How to build Graal-enabled JDK8 on CircleCI?

Citation: feature image on the blog can be found on flickr and created by Luca Galli. The image in one of the below sections can be also found on flickr and created by fklv (Obsolete hipster).

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The GraalVM compiler is a replacement to HotSpot’s server-side JIT compiler widely known as the C2 compiler. It is written in Java with the goal of better performance (among other goals) as compared to the C2 compiler. New changes starting with Java 9 mean that we can now plug in our own hand-written C2 compiler into the JVM, thanks to JVMCI. The researchers and engineers at Oracle Labs) have created a variant of JDK8 with JVMCI enabled which can be used to build the GraalVM compiler. The GraalVM compiler is open source and is available on GitHub (along with the HotSpot JVMCI sources) needed to build the GraalVM compiler). This gives us the ability to fork/clone it and build our own version of the GraalVM compiler.

In this post, we are going to build the GraalVM compiler with JDK8 on CircleCI. The resulting artifacts are going to be:

– JDK8 embedded with the GraalVM compiler, and
– a zip archive containing Graal & Truffle modules/components.

Note: we are not covering how to build the whole of the GraalVM suite in this post, that can be done via another post. Although these scripts can be used to that, and there exists a branch which contains the rest of the steps.

Why use a CI tool to build the GraalVM compiler?

Continuous integration (CI) and continuous deployment (CD) tools have many benefits. One of the greatest is the ability to check the health of the code-base. Seeing why your builds are failing provides you with an opportunity to make a fix faster. For this project, it is important that we are able to verify and validate the scripts required to build the GraalVM compiler for Linux and macOS, both locally and in a Docker container.

A CI/CD tool lets us add automated tests to ensure that we get the desired outcome from our scripts when every PR is merged. In addition to ensuring that our new code does not introduce a breaking change, another great feature of CI/CD tools is that we can automate the creation of binaries and the automatic deployment of those binaries, making them available for open source distribution.

Let’s get started

During the process of researching CircleCI as a CI/CD solution to build the GraalVM compiler, I learned that we could run builds via two different approaches, namely:

– A CircleCI build with a standard Docker container (longer build time, longer config script)
– A CircleCI build with a pre-built, optimised Docker container (shorter build time, shorter config script)

We will now go through the two approaches mentioned above and see the pros and cons of both of them.

Approach 1: using a standard Docker container

For this approach, CircleCI requires a docker image that is available in Docker Hub or another public/private registry it has access to. We will have to install the necessary dependencies in this available environment in order for a successful build. We expect the build to run longer the first time and, depending on the levels of caching, it will speed up.

To understand how this is done, we will be going through the CircleCI configuration file section-by-section (stored in .circleci/circle.yml), see config.yml in .circleci for the full listing, see commit df28ee7 for the source changes.

Explaining sections of the config file

The below lines in the configuration file will ensure that our installed applications are cached (referring to the two specific directories) so that we don’t have to reinstall the dependencies each time a build occurs:

    dependencies:
      cache_directories:
        - "vendor/apt"
        - "vendor/apt/archives"

We will be referring to the docker image by its full name (as available on http://hub.docker.com under the account name used – adoptopenjdk). In this case, it is a standard docker image containing JDK8 made available by the good folks behind the Adopt OpenJDK build farm. In theory, we can use any image as long as it supports the build process. It will act as the base layer on which we will install the necessary dependencies:

        docker:
          - image: adoptopenjdk/openjdk8:jdk8u152-b16

Next, in the pre-Install Os dependencies step, we will restore the cache, if it already exists, this may look a bit odd, but for unique key labels, the below implementation is recommended by the docs):

          - restore_cache:
              keys:
                - os-deps-{{ arch }}-{{ .Branch }}-{{ .Environment.CIRCLE_SHA1 }}
                - os-deps-{{ arch }}-{{ .Branch }}

Then, in the Install Os dependencies step we run the respective shell script to install the dependencies needed. We have set this step to timeout if the operation takes longer than 2 minutes to complete (see docs for timeout):

          - run:
              name: Install Os dependencies
              command: ./build/x86_64/linux_macos/osDependencies.sh
              timeout: 2m

Then, in then post-Install Os dependencies step, we save the results of the previous step – the layer from the above run step (the key name is formatted to ensure uniqueness, and the specific paths to save are included):

          - save_cache:
              key: os-deps-{{ arch }}-{{ .Branch }}-{{ .Environment.CIRCLE_SHA1 }}
              paths:
                - vendor/apt
                - vendor/apt/archives

Then, in the pre-Build and install make via script step, we restore the cache, if one already exists:

          - restore_cache:
              keys:
                - make-382-{{ arch }}-{{ .Branch }}-{{ .Environment.CIRCLE_SHA1 }}
                - make-382-{{ arch }}-{{ .Branch }}

Then, in the Build and install make via script step we run the shell script to install a specific version of make and it is set to timeout if step takes longer than 1 minute to finish:

          - run:
              name: Build and install make via script
              command: ./build/x86_64/linux_macos/installMake.sh
              timeout: 1m

Then, in the post Build and install make via script step, we save the results of the above action to the cache:

          - save_cache:
              key: make-382-{{ arch }}-{{ .Branch }}-{{ .Environment.CIRCLE_SHA1 }}
              paths:
                - /make-3.82/
                - /usr/bin/make
                - /usr/local/bin/make
                - /usr/share/man/man1/make.1.gz
                - /lib/

Then, we define environment variables to update JAVA_HOME and PATH at runtime. Here the environment variables are sourced so that we remember them for the next subsequent steps till the end of the build process (please keep this in mind):

