Profiling Command Line Tool

GraalVM provides Profiling command line tool that let you optimize your code through analysis of CPU and memory usage.

Most applications spend 80 percent of their runtime in 20 percent of the code. For this reason, to optimize the code, it is essential to know where the application spends its time. GraalVM provides simple command line tools for runtime and memory profiling to help you analyze and optimize your code.

Using the example application below the profiling capabilities are demonstrated. This example uses a basic prime number calculator based on the ancient Sieve of Eratosthenes algorithm.

  1. Copy the following code into a new file named primes.js:

     class AcceptFilter {
     accept(n) {
         return true
     }
 }

 class DivisibleByFilter {
     constructor(number, next) {
         this.number = number;
         this.next = next;
     }

     accept(n) {
         var filter = this;
         while (filter != null) {
             if (n % filter.number === 0) {
                 return false;
             }
             filter = filter.next;
         }
         return true;
     }
 }

 class Primes {
     constructor() {
         this.number = 2;
         this.filter = new AcceptFilter();
     }

     next() {
         while (!this.filter.accept(this.number)) {
             this.number++;
         }
         this.filter = new DivisibleByFilter(this.number, this.filter);
         return this.number;
     }
 }

 var primes = new Primes();
 var primesArray = [];
 for (let i = 0; i < 5000; i++) {
     primesArray.push(primes.next());
 }
 console.log(`Computed ${primesArray.length} prime numbers. ` +
             `The last 5 are ${primesArray.slice(-5)}.`);

  2. Run js primes.js.

    The example application should print output as follows:

     $> js primes.js
 Computed 5000 prime numbers. The last 5 are 48563,48571,48589,48593,48611.

    This code takes a moment to compute so let’s see where all the time is spent.

  3. Run js primes.js --cpusampler to enable CPU sampling.

    The CPU sampler tool should print output for the example application as follows:

     $ ./js primes.js --cpusampler
 Computed 5000 prime numbers. The last 5 are 48563,48571,48589,48593,48611.
 ---------------------------------------------------------------------------------------------------
 Sampling Histogram. Recorded 1184 samples with period 1ms
   Self Time: Time spent on the top of the stack.
   Total Time: Time the location spent on the stack.
   Opt %: Percent of time spent in compiled and therfore non-interpreted code.
 ---------------------------------------------------------------------------------------------------
  Name        |      Total Time     |  Opt % ||       Self Time     |  Opt % | Location
 ---------------------------------------------------------------------------------------------------
  next        |       1216ms  98.5% |  87.9% ||       1063ms  85.9% |  99.0% | primes.js~31-37:564-770
  accept      |        159ms  11.2% |  22.7% ||        155ms  12.5% |  14.8% | primes.js~13-22:202-439
  :program    |       1233ms 100.0% |   0.0% ||         18ms   1.5% |   0.0% | primes.js~1-47:0-1024
  constructor |          1ms   0.1% |   0.0% ||          1ms   0.1% |   0.0% | primes.js~7-23:72-442
 ---------------------------------------------------------------------------------------------------

    The sampler prints an execution time histogram for each JavaScript function. By default, CPU sampling takes a sample every single millisecond. From the result you can see that roughly 96 percent of the time is spent in the DivisibleByFilter.accept function.

     accept(n) {
     var filter = this;
     while (filter != null) {
         if (n % filter.number === 0) {
             return false;
         }
         filter = filter.next;
     }
     return true;
 }

    Now find out more about this function by filtering the samples and include statements in the profile in addition to methods.

  4. Run js primes.js --cpusampler --cpusampler.Mode=statements --cpusampler.FilterRootName=*accept to collect statement samples for all functions that end with accept.

     $ js primes.js --cpusampler --cpusampler.Mode=statements --cpusampler.FilterRootName=*accept
 Computed 5000 prime numbers. The last 5 are 48563,48571,48589,48593,48611.
 ----------------------------------------------------------------------------------------------------
 Sampling Histogram. Recorded 1567 samples with period 1ms
   Self Time: Time spent on the top of the stack.
   Total Time: Time the location spent on the stack.
   Opt %: Percent of time spent in compiled and therfore non-interpreted code.
 ----------------------------------------------------------------------------------------------------
  Name         |      Total Time     |  Opt % ||       Self Time     |  Opt % | Location
 ----------------------------------------------------------------------------------------------------
  accept~16-18 |        436ms  27.8% |  94.3% ||        435ms  27.8% |  94.5% | primes.js~16-18:275-348
  accept~15    |        432ms  27.6% |  97.0% ||        432ms  27.6% |  97.0% | primes.js~15:245-258
  accept~19    |        355ms  22.7% |  95.5% ||        355ms  22.7% |  95.5% | primes.js~19:362-381
  accept~17    |          1ms   0.1% |   0.0% ||          1ms   0.1% |   0.0% | primes.js~17:322-334
 ----------------------------------------------------------------------------------------------------

    Roughly 30 percent of the time is spent in this if condition:

     if (n % filter.number === 0) {
     return false;
 }

    The if condition contains an expensive modulo operation, which might explain the runtime of the statement.

