Benchmark: memo vs no memo - MeasureThat.net

Tests:

No memo
const memoizationTwoArgs = ( func ) => { const cache = {}; function memoFunc(a, b) { if (!cache.hasOwnProperty(a)) { cache[a] = {}; } if (!cache[a].hasOwnProperty(b)) { cache[a][b] = func(a, b); } return cache[a][b]; } return memoFunc; }; const randStringGen = (len) => Math.random().toString(16).substr(2, 2+len); const randIntGen = (min, max) => parseInt((Math.random() * (max - min + 1)), 10) + min; const partIds = []; for (let i=0;i<2;i++) { partIds.push(randStringGen(20)); } const meetingIds = []; for (let i=0;i<2;i++) { meetingIds.push(randStringGen(20)); } const func = (a,b) => `${a}/${b}`; for (let i=0;i<1000;i++) { const a = partIds[randIntGen(0, partIds.length-1)]; const b = meetingIds[randIntGen(0, meetingIds.length-1)]; console.log(func(a,b)); }
Memo
const memoizationTwoArgs = ( func ) => { const cache = {}; function memoFunc(a, b) { if (!cache.hasOwnProperty(a)) { cache[a] = {}; } if (!cache[a].hasOwnProperty(b)) { cache[a][b] = func(a, b); } return cache[a][b]; } return memoFunc; }; const randStringGen = (len) => Math.random().toString(16).substr(2, 2+len); const randIntGen = (min, max) => parseInt((Math.random() * (max - min + 1)), 10) + min; const partIds = []; for (let i=0;i<2;i++) { partIds.push(randStringGen(20)); } const meetingIds = []; for (let i=0;i<2;i++) { meetingIds.push(randStringGen(20)); } const memoFunc = memoizationTwoArgs((a,b) => `${a}/${b}`); for (let i=0;i<1000;i++) { const a = partIds[randIntGen(0, partIds.length-1)]; const b = meetingIds[randIntGen(0, meetingIds.length-1)]; console.log(memoFunc(a,b)); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
No memo
Memo

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**What is tested?**

The provided benchmark tests two approaches to concatenating strings in JavaScript: with and without memoization (caching).

**Options compared:**

There are two options being compared:

1. **No memo**: This approach creates a new function every time it's called, which means the string concatenation operation will be repeated every time.
2. **Memo**: This approach uses caching to store the results of previous concatenations, so that subsequent calls with the same arguments can return the cached result instead of recalculating it.

**Pros and Cons:**

* **No memo**: The pros are that there is no additional memory allocation or overhead due to caching. However, the cons are that the function will be executed repeatedly for each combination of input strings, which can lead to a significant performance degradation.
* **Memo**: The pros are that subsequent calls with the same arguments will return quickly, without recalculating the result. The cons are that there is an initial overhead due to creating and populating the cache, and there's also a small chance that the cache might not be populated correctly if multiple threads or processes are accessing it concurrently.

**Library:**

There is no explicit library being used in this benchmark. However, some libraries like Lodash or Ramda might provide similar functionality for memoization.

**Special JavaScript feature or syntax:**

The `const` keyword and arrow functions (`=>`) are being used to define small, anonymous functions. This is a common pattern in modern JavaScript development, as it allows for concise and readable code.

**Benchmark preparation code:**

The preparation code creates two arrays of random strings, `partIds` and `meetingIds`, which will be used as input strings for the concatenation operation. The `randStringGen` and `randIntGen` functions generate these random strings.

**Other alternatives:**

If you want to explore alternative approaches, here are a few options:

1. **Using a library like Lodash or Ramda**: These libraries provide built-in support for memoization and other functional programming techniques that can simplify your code.
2. **Implementing memoization using `Map` objects**: You can use JavaScript's built-in `Map` object to create a cache, which would allow you to store and retrieve values quickly.
3. **Using a just-in-time (JIT) compiler**: Some modern JavaScript engines, like SpiderMonkey or V8, have JIT compilers that can optimize your code at runtime.

Overall, the memoization approach provides a significant performance boost for this specific benchmark, but it's essential to consider the trade-offs and use cases where caching might not be suitable.

Related benchmarks:

memo vs no memo (version: 0)

Checking if concatenating two strings is costly enough to need memoization

Comparing performance of: No memo vs Memo

Created: 3 years ago by: Guest

Jump to the latest result

No memo

Memo

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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