<!--your preparation HTML code goes here-->
const str_en = "Comparing the performance of UTF-8 vs UTF-16 string encoding copying into and out of WASM. 🙂";
const str_ar = "استعار جحا مرة آنية من جاره وعندما أعادها له أعاد معها آنية صغيرة";
const str_en_large = str_en.repeat(10);
const str_ar_large = str_ar.repeat(10);
const encoder = new TextEncoder('utf-8');
const decoder = new TextDecoder('utf-8', { ignoreBOM: true, fatal: true });
const buf = encoder.encode(str_en);
const str = decoder.decode(buf);
const buf = encoder.encode(str_ar);
const str = decoder.decode(buf);
const buf = encoder.encode(str_en_large);
const str = decoder.decode(buf);
const buf = encoder.encode(str_ar_large);
const str = decoder.decode(buf);
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
str_en | |
str_ar | |
str_en_large | |
str_ar_large |
Test name | Executions per second |
---|---|
str_en | 6557358.5 Ops/sec |
str_ar | 2509458.5 Ops/sec |
str_en_large | 1376575.0 Ops/sec |
str_ar_large | 516037.7 Ops/sec |
The benchmark defined in the provided JSON is focused on the performance comparison of UTF-8 and UTF-16 string encoding in the context of WebAssembly (WASM) when executing in a JavaScript environment. The essential aspect being measured is the efficiency of encoding and decoding strings in different languages (English and Arabic) using these two encoding formats.
String Encoding:
Test Cases:
For each of these test cases, the benchmark measures the number of executions per second, which indicates how quickly the encoding and decoding processes occur for the respective strings.
The collected results from the latest benchmark show the following executions per second for each test case when run on Firefox:
UTF-8 Pros:
UTF-8 Cons:
UTF-16 Pros:
UTF-16 Cons:
The WebAssembly (WASM) environment allows for highly optimized execution of code. In this benchmark, the use of the UTF-8 and UTF-16 encoding coupled with WASM highlights performance characteristics that are important for applications that require frequent string manipulations, such as text editors, language processing tools, or applications relying on multiple languages.
Direct Binary Representation: For certain applications, especially those that involve numeric data or well-defined structures, using direct binary representations rather than encoded strings can improve performance.
Other Encoding Libraries: There are several libraries available for string encoding/decoding (e.g., iconv-lite
for Node.js) which may have different performance attributes. These libraries can provide additional functionalities like handling various encodings more efficiently.
Choosing Encoding Based on Context: Developers might choose to standardize on one encoding (like UTF-8) unless there are specific requirements that necessitate UTF-16, as this helps avoid potential encoding errors and optimizes performance for most web scenarios.
WebAssembly Optimized Libraries: Some libraries are specifically designed to leverage WASM's performance characteristics, which may provide better encoding/decoding performance compared to standard JavaScript implementations.
In conclusion, the benchmark highlights the different performance traits of UTF-8 and UTF-16 encoding when processed through a WASM interface, allowing developers to make informed decisions based on performance considerations tailored to their specific application requirements.