Benchmark: compare pow and mult

Tests:

pow
var x = Math.pow(50,3);
mult
var y = 50 * 50 * 50

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
pow
mult

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.82 Safari/537.36

Browser/OS: Chrome 93 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
pow	3684497.2 Ops/sec
mult	577728512.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 2 months ago):

LLMs can make mistakes. Check important info.

Measuring the performance of mathematical operations in JavaScript is crucial for optimizing code and understanding browser behavior.

The provided JSON benchmark definition tests two basic mathematical operations: exponentiation (`Math.pow()`) and multiplication (`*`). The goal is to compare the performance of these two approaches.

**Options being compared:**

1. **Exponentiation using `Math.pow()`**: This method raises a number to a given power.
2. **Multiplication by repeated addition**: This approach multiplies numbers together by repeatedly adding one of the factors to itself.

**Pros and Cons of each approach:**

* **`Math.pow()`**:
	+ Pros: Shorter code, more readable, and widely supported in most programming languages.
	+ Cons: May have slower performance due to its recursive nature and use of intermediate results.
* **Multiplication by repeated addition**:
	+ Pros: Can be faster for large numbers or when memory is limited (e.g., in embedded systems).
	+ Cons: Longer code, less readable, and less supported in most programming languages.

Other considerations:

* **Cache locality**: The `Math.pow()` method can benefit from cache locality, as the intermediate results are stored in registers. In contrast, repeated multiplication without addition does not exhibit the same benefits.
* **Branch prediction**: Some browsers may be able to predict which branch to take (i.e., whether to use `Math.pow()` or multiplication by repeated addition), affecting performance.

**Library usage:**

There is no library being used explicitly in these benchmark cases. However, it's essential to note that some libraries, like NumJS or mathjs, provide optimized implementations of mathematical functions, including exponentiation and multiplication.

**Special JavaScript features/syntax:**

None are mentioned in the provided examples.

Now, let's discuss alternatives:

1. **Native WebAssembly (WASM)**: Running JavaScript code directly on WASM can provide significant performance improvements by avoiding JavaScript interpretation overhead.
2. **Just-In-Time (JIT) compilation**: Some browsers use JIT compilers to optimize JavaScript code at runtime. For example, V8 in Chrome uses a complex JIT compiler called TurboFan.
3. **Parallel processing**: Modern CPUs and GPUs support parallel execution of tasks, which can be leveraged for benchmarking and performance optimization.

When preparing benchmarks like this one, consider the following best practices:

1. Write clear, concise test cases that accurately represent real-world scenarios.
2. Use meaningful test names and descriptions to facilitate understanding and comparison between results.
3. Run multiple iterations with different inputs or variations to ensure reliable results.
4. Document benchmark settings, such as JavaScript version, browser, and device platform.
5. Consider using tools like Benchmark.js or JSPerf to simplify the process of writing and running benchmarks.

By following these guidelines, you can create high-quality benchmarks that provide actionable insights for optimizing performance in your codebase.

Related benchmarks:

compare pow and mult (version: 0)

Comparing performance of: pow vs mult

Created: 3 years ago by: Guest

Jump to the latest result

pow

mult

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 2 months ago):