    Now use the CPU tracer tool to collect execution counts of each statement.

  5. Run js primes.js --cputracer --cputracer.TraceStatements --cputracer.FilterRootName=*accept to collect execution counts for all statements in methods ending with accept.

     $ js primes.js --cputracer --cputracer.TraceStatements --cputracer.FilterRootName=*accept
 Computed 5000 prime numbers. The last 5 are 48563,48571,48589,48593,48611.
 -----------------------------------------------------------------------------------------
 Tracing Histogram. Counted a total of 351278226 element executions.
   Total Count: Number of times the element was executed and percentage of total executions.
   Interpreted Count: Number of times the element was interpreted and percentage of total executions of this element.
   Compiled Count: Number of times the compiled element was executed and percentage of total executions of this element.
 -----------------------------------------------------------------------------------------
  Name     |          Total Count |    Interpreted Count |       Compiled Count | Location
 -----------------------------------------------------------------------------------------
  accept   |     117058669  33.3% |         63575   0.1% |     116995094  99.9% | primes.js~15:245-258
  accept   |     117053670  33.3% |         63422   0.1% |     116990248  99.9% | primes.js~16-18:275-348
  accept   |     117005061  33.3% |         61718   0.1% |     116943343  99.9% | primes.js~19:362-381
  accept   |         53608   0.0% |          1857   3.5% |         51751  96.5% | primes.js~14:215-227
  accept   |         53608   0.0% |          1857   3.5% |         51751  96.5% | primes.js~13-22:191-419
  accept   |         48609   0.0% |          1704   3.5% |         46905  96.5% | primes.js~17:322-334
  accept   |          4999   0.0% |           153   3.1% |          4846  96.9% | primes.js~21:409-412
  accept   |             1   0.0% |             1 100.0% |             0   0.0% | primes.js~2-4:25-61
  accept   |             1   0.0% |             1 100.0% |             0   0.0% | primes.js~3:52-55
 -----------------------------------------------------------------------------------------

    Now the output shows execution counters for each statement, instead of timing information. Tracing histograms often provides insights into the behaviour of the algorithm that needs optimization.

    Lastly, using the memory tracer tool for capturing allocations is currently an experimental feature in GraalVM. Node, --memtracer as an experimental tool must be preceded by the --experimental-options command line option.

  6. Run js primes.js --experimental-options --memtracer to display source code locations and counts of reported allocations.

     $ js primes.js --experimental-options --memtracer
 Computed 5000 prime numbers. The last 5 are 48563,48571,48589,48593,48611.
 ------------------------------------------------------------
  Location Histogram with Allocation Counts. Recorded a total of 5013 allocations.
    Total Count: Number of allocations during the execution of this element.
    Self Count: Number of allocations in this element alone (excluding sub calls).
 ------------------------------------------------------------
  Name        |      Self Count |     Total Count |  Location
 ------------------------------------------------------------
  next        |     5000  99.7% |     5000  99.7% | primes.js~31-37:537-737
  :program    |       11   0.2% |     5013 100.0% | primes.js~1-46:0-966
  Primes      |        1   0.0% |        1   0.0% | primes.js~25-38:454-739
 ------------------------------------------------------------

    This output shows the number of allocations which were recorded per function. For each prime number that was computed, the program allocates one object in next and one in constructor of DivisibleByFilter. Allocations are recorded independently of whether they could get eliminated by the compiler. The Graal compiler is particularly powerful in optimizing allocations and can push allocations into infrequent branches to increase execution performance. The GraalVM team plans to add information about memory optimizations to the memory tracer in the future.

Tool Reference

Use the --help:tools option in all guest language launchers to display reference information for the CPU sampler, the CPU tracer, and the memory tracer.

The current set of available options is as follows:

CPU Sampler Command Options

CPU Tracer Command Options

Memory Tracer Command Options

Note: The memory tracer tool is currently an experimental tool. Make sure to prepend --experimental-options flag to enable --memtracer.