var x = 0x12345678;
var y;
for (var i = 0; i < 10000; ++i) {
y = Math.imul(x, i);
}
for (var i = 0; i < 10000; ++i) {
y = (x & 0xffff) * i + (((x >>> 16) * (i & 0xffff)) << 16);
}
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
Math.imul | |
Polyfill |
Test name | Executions per second |
---|---|
Math.imul | 155.9 Ops/sec |
Polyfill | 204.5 Ops/sec |
Let's break down the provided benchmark and explain what's being tested.
Benchmark Definition
The benchmark definition represents two test cases: Math.imul
and Polyfill
. Both tests aim to measure the performance of multiplying two 32-bit integers using different approaches.
Options compared
Math.imul
: This is a built-in JavaScript function that multiplies two integers using a hardware-specific multiplication instruction, if available.Polyfill
: This approach uses a custom implementation of multiplication, relying on bitwise operations to achieve the same result as Math.imul
. The polyfill is designed to work in older browsers or environments where Math.imul
is not supported.Pros and Cons
Math.imul
:Polyfill
:Math.imul
due to the overhead of manual bitwise operations.Library/ Library-less approach
The Polyfill
test case relies on no external libraries, as it provides its own implementation of multiplication using bitwise operators.
Special JS feature/syntax
None mentioned in this benchmark. The tests only focus on the performance difference between two multiplication approaches.
Other alternatives
If you were to create a similar benchmark for multiplying two 64-bit integers or other types of numbers, you might consider adding additional test cases, such as:
BigInt
(if supported by the browser)Keep in mind that these alternatives would require significant changes to the benchmark definition and test cases.
In summary, this benchmark tests the performance difference between using Math.imul
(a built-in JavaScript function) and a custom polyfill implementation of multiplication for 32-bit integers. The results can help developers understand how different approaches affect performance in their applications.