The Importance of Benchmarking in Art Programming: A Guide to Measuring Performance
Every art programmer has uttered the phrase "my cordis law" at some point, followed by tears and crosses, not necessarily in that order. But what does it mean? How do you determine if your code is fast enough? The answer lies in benchmarking, a crucial concept in art programming.
Benchmarking is the process of comparing different solutions to measure their performance. It's essential to identify which solution is worth changing because of its speed. You need to compare your existing solution with one or more alternatives to make an informed decision. The concepts of benchmarking are straightforward: you simply tame how long each solution takes, and all things being equal, select the fastest.
Constructing a Benchmark Function
To begin benchmarking, you need to construct a function that enables you to vary the complexity of the task. A parameter that alters the data size is an excellent example. Suppose you want to generate a sequence of integers. There are three obvious ways to do this:
1. Using a cool one: This approach involves using a simple loop to generate the sequence.
2. The sequence function with the default increment step size: This function uses the built-in `sequence` function with its default parameters.
3. The `sequence` function where we explicitly specify the step size: This approach allows you to vary the step size and see how it affects performance.
To determine how long each solution takes, you need to wrap your code in a timing function. In this example, we use the `system.dot.time()` function to measure the elapsed time. This function returns three values: user time, system time, and elapsed time. The elapsed time is approximately the sum of the user and system times.
Using the Arrow Operator for Timing
In some cases, you want to both time and store the operation. To achieve this, you can use the arrow operator (`=>`) within a function call. This operator performs two tasks: argument passing and object assignment. When used inside `system.dot.time()`, it allows you to both time and store the operation.
However, using the equals operator (`=`) will raise an error because it only performs argument passing or assignment. Therefore, when calculating elapsed time, it's essential to consider relative time, which is simply a ratio of the elapsed times.
The Maker Benchmark Package
The `maker-benchmark` package is a wrapper around `system.dot.time()` that makes benchmarking straightforward. The key function in this package is `micro-benchmark`, which allows you to compare multiple functions. You can specify how many times to call each function using the `x` argument, and as an added bonus, the `CLD` column provides a statistical ranking of functions.
In our example code, we are comparing three functions: `cool one`, `sequence` with default parameters, and `sequence` with explicitly specified step size. The results show that the `cool one` function takes approximately 0.6 seconds to run, while the `sequence` function takes around 1.6 seconds.
Conclusion
Benchmarking is an essential tool for art programmers to measure performance and make informed decisions about code optimization. By constructing a benchmark function, using timing functions like `system.dot.time()` or `micro-benchmark`, and considering relative time, you can determine which solution is worth changing because of its speed. Remember to use the arrow operator to both time and store operations, and don't forget to consider statistical rankings when comparing multiple functions.
"WEBVTTKind: captionsLanguage: enevery art programmer at one point or another has uttered the phrase my cordis law and this is usually followed with tears and crosses and not necessarily in that order but what do you mean by saw is one-second slaw a minute an hour this is obviously problem dependent what you need is caught that is fast enough to determine if it is worth changing your code you need to compare your existing solution with one or more alternatives this is what we mean by benchmarking and the concepts straightforward you simply tame how long each solution takes and all things being equal select the fastest benchmarking is a two-step process first construct function typically the function is an argument enables you to vary the complexity of the task for example a parameter that alters the data size second you tame this function under different scenarios let's have an example suppose you want to generate a sequence of integers there are three obvious ways to do this the first use a cool one the second the sequence function with the default increment step size and the thought the sequence function where we explicitly specify the step size we began by wrapping the options and functions and allow the sequence length n to be passed as an argument next to determine how long the function takes to run we wrap the function again but this time with system dot time running this chord produces three numbers user system elapsed roughly the user tame is a CPU time charged for the execution of the user instructions the system time is a CPU time charged for the execution by the system on behalf of the calling process and the elapsed time the important one is approximately the sum of the user and system this is a number with typically caribou so in this example it took not point not six seconds for the coolant function but one point six seconds for the sequence function I often use system time during an analysis I set my code running as they leave the office and want to know how long the job took when aritaum the next morning however I also want to use a result in this case we use the arrow operator using the arrow within a function call performs two tasks argument passing and object assignment this allows us to both time and store the operation the equals operator only performs argument passing or assignment so using equals inside system time will raise an error as well as considering elapsed time is worth calculating the relative time this is simply a ratio so in this example the elapsed times R naught point naught sex and 1.6 seconds the relative time is therefore 26 that is the sick by function is 26 times sore than the current function the maker benchmark package is a wrapper around system door time and makes it straightforward when comparing multiple functions the key function in this package is the unimaginative li named micro benchmark and this code we are comparing functions call on sick default and seek by the x argument specifies how many times we should call each function and as a bonus the CLD column provides a statistical ranking of functions as you would expect the colon operator is a fastest function for generating a sequence of integers and takes an average 220 milliseconds and the next exercise you'll get a chance to tame various functions and calculate the relative timesevery art programmer at one point or another has uttered the phrase my cordis law and this is usually followed with tears and crosses and not necessarily in that order but what do you mean by saw is one-second slaw a minute an hour this is obviously problem dependent what you need is caught that is fast enough to determine if it is worth changing your code you need to compare your existing solution with one or more alternatives this is what we mean by benchmarking and the concepts straightforward you simply tame how long each solution takes and all things being equal select the fastest benchmarking is a two-step process first construct function typically the function is an argument enables you to vary the complexity of the task for example a parameter that alters the data size second you tame this function under different scenarios let's have an example suppose you want to generate a sequence of integers there are three obvious ways to do this the first use a cool one the second the sequence function with the default increment step size and the thought the sequence function where we explicitly specify the step size we began by wrapping the options and functions and allow the sequence length n to be passed as an argument next to determine how long the function takes to run we wrap the function again but this time with system dot time running this chord produces three numbers user system elapsed roughly the user tame is a CPU time charged for the execution of the user instructions the system time is a CPU time charged for the execution by the system on behalf of the calling process and the elapsed time the important one is approximately the sum of the user and system this is a number with typically caribou so in this example it took not point not six seconds for the coolant function but one point six seconds for the sequence function I often use system time during an analysis I set my code running as they leave the office and want to know how long the job took when aritaum the next morning however I also want to use a result in this case we use the arrow operator using the arrow within a function call performs two tasks argument passing and object assignment this allows us to both time and store the operation the equals operator only performs argument passing or assignment so using equals inside system time will raise an error as well as considering elapsed time is worth calculating the relative time this is simply a ratio so in this example the elapsed times R naught point naught sex and 1.6 seconds the relative time is therefore 26 that is the sick by function is 26 times sore than the current function the maker benchmark package is a wrapper around system door time and makes it straightforward when comparing multiple functions the key function in this package is the unimaginative li named micro benchmark and this code we are comparing functions call on sick default and seek by the x argument specifies how many times we should call each function and as a bonus the CLD column provides a statistical ranking of functions as you would expect the colon operator is a fastest function for generating a sequence of integers and takes an average 220 milliseconds and the next exercise you'll get a chance to tame various functions and calculate the relative times\n"
