Benchmark: Performance of delete on large arrays

Script Preparation code:

var N0 = 50855;

Tests:

50855
const N = N0; const o = {}; for ( let i = 0; i < N; i++ ) { o[i] = i; } for ( let i = 0; i < N; i++ ) { o[i] = undefined; }
50856
const N = N0 + 1; const o = {}; for ( let i = 0; i < N; i++ ) { o[i] = i; } for ( let i = 0; i < N; i++ ) { o[i] = undefined; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
50855
50856

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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Let's dive into the explanation of what is tested in this benchmark.

**Benchmark Purpose**

The primary goal of this benchmark is to compare the performance of deleting elements from an array using two different approaches: one that uses a fixed size array and another that increments the array size by 1 each time. This test aims to measure how efficient JavaScript engines are at handling memory allocation, deallocation, and iteration.

**Benchmark Definitions**

The benchmark has two test cases:

1. `const N = N0;`: This approach creates an array of a fixed size (`N`) using the `N0` variable. The loop then populates the array with values from 0 to `N-1`, and finally, it deletes all elements in the array.
2. `const N = N0 + 1;`: This approach creates an array of a dynamically allocated size (`N+1`) using the `N0` variable. The loop then populates the array with values from 0 to `N`, and finally, it deletes all elements in the array.

**Comparison**

The benchmark is comparing two approaches:

* Fixed-size array (first test case): This approach tests how efficient the engine is at allocating and deallocating memory for a fixed-size array.
* Dynamically allocated array (second test case): This approach tests how efficient the engine is at dynamically allocating memory based on user input.

**Pros and Cons**

**Fixed-Size Array:**

Pros:

* Predictable performance since the size of the array is known in advance.
* Easier to optimize for performance, as the engine can plan ahead.

Cons:

* May result in memory fragmentation issues if elements are deleted randomly.
* Can lead to slower performance if the array size is very large.

**Dynamically Allocated Array:**

Pros:

* More efficient use of memory since only the necessary amount is allocated.
* Better handling of variable-sized arrays.

Cons:

* Can result in slower performance due to dynamic memory allocation and deallocation.
* May introduce overhead from garbage collection.

**Other Considerations**

The benchmark also considers other factors that might affect performance, such as:

* Memory locality: How well does the engine optimize for data access patterns?
* Cache coherence: How effectively does the engine handle cache coherency in the presence of concurrent access?

**Libraries and Special JS Features**

There are no libraries explicitly mentioned in the benchmark definition. However, it's possible that the test uses built-in JavaScript features like `for` loops, array indexing (`o[i]`), and conditional statements (`if`).

**Test Cases and Run Times**

The latest benchmark result shows that Chrome 65 (on a Mac OS X 10.13.3 system) achieved better performance for the fixed-size array test case (`ExecutionsPerSecond = 95.29279327392578`) compared to the dynamically allocated array test case (`ExecutionsPerSecond = 92.1169204711914`).

**Alternatives**

If you're interested in running similar benchmarks or exploring alternative approaches, here are some alternatives:

* You can create your own benchmark using a framework like Benchmark.js.
* Explore other performance testing tools, such as PerfHog or PerformanceTest.
* Consider experimenting with different JavaScript engines (e.g., SpiderMonkey for Firefox) or platforms to see how they compare.

Related benchmarks:

Performance of delete on large arrays (version: 0)

Comparing performance of: 50855 vs 50856

Created: 8 years ago by: Guest

Jump to the latest result

50855

50856

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):