Benchmark: Calculate vs Cache in Map

Script Preparation code:

var nums = [];
for(let i = 0; i < 100; i++) {
 	nums.push(Math.floor(Math.random() * 9));
}

function flip(num) {
	const row = Math.floor(num / 3);
 	const col = num % 3;
 	return row * 3 + (2 - col); 
}

Tests:

Calculate
const a = []; for(const num of nums) { a.push(flip(num)); }
Cache in Map
const b = []; const flipMap = new Map(); for(let i = 0; i < 9; i++) { flipMap.set(i, flip(i)); } for(const num of nums) { b.push(flipMap.get(num)); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Calculate
Cache in Map

Fastest: N/A

Slowest: N/A

Latest run results:

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

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

**Benchmark Overview**

The benchmark measures the performance difference between two approaches:

1. **Calculate**: Iterating over the `nums` array to calculate the result for each number, using the `flip` function directly.
2. **Cache in Map**: Storing the results of the `flip` function in a Map (`flipMap`) and then looking up the result for each number in the `nums` array.

**Library**

The `flip` function uses a library called `Math` module, which is built into JavaScript. The purpose of this library is to provide mathematical functions such as `Math.floor()`, `Math.random()`, etc.

**Test Cases**

There are two test cases:

1. **Calculate**: This test case measures the performance of iterating over the `nums` array and calculating the result for each number using the `flip` function directly.
2. **Cache in Map**: This test case measures the performance of storing the results of the `flip` function in a Map (`flipMap`) and then looking up the result for each number in the `nums` array.

**Options Compared**

The two options compared are:

1. Iterating over the array and calculating the result directly (Calculate)
2. Using a Map to cache the results (Cache in Map)

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

**Calculate**

* Pros:
	+ Simple and easy to understand
	+ No additional data structure overhead
* Cons:
	+ Requires iterating over the entire array, which can be slow for large datasets

**Cache in Map**

* Pros:
	+ Can reduce the number of iterations required (since we're looking up values in the Map)
	+ Can be faster for large datasets
* Cons:
	+ Requires additional memory to store the Map and its entries
	+ May require more complex code to manage the cache

**Other Considerations**

* **Cache invalidation**: The `flipMap` data structure requires a way to invalidate or update it when the underlying data changes. This might add complexity to the implementation.
* **Cache size**: If the `nums` array is too large, storing all values in the Map might not be efficient.

**Special JS Features/Syntax**

None mentioned in this benchmark, but there are many other features and syntax in JavaScript that can impact performance, such as:

* Array methods (e.g., `map()`, `filter()`)
* Object methods (e.g., `forEach()`, `reduce()`)
* Async/await
* Promises

**Alternatives**

Other alternatives to consider for this benchmark could be:

* Using a different data structure, such as an array or a vector, instead of a Map.
* Implementing a custom caching mechanism using a separate data structure.
* Using a Just-In-Time (JIT) compiler or a native compiler to optimize the performance of the code.

Keep in mind that these alternatives would require significant changes to the benchmark implementation and might not be feasible for a simple microbenchmark like this one.

Related benchmarks:

Calculate vs Cache in Map (version: 0)

Comparing performance of: Calculate vs Cache in Map

Created: 3 years ago by: Guest

Jump to the latest result

Calculate

Cache in Map

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):