          - run:
              name: Define Environment Variables and update JAVA_HOME and PATH at Runtime
              command: |
                echo '....'     <== a number of echo-es displaying env variable values
                source ${BASH_ENV}

Then, in the step to Display Hardware, Software, Runtime environment and dependency versions, as best practice we display environment-specific information and record it into the logs for posterity (also useful during debugging when things go wrong):

          - run:
              name: Display HW, SW, Runtime env. info and versions of dependencies
              command: ./build/x86_64/linux_macos/lib/displayDependencyVersion.sh

Then, we run the step to setup MX – this is important from the point of view of the GraalVM compiler (mx) is a specialised build system created to facilitate compiling and building Graal/GraalVM and  components):

          - run:
              name: Setup MX
              command: ./build/x86_64/linux_macos/lib/setupMX.sh ${BASEDIR}

Then, we run the important step to Build JDK JVMCI (we build the JDK with JVMCI enabled here) and timeout, if the process takes longer than 15 minutes without any output or if the process takes longer than 20 minutes in total to finish:

          - run:
              name: Build JDK JVMCI
              command: ./build/x86_64/linux_macos/lib/build_JDK_JVMCI.sh ${BASEDIR} ${MX}
              timeout: 20m
              no_output_timeout: 15m

Then, we run the step Run JDK JVMCI Tests, which runs tests as part of the sanity check after building the JDK JVMCI:

          - run:
              name: Run JDK JVMCI Tests
              command: ./build/x86_64/linux_macos/lib/run_JDK_JVMCI_Tests.sh ${BASEDIR} ${MX}

Then, we run the step Setting up environment and Build GraalVM Compiler, to set up the build environment with the necessary environment variables which will be used by the steps to follow:

          - run:
              name: Setting up environment and Build GraalVM Compiler
              command: |
                echo ">>>> Currently JAVA_HOME=${JAVA_HOME}"
                JDK8_JVMCI_HOME="$(cd ${BASEDIR}/graal-jvmci-8/ && ${MX} --java-home ${JAVA_HOME} jdkhome)"
                echo "export JVMCI_VERSION_CHECK='ignore'" >> ${BASH_ENV}
                echo "export JAVA_HOME=${JDK8_JVMCI_HOME}" >> ${BASH_ENV}
                source ${BASH_ENV}

Then, we run the step Build the GraalVM Compiler and embed it into the JDK (JDK8 with JVMCI enabled) which timeouts if the process takes longer than 7 minutes without any output or longer than 10 minutes in total to finish:

          - run:
              name: Build the GraalVM Compiler and embed it into the JDK (JDK8 with JVMCI enabled)
              command: |
                echo ">>>> Using JDK8_JVMCI_HOME as JAVA_HOME (${JAVA_HOME})"
                ./build/x86_64/linux_macos/lib/buildGraalCompiler.sh ${BASEDIR} ${MX} ${BUILD_ARTIFACTS_DIR}
              timeout: 10m
              no_output_timeout: 7m

Then, we run the simple sanity checks to verify the validity of the artifacts created once a build has been completed, just before archiving the artifacts:

          - run:
              name: Sanity check artifacts
              command: |
                ./build/x86_64/linux_macos/lib/sanityCheckArtifacts.sh ${BASEDIR} ${JDK_GRAAL_FOLDER_NAME}
              timeout: 3m
              no_output_timeout: 2m

Then, we run the step Archiving artifacts (means compressing and copying final artifacts into a separate folder) which timeouts if the process takes longer than 2 minutes without any output or longer than 3 minutes in total to finish:

          - run:
              name: Archiving artifacts
              command: |
                ./build/x86_64/linux_macos/lib/archivingArtifacts.sh ${BASEDIR} ${MX} ${JDK_GRAAL_FOLDER_NAME} ${BUILD_ARTIFACTS_DIR}
              timeout: 3m
              no_output_timeout: 2m

For posterity and debugging purposes, we capture the generated logs from the various folders and archive them:

          - run:
              name: Collecting and archiving logs (debug and error logs)
              command: |
                ./build/x86_64/linux_macos/lib/archivingLogs.sh ${BASEDIR}
              timeout: 3m
              no_output_timeout: 2m
              when: always
          - store_artifacts:
              name: Uploading logs
              path: logs/

Finally, we store the generated artifacts at a specified location – the below lines will make the location available on the CircleCI interface (we can download the artifacts from here):

          - store_artifacts:
              name: Uploading artifacts in jdk8-with-graal-local
              path: jdk8-with-graal-local/

Approach 2: using a pre-built optimised Docker container

For approach 2, we will be using a pre-built docker container, that has been created and built locally with all necessary dependencies, the docker image saved and then pushed to a remote registry for e.g. Docker Hub. And then we will be referencing this docker image in the CircleCI environment, via the configuration file. This saves us time and effort for running all the commands to install the necessary dependencies to create the necessary environment for this approach (see the details steps in Approach 1 section).

We expect the build to run for a shorter time as compared to the previous build and this speedup is a result of the pre-built docker image (we will see in the Steps to build the pre-built docker image section), to see how this is done). The additional speed benefit comes from the fact that CircleCI caches the docker image layers which in turn results in a quicker startup of the build environment.

We will be going through the CircleCI configuration file section-by-section (stored in .circleci/circle.yml) for this approach, see config.yml in .circleci for the full listing, see commit e5916f1 for the source changes.

