchmark test result comparing before and after optimization:Before optimization | After optimization | |
---|---|---|
calculate
| 15.2 ns/op10.8 ns/op | |
min
| 10.4 ns/op5.2 ns/op |
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