Jax keynote

Marcus Lagergren | Oracle
Why dynamic languages
on the JVM matter

Marcus Lagergren | Oracle
Why dynamic languages
on the JVM matter
[and project Nashorn]

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I am here to talk about…
The Java Runtime:
The JVM

The Universal Meta-
execution environment

The JVM as a multi-
language runtime

The JVM as a multi-
language runtime
(especially in the context of dynamic languages)

History
(what is a runtime, anyway?)

LISP
1950s – First compiler in 1962

LISP
Also – Garbage Collection!

Smalltalk
First class library.

Smalltalk
First class library. First visual GUI
driven IDE.

Smalltalk
First class library. First visual GUI
driven IDE. Bytecode.

Dynamic languages
ActionScript Adenine APL BASIC
BeanShell Clojure ColdFusion Dart
Dylan Groovy E Fancy JavaScript
Julia Lua MATLAB Objective-C Perl
PHP Powershell Python Qore R
REBOL REXX Ruby Scheme
Smalltalk Snit Tcl VBScript Yoix etc
etc etc etc…

Dynamic languages
•  Dynamic languages are hot today because
–  They are easy to use
–  Have no explicit compile stage
–  Have good code readability
–  Allow short development time for small projects
–  Performance is good enough

Trendy Dynamic Languages
Already on top of the JVM

…and of course
V8, Futhark, Carakan, SpiderMonkey,
JägerMonkey, *Monkey, Nitro, Rhino,
Nashorn, etc etc

Putting your
language on top of
the JVM

Why?
•  You get so much for free!
–  Automatic memory management
–  State of the art JIT optimizations
–  Native threading capability
–  Hybridization (javax.scripting, JSR-223)
–  Extending Java
–  Man decades of high tech

Why?
0
100000
200000
300000
400000
500000
Code bases
Lines

Why?
0
100000
200000
300000
400000
500000
Code bases
Lines
If it were all about code complexity – TOTALLY WORTH IT!

“All problems in computer science can be solved
by another level of indirection”
- David Wheeler

Sounds good – implement it!
•  Just serve up some bytecode
•  People have been doing it since 1996

They have been doing it a lot,
actually…
Fantom
Fortress
BeanShell
Jaskell
ANTLR
JudoScript
ABCL
Erjang
X10
jdart
jgo
Nice
Gosu
Jacl

“All problems in computer science can be solved
by another level of indirection”
- David Wheeler
“Except for the problem of too many layers of
indirection”
- Kevlin Henney

So why is it hard?
•  “Java bytecode”
–  Notice the “Java”
•  There are “classes”, “methods”, size
limitations, strong types
•  Languages can be much more dynamic than
Java
–  Different linkage
–  Loose types

So why is it hard?
•  Different levels of “hard”
•  Square peg, round hole or round peg, oval
hole
•  Scala is a fairly good fit
•  Ruby or JavaScript are (at least at first
glance) pretty lousy ones

Not every language has
exactly 5 strong types
int, float, long, double, Object

int sum(int a, int b) {
return a + b;
}

iload_1
iload_2
iadd
ireturn

function sum(a, b) {
return a + b;
}

???
???
???
???

Also: It is hard to
swap out code
with other code

Applicability and Performance
•  The extra layer also costs us performance
•  How can we work around it?

•  Passive
–  Just wait
–  JIT is getting better all the time, GC is getting
better all the time

•  Passive
–  Just wait
–  JIT is getting better all the time, GC is getting
better all the time
•  Active
–  Punch through the indirection layer
–  There are tools these days

Punch through the indirection
layer
invokedynamic is my ice pick

Invokedynamic
•  Breaks the constraints of Java calls and
linkage
•  Can implement calls that act like function
pointers
•  More general: can implement custom data
access
•  Makes it possible to efficiently swap out code

The whole point:
The JVM can
optimize this!

The Nashorn
Project
(a Rhino for 2013)

Rationale
•  Proof of concept: invokedynamic
•  Does it provide all required functionality?
•  Does it perform?
•  Back in late 2010:
–  We must become the ultimate invokedynamic
consumer and find out
–  Cross communication with other teams

Rationale – JavaScript?
•  Extremely dynamic
–  All (well, most) getters, setters, calls have to be
invokedynamics
•  Rhino is slow and old
•  JSR-223
–  Should make it easy to provide POC apps for
Nashorn

Performance
rhino

0

2000

4000

6000

8000

10000

12000

rhino

nashorn

Further POC: node.jar
•  A node.js implmentation in only Java and
JavaScript
–  Forked the original node.js – threw out all native
code
–  Async I/O implemented with Grizzly
•  Deploys fine on the ARM JVM on Raspberry
PI
•  Might just as easy be a Java EE cloud
offering

Nashorn already in OpenJDK 8
Now: more Nashorn & JVM performance
enhancements
Now: more powerful hybrid proof of
concepts, e.g. node.jar, JavaFX

Contribute!
1.  Ask the community to contribute
functionality, testing, performance [analysis],
bug fixes, library optimizations, browser
simulation frameworks, kick-ass hybrid Java
solutions. JVM optimizations
2.  …
3.  PROFIT!
blogs.oracle.com/nashorn
nashorn-dev@openjdk.java.net

Can we do better than the ice
pick?
Reshape the hole!

Let’s continue building our
“future VM”
•  An open source incubator for
JVM futures
•  Contains code fragments
(patches)
•  Migration to OpenJDK requires
–  A standard
–  A feature release plan
mlvm-dev@openjdk.java.net

It’s more than just
invokedynamic
•  Unified type systems
•  Pluggable frontends, “bytecode 2.0”
•  Tail calls
•  (delimited) Continuations / Coroutines
•  Tuple types or C-style structs
•  Tagged values
•  Arrays 2.0
•  …

It’s not just invokedynamic
The JVM is evolving to become the
multi-language runtime

Danke!
[Hopefully, I’ll see you again at the
Nashorn / invokedynamic deep dive 16.45 this
afternoon]
@lagergren

Jax keynote

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