Explaining sections of the config file

Here again, we will be referring to the docker image by it’s full name. It is a pre-built docker image neomatrix369/graalvm-suite-jdk8 made available by neomatrix369. It was built and uploaded to Docker Hub in advance before the CircleCI build was started. It contains the necessary dependencies for the GraalVM compiler to be built:

        docker:
          - image: neomatrix369/graal-jdk8:${IMAGE_VERSION:-python-2.7}
        steps:
          - checkout

All the sections below do the exact same tasks (and for the same purpose) as in Approach 1, see Explaining sections of the config file section.

Except, we have removed the below sections as they are no longer required for Approach 2:

    - restore_cache:
              keys:
                - os-deps-{{ arch }}-{{ .Branch }}-{{ .Environment.CIRCLE_SHA1 }}
                - os-deps-{{ arch }}-{{ .Branch }}
          - run:
              name: Install Os dependencies
              command: ./build/x86_64/linux_macos/osDependencies.sh
              timeout: 2m
          - save_cache:
              key: os-deps-{{ arch }}-{{ .Branch }}-{{ .Environment.CIRCLE_SHA1 }}
              paths:
                - vendor/apt
                - vendor/apt/archives
          - restore_cache:
              keys:
                - make-382-{{ arch }}-{{ .Branch }}-{{ .Environment.CIRCLE_SHA1 }}
                - make-382-{{ arch }}-{{ .Branch }}
          - run:
              name: Build and install make via script
              command: ./build/x86_64/linux_macos/installMake.sh
              timeout: 1m
          - save_cache:
              key: make-382-{{ arch }}-{{ .Branch }}-{{ .Environment.CIRCLE_SHA1 }}
              paths:
                - /make-3.82/
                - /usr/bin/make
                - /usr/local/bin/make
                - /usr/share/man/man1/make.1.gz

In the following section, I will go through the steps show how to build the pre-built docker image. It will involve running the bash scripts – ./build/x86_64/linux_macos/osDependencies.sh and ./build/x86_64/linux_macos/installMake.sh to install the necessary dependencies as part of building a docker image. And, finally pushing the image to Docker Hub (can be pushed to any other remote registry of your choice).

Steps to build the pre-built docker image

– Run build-docker-image.sh (see bash script source) which depends on the presence of Dockerfile (see docker script source). The Dockerfile does all the necessary tasks of running the dependencies inside the container i.e. runs the bash scripts ./build/x86_64/linux_macos/osDependencies.sh and ./build/x86_64/linux_macos/installMake.sh:

    $ ./build-docker-image.sh

– Once the image has been built successfully, run push-graal-docker-image-to-hub.sh after setting the USER_NAME and IMAGE_NAME (see source code) otherwise it will use the default values as set in the bash script:

    $ USER_NAME="[your docker hub username]" IMAGE_NAME="[any image name]" \
        ./push-graal-docker-image-to-hub.sh

CircleCI config file statistics: Approach 1 versus Approach 2

Areas of interest	Approach 1	Approach 2
Config file (full source list)	build-on-circleci	build-using-prebuilt-docker-image
Commit point (sha)	df28ee7	e5916f1
Lines of code (loc)	110 lines	85 lines
Source lines (sloc)	110 sloc	85 sloc
Steps (steps: section)	19	15
Performance (see Performance section)	Some speedup due to caching, but slower than Approach 2	Speed-up due to pre-built docker image, and also due to caching at different steps. Faster than Approach 1 Ensure DLC layering is enabled (its a paid feature)

What not to do?

Approach 1 issues

I came across things that wouldn’t work initially, but were later fixed with changes to the configuration file or the scripts:

• please make sure the .circleci/config.yml is always in the root directory of the folder
• when using the store_artifacts directive in the .circleci/config.yml file setting, set the value to a fixed folder name i.e. jdk8-with-graal-local/ – in our case, setting the path to ${BASEDIR}/project/jdk8-with-graal didn’t create the resulting artifact once the build was finished hence the fixed path name suggestion.
• environment variables: when working with environment variables, keep in mind that each command runs in its own shell hence the values set to environment variables inside the shell execution environment isn’t visible outside, follow the method used in the context of this post. Set the environment variables such that all the commands can see its required value to avoid misbehaviours or unexpected results at the end of each step.
• caching: use the caching functionality after reading about it, for more details on CircleCI caching refer to the caching docs. See how it has been implemented in the context of this post. This will help avoid confusions and also help make better use of the functionality provided by CircleCI.

Approach 2 issues

• Caching: check the docs when trying to use the Docker Layer Caching (DLC) option as it is a paid feature, once this is known the doubts about “why CircleCI keeps downloading all the layers during each build” will be clarified, for Docker Layer Caching details refer to docs. It can also clarify why in non-paid mode my build is still not as fast as I would like it to be.

General note:

• Light-weight instances: to avoid the pitfall of thinking we can run heavy-duty builds, check the documentation on the technical specifications of the instances. If we run the standard Linux commands to probe the technical specifications of the instance we may be misled by thinking that they are high specification machines. See the step that enlists the Hardware and Software details of the instance (see Display HW, SW, Runtime env. info and versions of dependencies section). The instances are actually Virtual Machines or Container like environments with resources like 2CPU/4096MB. This means we can’t run long-running or heavy-duty builds like building the GraalVM suite. Maybe there is another way to handle these kinds of builds, or maybe such builds need to be decomposed into smaller parts.
• Global environment variables: as each run line in the config.yml, runs in its own shell context, from within that context environment variables set by other executing contexts do not have access to these values. Hence in order to overcome this, we have adopted two methods:

• pass as variables as parameters to calling bash/shell scripts to ensure scripts are able to access the values in the environment variables
• use the source command as a run step to make environment variables accessible globally

End result and summary

We see the below screen (the last step i.e. Updating artifacts enlists where the artifacts have been copied), after a build has been successfully finished:

The artifacts are now placed in the right folder for download. We are mainly concerned about the jdk8-with-graal.tar.gz artifact.

