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(version: 0)
Comparing performance of:
branched vs not branched
Created:
5 years ago
by:
Guest
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Script Preparation code:
const ARRAY_LENGTH = 1000000 x = Array.from(Array(ARRAY_LENGTH)).map(x=>Math.random())
Tests:
branched
let moreThan50 = 0; const reducer = (accumulator, currentValue) => { if(currentValue < .5) { accumulator + 1; } } console.log(x.reduce(reducer))
not branched
let moreThan50 = 0; const reducer = (accumulator, currentValue) => { accumulator + (currentValue < .5) } console.log(x.reduce(reducer))
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
branched
not branched
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'd be happy to explain what's being tested in the provided benchmark. **Benchmark Definition** The benchmark is defined by two different scripts, which will be executed and compared. The main difference between the two scripts lies in the branching logic used in the `reduce` function. **Unrolled Reduction vs Branchless Reduction** 1. **Unrolled Reduction**: In this approach, the `reduce` function is implemented with a branching condition (`if` statement). If the current value is less than 0.5, it increments the accumulator. 2. **Branchless Reduction**: In this alternative approach, the branching condition is eliminated by using bitwise operators to achieve the same result. The expression `(currentValue < .5)` is replaced with `currentValue < 0.5`, which can be implemented using a single bitwise operation. **Options Compared** The benchmark tests the performance difference between these two approaches: * Unrolled Reduction (with branching) * Branchless Reduction **Pros and Cons of Each Approach** 1. **Unrolled Reduction**: * Pros: Simpler to understand and implement, especially for those without deep knowledge of bitwise operations. * Cons: May be slower due to the overhead of branching and conditional jumps. 2. **Branchless Reduction**: * Pros: Can be faster since it eliminates the branching overhead and uses a single operation. * Cons: Requires a deeper understanding of bitwise operations and may be harder to understand for those without experience. **Library Usage** There is no library mentioned in the benchmark definition or test cases. The benchmark relies solely on JavaScript built-in functions, such as `Array.from`, `map`, `reduce`, and bitwise operators. **Special JS Features/Syntax** There are no special JavaScript features or syntax used in this benchmark. It only utilizes standard JavaScript functionality. **Other Alternatives** If the benchmark were to explore further optimizations, other approaches might include: * Using SIMD (Single Instruction, Multiple Data) instructions for parallel processing. * Implementing the reduction using a different algorithm, such as a custom loop-based approach. * Utilizing just-in-time (JIT) compilation or ahead-of-time (AOT) optimization to optimize performance. Keep in mind that these alternatives would likely require more significant changes to the benchmark definition and implementation.
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