- GraalVM for JDK 21 (Latest)
- GraalVM for JDK 22 (Early Access)
- GraalVM for JDK 20
- GraalVM for JDK 17
- GraalVM 22.3
- GraalVM 22.2
- GraalVM 22.1
- GraalVM 22.0
- GraalVM 21.3
- Dev Build
- Java on Truffle
- LLVM Languages Reference
- Python Reference
- Ruby Reference
- Debugging Ruby
- Runtime Configurations
- Using Ruby with GraalVM
- Installing `libssl`
- Installing LibYAML
- Installing Make and GCC
- Installing `zlib`
- Migration from JRuby to Ruby
- TruffleRuby Options and Command Line
- Polyglot Programming
- Ruby Managers and Installers
- Standalone Distribution
- Development Tools for Ruby
- Ruby Additional Functionality
- Setting up a UTF-8 Locale
- Reporting Performance Problems
- Optcarrot Example
- R Reference
- WebAssembly Reference
This document lists the most important points to consider when benchmarking TruffleRuby.
Guidelines for Benchmarking TruffleRuby #
We expect anyone publishing benchmark numbers about TruffleRuby to follow these guidelines.
Use TruffleRuby EE #
Use TruffleRuby EE, it is faster than CE overall and represents what TruffleRuby is capable of.
Use the Latest Release #
Always use the latest release at the time of benchmarking (so it does not misrepresent TruffleRuby by using an old release which may have known performance issues).
Use the Correct Runtime Configuration #
TruffleRuby has two Runtime Configurations, Native and JVM, see this comparison.
If you want to benchmark peak performance, you should use the JVM configuration.
To do so, set the environment variable
TRUFFLERUBYOPT=--jvm so it affects all TruffleRuby processes.
You can also pass
--jvm as an argument to TruffleRuby if you are sure there are no subprocesses.
The Native configuration provides better startup and warmup but has slower peak performance.
Of course you can also benchmark both configurations and see which one is better for what you are benchmarking.
Run with Enough Warmup #
TruffleRuby like other runtimes with a just-in-time compiler needs some time (called warmup) to reach peak performance, because it takes time to just-in-time compile the relevant methods of the benchmark. The easiest way to check if there was enough warmup is to run the benchmark workload repeatedly inside a process and print the times of each run. The times should be very stable once it’s warmed up and conversely keep changing while it is not warmed up yet. See this documentation for more details about warmup.
Consider Disabling the Global C-Extension Lock #
On TruffleRuby, C extensions by default use a global lock for maximum compatibility with CRuby.
If you are benchmarking a multi-threaded Ruby program (e.g. Rails on a multi-threaded server), it is worth trying
This issue tracks a way to automatically not use the lock for extensions which do not need it.
These are more general recommendations about benchmarking.
Avoid Benchmarking on a Laptop #
Performance on laptops is very sensitive to heat, and so overall quite unstable. As an example, if the CPU gets too warm the operating system will throttle it, making the benchmark results unfair and unstable. So benchmarking should be done on on a desktop computer or server.
Avoid Other Running Processes #
As those would cause extra noise in benchmarking results. Definitely no browser, slack, IDE, etc as those use a lot of CPU.
Disable Frequency Scaling #
CPU frequency scaling and boost generally just increases noise in benchmarking results, so it is recommended to disable them when benchmarking for more stable results.
For Intel CPUs use:
sudo sh -c 'echo 1 > /sys/devices/system/cpu/intel_pstate/no_turbo'
For AMD CPUs use:
sudo sh -c 'echo 0 > /sys/devices/system/cpu/cpufreq/boost'
Also make sure the performance governor is used on Linux:
sudo cpupower frequency-set -g performance
Do not pin TruffleRuby to a Single Core #
TruffleRuby uses multiple threads for the JIT Compiler, the GC, etc. Restricting it to a single core for benchmarking does not make sense, it would cause a lot of contention.
Avoid Benchmarking on macOS #
macOS’s memory management is subpar and can cause unnecessary memory swapping even when there is enough memory (e.g. it sometimes keeps terminated processes in memory needlessly).
macOS’s TCP stack is also subpar, see the Passenger docs on this subject.
If you have no choice but to benchmark on macOS then mention that with the results
and ensure there is plenty free memory and no swap while benchmarking.
Pages free) or
unused) to check the amount of free memory.
Unfortunately neither of these tools show the swap usage, illustrating how difficult it is to ensure there is no swapping going on when benchmarking on macOS.
Activity Monitor before and after benchmarking to ensure there is no swap (
Swap Used) as a workaround.
Activity Monitor is too heavy to be used during benchmarking.