Performance

Before writing this post, I ran multiple passes of both the approaches and jotted down the time taken to finish the builds, which can be seen below:

– Approach 1: standard CircleCI build (caching enabled)
– 13 mins 28 secs
– 13 mins 59 secs
– 14 mins 52 secs
– 10 mins 38 secs
– 10 mins 26 secs
– 10 mins 23 secs
– Approach 2: using pre-built docker image (caching enabled, DLC) feature unavailable)
– 13 mins 15 secs
– 15 mins 16 secs
– 15 mins 29 secs
– 15 mins 58 secs
– 10 mins 20 secs
– 9 mins 49 secs

Note: Approach 2 should show better performance when using a paid tier, as Docker Layer Caching) is available as part of this plan.

Sanity check

In order to be sure that by using both the above approaches we have actually built a valid JDK embedded with the GraalVM compiler, we perform the following steps with the created artifact:

– Firstly, download the jdk8-with-graal.tar.gz artifact from under the Artifacts tab on the CircleCI dashboard (needs sign-in):

– Then, unzip the .tar.gz file and do the following:

    tar xvf jdk8-with-graal.tar.gz

– Thereafter, run the below command to check the JDK binary is valid:

    cd jdk8-with-graal
    ./bin/java -version

– And finally check if we get the below output:

    openjdk version "1.8.0-internal"
    OpenJDK Runtime Environment (build 1.8.0-internal-jenkins_2017_07_27_20_16-b00)
    OpenJDK 64-Bit Graal:compiler_ab426fd70e30026d6988d512d5afcd3cc29cd565:compiler_ab426fd70e30026d6988d512d5afcd3cc29cd565 (build 25.71-b01-internal-jvmci-0.46, mixed mode)

– Similarly, to confirm if the JRE is valid and has the GraalVM compiler built in, we do this:

    ./bin/jre/java -version

– And check if we get a similar output as above:

    openjdk version "1.8.0-internal"
    OpenJDK Runtime Environment (build 1.8.0-internal-jenkins_2017_07_27_20_16-b00)
    OpenJDK 64-Bit Graal:compiler_ab426fd70e30026d6988d512d5afcd3cc29cd565:compiler_ab426fd70e30026d6988d512d5afcd3cc29cd565 (build 25.71-b01-internal-jvmci-0.46, mixed mode)

With this, we have successfully built JDK8 with the GraalVM compiler embedded in it and also bundled the Graal and Truffle components in an archive file, both of which are available for download via the CircleCI interface.

Note: you will notice that we do perform sanity checks of the binaries built just before we pack them into compressed archives, as part of the build steps (see bottom section of CircleCI the configuration files section).

Nice badges!

We all like to show-off and also like to know the current status of our build jobs. A green-colour, build status icon is a nice indication of success, which looks like the below on a markdown README page:

We can very easily embed both of these status badges displaying the build status of our project (branch-specific i.e. master or another branch you have created) built on CircleCI (see docs) on how to do that).

Conclusions

We explored two approaches to build the GraalVM compiler using the CircleCI environment. They were good experiments to compare performance between the two approaches and also how we can do them with ease. We also saw a number of things to avoid or not to do and also saw how useful some of the CircleCI features are. The documentation and forums do good justice when trying to make a build work or if you get stuck with something.

Once we know the CircleCI environment, it’s pretty easy to use and always gives us the exact same response (consistent behaviour) every time we run it. Its ephemeral nature means we are guaranteed a clean environment before each run and a clean up after it finishes. We can also set up checks on build time for every step of the build, and abort a build if the time taken to finish a step surpasses the threshold time-period.

The ability to use pre-built docker images coupled with Docker Layer Caching on CircleCI can be a major performance boost (saves us build time needed to reinstall any necessary dependencies at every build). Additional performance speedups are available on CircleCI, with caching of the build steps – this again saves build time by not having to re-run the same steps if they haven’t changed.

There are a lot of useful features available on CircleCI with plenty of documentation and everyone on the community forum are helpful and questions are answered pretty much instantly.

Next, let’s build the same and more on another build environment/build farm – hint, hint, are you think the same as me? Adopt OpenJDK build farm)? We can give it a try!

Thanks and credits to Ron Powell from CircleCI and Oleg Šelajev from Oracle Labs for proof-reading and giving constructive feedback. 

Please do let me know if this is helpful by dropping a line in the comments below or by tweeting at @theNeomatrix369, and I would also welcome feedback, see how you can reach me, above all please check out the links mentioned above.

Useful resources

– Links to useful CircleCI docs
– About Getting started | Videos
– About Docker
– Docker Layer Caching
– About Caching
– About Debugging via SSH
– CircleCI cheatsheet
– CircleCI Community (Discussions)
– Latest community topics
– CircleCI configuration and supporting files
– Approach 1: https://github.com/neomatrix369/awesome-graal/tree/build-on-circleci (config file and other supporting files i.e. scripts, directory layout, etc…)
– Approach 2: https://github.com/neomatrix369/awesome-graal/tree/build-on-circleci-using-pre-built-docker-container (config file and other supporting files i.e. scripts, directory layout, etc…)
– Scripts to build Graal on Linux, macOS and inside the Docker container
– Truffle served in a Holy Graal: Graal and Truffle for polyglot language interpretation on the JVM
– Learning to use Wholly GraalVM!
– Building Wholly Graal with Truffle!

