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

03 Hotspot versus GraalVM

Reblogging from ZeroTurnaround’s Rebellab 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 Rebellab blogs


 

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:

02-a Program to machine code diagram (excludes expansion)
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:  

02-b Program to machine code diagram (via byte-code)

(ASM = assembly)

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

02-c Program to machine code diagram (via JIT)
But with Graal, we get the below route or flow:

02-d Program to machine code diagram (via AST)
(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 !

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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)
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:

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 –
.
.
.
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
[17] SouJava

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.

(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)