Benchmark: Gain to dB LN10 vs log10

HTML Preparation code:

<!--your preparation HTML code goes here-->

Script Preparation code:

function gainToDbLN10(gain) {
	return 20 * (Math.log(gain) / Math.LN10);
}

function gainToDbLog10(gain) {
    return 20 * Math.log10(gain);
}

Tests:

LN10
gainToDbLN10(3);
Log10
gainToDbLog10(3);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
LN10
Log10

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/137.0.0.0 Safari/537.36

Browser/OS: Chrome 137 on Mac OS X 10.15.7

View result in a separate tab

LN10

278.3M/s

Log10

256.6M/s

View exact numbers

Test name	Executions per second
✓ LN10	278,258,496 Ops/sec
Log10	256,590,240 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

LLMs can make mistakes. Check important info.

The benchmark defined in the provided JSON tests the performance of two functions that convert gain values into decibels. The functions accomplish this using different logarithmic bases: natural logarithm (base e) for LN10 and common logarithm (base 10) for log10. Here’s a breakdown of the benchmark, its options, pros/cons, and other considerations:

### Functions Being Tested

1. **gainToDbLN10(gain)**:
   - **Calculation**: This function uses the natural logarithm, specifically `Math.log()` divided by `Math.LN10`.
   - **Purpose**: Converts a gain value to decibels using natural logarithm. The factor of 20 is standard in dB calculations related to power.

2. **gainToDbLog10(gain)**:
   - **Calculation**: This function directly employs `Math.log10()`, which is specifically optimized for logarithms with base 10.
   - **Purpose**: Converts the gain value to decibels using the more straightforward calculation of base 10 logarithm.

### Test Cases

1. **Test Case 1 - LN10**:
   - **Benchmark Definition**: `gainToDbLN10(3);`
   - **Executions per Second**: 278,258,496 (indicating high performance)
   
2. **Test Case 2 - Log10**:
   - **Benchmark Definition**: `gainToDbLog10(3);`
   - **Executions per Second**: 256,590,240 (also indicating high performance, but slightly lower than LN10)

### Performance and Comparison

- **Results**: 
  - `gainToDbLN10`: In this particular test setup, it outperformed the `gainToDbLog10` function, executing significantly more times per second.
  - `gainToDbLog10`: While very close in performance, it showed a slightly lower rate of execution.

### Pros and Cons

#### Using `gainToDbLN10` (Natural Logarithm):
- **Pros**:
  - In some mathematical applications, natural logarithms are more commonly used, especially in continuous systems.
  - Can be more efficient in scenarios where the calculation involves combinations of exponential and logarithmic functions.
- **Cons**:
  - Slightly more complex calculation due to division by `Math.LN10`, which could introduce negligible overhead.

#### Using `gainToDbLog10` (Common Logarithm):
- **Pros**:
  - Direct and potentially simpler calculation as `Math.log10()` is specifically optimized for base-10 logarithms.
  - More straightforward interpretation and better understood in broad applications, particularly in audio and signal processing contexts.
- **Cons**:
  - In this benchmark, it performed slightly slower than the natural log variant.

### Other Alternatives

Apart from these two approaches, one could consider the following alternatives for converting gain to decibels:

1. **Custom Logarithm Implementation**:
   - Implementing logarithm functions without relying on built-in library functions which can be useful in environments where such functions are not available or to gain additional control over performance.
   
2. **Use of Libraries**:
   - Libraries like Math.js which may provide additional mathematical operations and optimizations, although they might introduce overhead due to their size.

3. **Pre-computed Tables**:
   - For fixed values of gain, pre-computed logarithmic values can be stored and accessed to save on computation time, applicable in real-time systems where performance is crucial.

In conclusion, while both logarithmic approaches serve the same purpose, the choice between them can depend on the specific context of the application and the underlying performance characteristics as highlighted in the benchmark results. The evident performance advantage of `gainToDbLN10` in this case provides a compelling argument for its use, despite the marginal complexity.

Gain to dB LN10 vs log10 (version: 1)

Comparing performance of: `LN10 vs Log10`

Created: one year ago by: Registered User

Go to the latest result

LN10

Log10

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

Gain to dB LN10 vs log10 (version: 1)

Comparing performance of: LN10 vs Log10

Created: one year ago by: Registered User

Go to the latest result

LN10

Log10

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

Related benchmarks

Comparing performance of: `LN10 vs Log10`