Building Wholly Graal with Truffle!

Citation: credits to the feature image go to David Luders and reused under a CC license, the original image can be found on this Flickr page.

Introduction

It has been some time, since the two posts [1][2] on Graal/GraalVM/Truffle, and a general request was when are you going to write something about “how to build” this awesome thing called Graal. Technically, we will be building HotSpot’s C2 compiler (look for C2 in the glossary list) replacement, called Graal. This binary is different from the  GraalVM suite you download from OTN via http://graalvm.org/downloads.

I wasn’t just going to stop at the first couple of posts on this technology. In fact, one of the best ways to learn and get an in-depth idea about any tech work, is to know how to build it.

Getting Started

Building JVMCI for JDK8, Graal and Truffle is fairly simple, and the instructions are available on the graal repo. We will be running them on both the local (Linux, MacOS) and container (Docker) environments. To capture the process as-code, they have been written in bash, see https://github.com/neomatrix369/awesome-graal/tree/master/build/x86_64/linux_macos.

During the process of writing the scripts and testing them on various environments, there were some issues, but these were soon resolved with the help members of the Graal team — thanks Doug.

Running scripts

Documentation on how to run the scripts are provided in the README.md on awesome-graal. For each of the build environments they are merely a single command:

Linux & MacOS

$ ./local-build.sh

$ RUN_TESTS=false           ./local-build.sh

$ OUTPUT_DIR=/another/path/ ./local-build.sh

Docker

$ ./docker-build.sh

$ DEBUG=true                ./docker-build.sh

$ RUN_TESTS=false           ./docker-build.sh

$ OUTPUT_DIR=/another/path/ ./docker-build.sh

Both the local and docker scripts pass in the environment variables i.e. RUN_TESTS and OUTPUT_DIR to the underlying commands. Debugging the docker container is also possible by setting the DEBUG environment variable.

For a better understanding of how they work, best to refer to the local and docker scripts in the repo.

Build logs

I have provided build logs for the respective environments in the build/x86_64/linux_macos  folder in https://github.com/neomatrix369/awesome-graal/

Once the build is completed successfully, the following messages are shown:

[snipped]

>> Creating /path/to/awesome-graal/build/x86_64/linux/jdk8-with-graal from /path/to/awesome-graal/build/x86_64/linux/graal-jvmci-8/jdk1.8.0_144/linux-amd64/product
Copying /path/to/awesome-graal/build/x86_64/linux/graal/compiler/mxbuild/dists/graal.jar to /path/to/awesome-graal/build/x86_64/linux/jdk8-with-graal/jre/lib/jvmci
Copying /path/to/awesome-graal/build/x86_64/linux/graal/compiler/mxbuild/dists/graal-management.jar to /path/to/awesome-graal/build/x86_64/linux/jdk8-with-graal/jre/lib/jvmci
Copying /path/to/awesome-graal/build/x86_64/linux/graal/sdk/mxbuild/dists/graal-sdk.jar to /path/to/awesome-graal/build/x86_64/linux/jdk8-with-graal/jre/lib/boot
Copying /path/to/awesome-graal/build/x86_64/linux/graal/truffle/mxbuild/dists/truffle-api.jar to /path/to/awesome-graal/build/x86_64/linux/jdk8-with-graal/jre/lib/truffle

>>> All good, now pick your JDK from /path/to/awesome-graal/build/x86_64/linux/jdk8-with-graal :-)

Creating Archive and SHA of the newly JDK8 with Graal & Truffle at /home/graal/jdk8-with-graal
Creating Archive jdk8-with-graal.tar.gz
Creating a sha5 hash from jdk8-with-graal.tar.gz
jdk8-with-graal.tar.gz and jdk8-with-graal.tar.gz.sha256sum.txt have been successfully created in the /home/graal/output folder.

Artifacts

All the Graal and Truffle artifacts are created in the graal/compiler/mxbuild/dists/ folder and copied to the newly built jdk8-with-graal folder, both of these will be present in the folder where the build.sh script resides:

jdk8-with-graal/jre/lib/jvmci/graal.jar
jdk8-with-graal/jre/lib/jvmci/graal-management.jar
jdk8-with-graal/jre/lib/boot/graal-sdk.jar
jdk8-with-graal/jre/lib/truffle/truffle-api.jar

In short, we started off with vanilla JDK8 (JAVA_HOME) and via the build script created an enhanced JDK8 with Graal and Truffle embedded in it. At the end of a successful build process, the script will create a .tar.gz archive file in the jdk8-with-graal-local folder, alongside this file you will also find the sha5 hash of the archive.

In case of a Docker build, the same folder is called jdk8-with-graal-docker and in addition to the above mentioned files, it will also contain the build logs.

Running unit tests

Running unit tests is a simple command:

mx --java-home /path/to/jdk8 unittest

This step should follow the moment we have a successfully built artifact in the jdk8-with-graal-local folder. The below messages indicate a successful run of the unit tests:

>>>> Running unit tests...
Warning: 1049 classes in /home/graal/mx/mxbuild/dists/mx-micro-benchmarks.jar skipped as their class file version is not supported by FindClassesByAnnotatedMethods
Warning: 401 classes in /home/graal/mx/mxbuild/dists/mx-jacoco-report.jar skipped as their class file version is not supported by FindClassesByAnnotatedMethods
WARNING: Unsupported class files listed in /home/graal/graal-jvmci-8/mxbuild/unittest/mx-micro-benchmarks.jar.jdk1.8.excludedclasses
WARNING: Unsupported class files listed in /home/graal/graal-jvmci-8/mxbuild/unittest/mx-jacoco-report.jar.jdk1.8.excludedclasses
MxJUnitCore
JUnit version 4.12
............................................................................................
Time: 5.334

OK (92 tests)

JDK differences

So what have we got that’s different from the JDK we started with. If we compare the boot JDK with the final JDK here are the differences:

Combination of diff between $JAVA_HOME and jdk8-with-graal and meld will give the above:

diff -y --suppress-common-lines $JAVA_HOME jdk8-with-graal | less

meld $JAVA_HOME ./jdk8-with-graal

Note: $JAVA_HOME points to your JDK8 boot JDK.

