Benchmark: js timestamp cost

Script Preparation code:

let noOp_ts

Tests:

perf.now
noOp_ts = performance.now()
control
noOp_ts = Date.now()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
perf.now
control

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 months ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Linux

View result in a separate tab

Test name	Executions per second
perf.now	5735630.0 Ops/sec
control	11577904.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark definition is a JSON object that defines the basic structure of the test. It contains three main parts:

*   `Name`: A human-readable name for the benchmark, which in this case is "js timestamp cost".
*   `Description`: An optional description of the benchmark, but it's empty in this example.
*   `Script Preparation Code` and `Html Preparation Code`: These are used to set up the environment for the test. In this case, the script preparation code sets a variable `noOp_ts` to the current timestamp using either `performance.now()` or `Date.now()`, depending on the test.

**Individual Test Cases**

There are two test cases:

*   "perf.now" (using `performance.now()`): This test measures the cost of calling `performance.now()`.
*   "control" (using `Date.now()`): This test is a control benchmark, measuring the cost of calling `Date.now()`.

**Library and Purpose**

In this benchmark, two libraries are used:

*   `performance`: This library provides the `performance.now()` function, which returns the number of milliseconds since the Unix epoch. It's used to measure high-resolution time.
*   `Date`: This library provides the `Date.now()` function, which also returns the number of milliseconds since the Unix epoch.

Both libraries are used to measure the cost of calling their respective functions.

**Special JavaScript Feature or Syntax**

The test uses two special JavaScript features:

*   `performance.now()`: This is a high-resolution timer function that's designed for measuring time intervals.
*   `Date.now()`: This is a lower-resolution timer function that's designed for measuring time intervals in the past (i.e., since the Unix epoch).

These functions are used to measure the cost of calling them.

**Pros and Cons**

Here are some pros and cons of each approach:

*   Using `performance.now()`:
    *   Pros: High-resolution timer, suitable for precise measurements.
    *   Cons: Not supported in older browsers, may be slower than `Date.now()` due to additional overhead.
*   Using `Date.now()`:
    *   Pros: Widespread support across browsers and platforms, faster execution compared to `performance.now()`.
    *   Cons: Lower resolution, not suitable for precise measurements.

**Other Considerations**

When choosing between these two approaches, consider the specific requirements of your benchmark:

*   If you need high precision, use `performance.now()`.
*   If you need wide browser support and acceptable performance, use `Date.now()`.

**Alternative Approaches**

If you don't have access to either `performance` or `Date`, there are alternative approaches:

*   Using a dedicated timer library like `requestAnimationFrame()` or `setInterval()`.
*   Using a platform-specific function like `setTimeout()` (on Windows) or `setImmediate()` (on Node.js).
*   Implementing your own timer using high-resolution hardware counters.

Keep in mind that each of these alternatives has its pros and cons, and may not provide the same level of accuracy as `performance.now()` or `Date.now()`.

Related benchmarks:

js timestamp cost (version: 0)

Comparing performance of: perf.now vs control

Created: one year ago by: Guest

Jump to the latest result

perf.now

control

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):