Build execution time

The build execution time was captured on both Linux and MacOS and there was a small difference between running tests and not running tests:

Running the build with or without tests on a quad-core, with hyper-threading:

 real 4m4.390s
 user 15m40.900s
 sys 1m20.386s
 ^^^^^^^^^^^^^^^
 user + sys = 17m1.286s (17 minutes 1.286 second)

Similar running the build with and without tests on a dual-core MacOS, with 4GB RAM, SSD drive, differs little:

 real 9m58.106s
 user 18m54.698s 
 sys 2m31.142s
 ^^^^^^^^^^^^^^^ 
 user + sys = 21m25.84s (21 minutes 25.84 seconds)

Disclaimer: these measurements can certainly vary across the different environments and configurations. If you have a more accurate way to benchmark such running processes, please do share back.

Summary

In this post, we saw how we can build Graal and Truffle for JDK8 on both local and container environments.

The next thing we will do is build them on a build farm provided by Adopt OpenJDK. We will be able to run them across multiple platforms and operating systems, including building inside docker containers. This binary is different from the GraalVM suite you download from OTN via http://graalvm.org/downloads, hopefully we will be able to cover GraalVM in a future post.

Thanks to Julien Ponge for making his build script available for re-use and the Graal team for supporting during the writing of this post.

Feel free to share your feedback at @theNeomatrix369. Pull requests with improvements and best-practices are welcome at https://github.com/neomatrix369/awesome-graal.

Truffle served in a Holy Graal: Graal and Truffle for polyglot language interpretation on the JVM

Reblogging from ZeroTurnaround’s Rebellabs blog site

One of the most fascinating additions to Java 9 is the JVMCI: Java-Level JVM Compiler Interface, a Java based compiler interface which allows us to plug in a dynamic compiler into the JVM. One of the main inspirations for including it into Java 9 was due to project Graal — a dynamic state-of-the-art compiler written in Java.

In this post we look at the reasons Graal is such a fascinating project, its advantages, what are the general code optimization ideas, some performance comparisons, and why would you even bother with tinkering with a new compiler.

Like everyone else we were inspired by the vJUG session by Chris Seaton on Graal – it looks like a great tool and technology and so we decided to play with the technology and share it with the community.

…you can read the rest at ZeroTurnaround’s Rebellabs blogs

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In case, you are wondering what some of the ASCII-art images in one of the paragraphs is about, here’s a bit of explanation, hopefully it will clear up any doubts.

How does it actually work?

A typical flow would look like this:

AST → Abstract Syntax Tree  (explicit data structures in memory)

We all know that a JIT is embedded inside HotSpot or the JVM. It’s old, complicated, written in C++ and assembly and is fairly hard to understand. It is a black box and there is no way to hook or link into the JIT.  All the JVM languages have to go through the same route:  

(ASM = assembly)

The flow or route when dealing with traditional compilers and VM would be:

But with Graal, we get the below route or flow:

(notice Graal skips the steps that create byte-code by directly generating platform specific machine code)

Graal basically helps moving the control-flow from Code to the JIT bypassing the JVM (HotSpot, in our case). It means we will be running faster and more performant applications, on the JVM. These applications will not be interpreted anymore but compiled to machine code on fly or even natively.

---

I hope you enjoyed the read, please feel free to share any constructive feedback, so we can improve the material for the community as a whole. We learnt a lot while drafting this post and hope the same for you.

Original post by @theNeomatrix369 and  @shelajev !

How is Java / JVM built ? Adopt OpenJDK is your answer!

Introduction & history

As some of you may already know, starting with Java 7, OpenJDK is the Reference Implementation (RI) to Java. The below time line gives you an idea about the history of OpenJDK:

OpenJDK history (2006 till date)

See Adopt OpenJDK – the past present and future [1] for some more details.

If you have wondered about the JDK or JRE binaries that you download from vendors like Oracle, Red Hat, etcetera, then the clue is that these all stem from OpenJDK. Each vendor then adds some extra artefacts that are not open source yet due to security, proprietary or other reasons.

What is OpenJDK made of ?

OpenJDK is made up of a number of repositories, namely corba, hotspot, jaxp, jaxws, jdk, langtools, and nashorn. Between OpenjJDK8 and OpenJDK9 there have been no new repositories introduced, but lots of new changes and restructuring, primarily due to Jigsaw – the modularisation of Java itself [2] [3] [4] [5].

repo composition, language breakdown (metrics are estimated)

Recent history

OpenJDK Build Benchmarks – build-infra (Nov 2011) by Fredrik Öhrström, ex-Oracle, OpenJDK hero!

Fredrik Öhrström visited the LJC [16] in November 2011 where he showed us how to build OpenJDK on the three major platforms, and also distributed a four page leaflet with the benchmarks of the various components and how long they took to build. The new build system and the new makefiles are a result of the build system being re-written (build-infra).

Below are screen-shots of the leaflets, a good reference to compare our journey:

The New Build System [23]

The New Makefiles [24]

Build Benchmarks page 1 [25]

Build Benchmarks page 2 [26]

How has Java the language and platform built over the years ?

Java is built by bootstrapping an older (previous) version of Java – i.e. Java is built using Java itself as its building block. Where older components are put together to create a new component which in the next phase becomes the building block. A good example of bootstrapping can be found at Scheme from Scratch [6] or even on Wikipedia [7].

OpenJDK8 [8] is compiled and built using JDK7, similarly OpenJDK9 [9] is compiled and built using JDK8. In theory OpenJDK8 can be compiled using the images created from OpenJDK8, similarly for OpenJDK9 using OpenJDK9. Using a process called bootcycle images – a JDK image of OpenJDK is created and then using the same image, OpenJDK is compiled again, which can be accomplished using a make command option:

$ make bootcycle-images       # Build images twice, second time with newly built JDK

make offers a number of options under OpenJDK8 and OpenJDK9, you can build individual components or modules by naming them, i.e.

$ make [component-name] | [module-name]

or even run multiple build processes in parallel, i.e.

$ make JOBS=<n>                 # Run <n> parallel make jobs

Finally install the built artefact using the install option, i.e.

$ make install

Some myths busted

OpenJDK or Hotspot to be more specific isn’t completely written in C/C++, a good part of the code-base is good ‘ole Java (see the composition figure above). So you don’t have to be a hard-core developer to contribute to OpenJDK. Even the underlying C/C++ code code-base isn’t scary or daunting to look at. For example here is an extract of a code snippet from vm/memory/universe.cpp in the HotSpot repo –

http://hg.openjdk.java.net/jdk6/jdk6/hotspot/raw-file/a541ca8fa0e3/src/share/vm/memory/universe.cpp [10]:

.
.
.
Universe::initialize_heap()

if (UseParallelGC) {
    #ifndef SERIALGC
    Universe::_collectedHeap = new ParallelScavengeHeap();
    #else // SERIALGC
        fatal("UseParallelGC not supported in this VM.");
    #endif // SERIALGC

} else if (UseG1GC) {
    #ifndef SERIALGC
    G1CollectorPolicy* g1p = new G1CollectorPolicy();
    G1CollectedHeap* g1h = new G1CollectedHeap(g1p);
    Universe::_collectedHeap = g1h;
    #else // SERIALGC
        fatal("UseG1GC not supported in java kernel vm.");
    #endif // SERIALGC

} else {
    GenCollectorPolicy* gc_policy;

    if (UseSerialGC) {
        gc_policy = new MarkSweepPolicy();
    } else if (UseConcMarkSweepGC) {
        #ifndef SERIALGC
        if (UseAdaptiveSizePolicy) {
            gc_policy = new ASConcurrentMarkSweepPolicy();
        } else {
            gc_policy = new ConcurrentMarkSweepPolicy();
        }
        #else // SERIALGC
            fatal("UseConcMarkSweepGC not supported in this VM.");
        #endif // SERIALGC
    } else { // default old generation
        gc_policy = new MarkSweepPolicy();
    }

    Universe::_collectedHeap = new GenCollectedHeap(gc_policy);
}
.
.
.

(please note that the above code snippet might have changed since published here)

The things that appears clear from the above code-block are, we are looking at how pre-compiler notations are used to create Hotspot code that supports a certain type of GC i.e. Serial GC or Parallel GC. Also the type of GC policy is selected in the above code-block when one or more GC switches are toggled i.e. UseAdaptiveSizePolicy when enabled selects the Asynchronous Concurrent Mark and Sweep policy. In case of either Use Serial GC or Use Concurrent Mark Sweep GC are not selected, then the GC policy selected is Mark and Sweep policy. All of this and more is pretty clearly readable and verbose, and not just nicely formatted code that reads like English.

Further commentary can be found in the section called Deep dive Hotspot stuff in the Adopt OpenJDK Intermediate & Advance experiences [11] document.

Steps to build your own JDK or JRE

Earlier we mentioned about JDK and JRE images – these are no longer only available to the big players in the Java world, you and I can build such images very easily. The steps for the process have been simplified, and for a quick start see the Adopt OpenJDK Getting Started Kit [12] and Adopt OpenJDK Intermediate & Advance experiences [11] documents. For detailed version of the same steps, please see the Adopt OpenJDK home page [13]. Basically building a JDK image from the OpenJDK code-base boils down to the below commands:

(setup steps have been made brief and some commands omitted, see links above for exact steps)

 $ hg clone http://hg.openjdk.java.net/jdk8/jdk8 jdk8  (a)...OpenJDK8

or

$ hg clone http://hg.openjdk.java.net/jdk9/jdk9 jdk9  (a)...OpenJDK9

$ ./get_source.sh                                     (b)

$ bash configure                                      (c)

$ make clean images                                   (d)

(setup steps have been made brief and some commands omitted, see links above for exact steps)

To explain what is happening at each of the steps above:

(a) We clone the openjdk mercurial repo just like we would using git clone ….

(b) Once we have step (a) completed, we change into the folder created, and run the get_source.sh command, which is equivalent to a git fetch or a git pull, since the step (a) only brings down base files and not all of the files and folders.

(c) Here we run a script that checks for and creates the configuration needed to do the compile and build process

(d) Once step (c) is success we perform a complete compile, build and create JDK and JRE images from the built artefacts

As you can see these are dead-easy steps to follow to build an artefact or JDK/JRE images [step (a) needs to be run only once].

Benefits

– contribute to the evolution and improvement of the Java the language & platform

– learn about the internals of the language and platform

– learn about the OS platform and other technologies whilst doing the above

– get involved in F/OSS projects

– stay on top the latest changes in the Java / JVM sphere

– knowledge and experience that helps professionally but also these are not readily available from other sources (i.e. books, training, work-experience, university courses, etcetera).

– advancement in career

– personal development (soft skills and networking)

Contribute

Join the Adopt OpenJDK [13] and Betterrev [15] projects and contribute by giving us feedback about everything Java including these projects. Join the Adoption Discuss mailing list [14] and other OpenJDK related mailing lists to start with, these will keep you updated with latest progress and changes to OpenJDK. Fork any of the projects you see and submit changes via pull-requests.

Thanks and support

Adopt OpenJDK [13] and umbrella projects have been supported and progressed with help of JCP [21], the Openjdk team [22], JUGs like London Java Community [16], SouJava [17] and other JUGs in Brazil, a number of JUGs in Europe i.e. BGJUG (Bulgarian JUG) [18], BeJUG (Belgium JUG) [19], Macedonian JUG [20], and a number of other small JUGs. We hope in the coming time more JUGs and individuals would get involved. If you or your JUG wish to participate please get in touch.

—-

Credits

Special thanks to +Martijn Verburg (incepted Adopt OpenJDK),+Richard Warburton, +Oleg Shelajev, +Mite Mitreski, +Kaushik Chaubal and +Julius G for helping improve the content and quality of this post, and sharing their OpenJDK experience with us.

—-

How to get started ?

Join the Adoption Discuss mailing list [14], go to the Adopt OpenJDK home page [13] to get started, followed by referring to the Adopt OpenJDK Getting Started Kit [12] and Adopt OpenJDK Intermediate & Advance experiences [11] documents.

Please share your comments here or tweet at @theNeomatrix369.

Resources

[1] Adopt OpenJDK – the past present and future

[2] http://mreinhold.org/blog/on-the-next-train

[3] http://mreinhold.org/blog/jigsaw-phase-two

[4] http://mreinhold.org/blog/late-for-the-train-qa

[5] http://openjdk.java.net/projects/jigsaw/

[6] Scheme from Scratch

[7] Bootstrapping on Wikipedia

[8] OpenJDK8

[9] OpenJDK9

[10] Source src/share/vm/memory/universe.cpp in hotspot

[11] Adopt OpenJDK Intermediate & Advance experiences

[12] Adopt OpenJDK Getting Started Kit

[13] Adopt OpenJDK home page

[14] Adoption Discuss

[15] Betterrev

[16] London Java Community

[17] SouJava

[18] BGJUG (Bulgarian JUG)

[19] BeJUG (Belgium JUG)

[20] Macedonian JUG

[21] Java Community Process – JCP

[22] OpenJDK team

Our sister project – Adopt-a-JSR

[23] The New Build System

[24] The New Makefiles

[25] Build Benchmarks page 1

[26] Build Benchmarks page 2

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This post is part of the Java Advent Calendar and is licensed under the Creative Commons 3.0 Attribution license. If you like it, please spread the word by sharing, tweeting, FB, G+ and so on!

(Part 3 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al

This is a continuation of the previous post titled (Part 2 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al.

In our first review, The Atlassian guide to GC tuning is an extensive post covering the methodology and things to keep in mind when tuning GC, practical examples are given and references to important resources are also made in the process. The next one How NOT to measure latency by Gil Tene, he discusses some common pitfalls encountered in measuring and characterizing latency, demonstrating and discussing some false assumptions and measurement techniques that lead to dramatically incorrect reporting results, and covers simple ways to sanity check and correct these situations.  Finally Kirk Pepperdine in his post Poorly chosen Java HotSpot Garbage Collection Flags and how to fix them! throws light on some JVM flags – he starts with some 700 flags and boils it down to merely 7 flags. Also cautions you to not just draw conclusions or to take action in a whim but consult and examine – i.e. measure don’t guess!

….read more (reblogged from the Java Advent Calendar)

(Part 2 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al

This is a continuation of the previous post titled (Part 1 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al.

Without any further ado, lets get started with our next set of blogs and videos, chop…chop…! This time its Martin Thompson’s blog posts and talks. Martin’s first post on Java Garbage collection distilled basically distils the GC process and the underlying components including throwing light on a number of interesting GC flags (-XX:…). In his next talk he does his myth busting shaabang about mechanical sympathy, what people correctly believe in and the misconceptions. In the talk on performance testing, Martin takes its further and fuses Java, OS and the hardware to show how understanding of all these aspects can help write better programs.

Java Garbage Collection Distilled by Martin Thompson

There are too many flags to allow tuning the GC to achieve the throughput and latency your application requires. There’s plenty of documentation on the specifics of the bells and whistles around them but none to guide you through them.

….read more (reblogged from the Java Advent Calendar)

(Part 1 of 3): Synopsis of articles & videos on Performance tuning, JVM, GC in Java, Mechanical Sympathy, et al

I have been contemplating for a number of months about reviewing a cache of articles and videos on topics like Performance tuning, JVM, GC in Java, Mechanical Sympathy, etc… and finally took the time to do it – may be this was the point in my intellectual progress when was I required to do such a thing!

Thanks to Attila-Mihaly for giving me the opportunity to write a post for his yearly newsletter Java Advent Calendar, hence a review on various Java related topics fits the bill! The selection of videos and articles are purely random, and based on the order in which they came to my knowledge. My hidden agenda is to mainly go through them to understand and broaden my own knowledge at the same time share any insight with others along the way….read more (reblogged from the Java Advent Calendar)