JVMCON Java in the 21st Century: are you thinking far enough ahead?

© 2015 INTERNATIONAL BUSINESS MACHINES CORPORATION
@spoole167
Java in the 21 Century: Are
you thinking far enough
ahead?
JVMCON 2018

@spoole167
This talk may seem to be about possible futures
for Java and the JVM

This talk is actually about why we have to think differently
about solving the problems of the future
Cloud Data Machine And
Analytics Learning Beyond
?

@spoole167
So really this talk is about your future.

@spoole167
Whatchya thinking
about now?

@spoole167
Thinking Java?
Still learning about features in Java 8?
Looking at Java 9 or going to Java 10?
Trying to understand the new feature release process?
What does “LTS” mean for Java?
Exploring “Java Platform Module System”?
Trying out Jshell?
Figuring out jlink?

@spoole167It’s easy to focus on now – it’s what we get paid for

@spoole167
What about a wider view?
What does it mean for EE now Oracle are donating it to Eclipse?
Why have IBM open sourced their JVM and Application Servers?
What should you be doing with MicroProfile?
Is Spring the right answer?
Should I be learning other programming languages?
Where does Java fit?

@spoole167Let’s think about what’s driving us

@spoole167
Economics
Faster, cheaper, easier, better …

@spoole167
Economics
Faster, cheaper, easier, better …
Like ‘Cloud’

@spoole167
From a JVM developers point of view…

@spoole167
Cloud sucks!

@spoole167
You wanted Very long running, efficient,
monolithic applications
You were willing to trade startup time
for throughput
You were in it for the long
haul

@spoole167
Short lived, container based, micro
service oriented, instant-on, always
available, cross server, polyglot
services
Now you want

@spoole167
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 1 2 3 4 5 6 7 8 9 101112131415161718
Throughput
Throughput
0
0.5
1
1.5
0 1 2 3 4 5 6
Throughput
Throughput
0
0.5
1
1.5
0 1 2 3 4 5 6
Throughput
Throughput
0
0.5
1
1.5
0 1 2 3 4 5 6
Throughput
Throughput
0
0.5
1
1.5
0 1 2 3 4 5 6
Throughput
Throughput
You want all of these models

@spoole167
And you want it ..

@spoole167
Is to innovate faster – or loose to the competition
The immediate challenge for Java and the JVM

@spoole167
And to be fair – the JVM is rising to the challenges of Cloud

predictable
consistent cadence
easier migration increased innovation
There are good signs that our
ecosystem is positioning for a faster
pace

Every development
team has both
common and unique
problems to solve.
Open source is key
to fast innovation
and adoption
OpenJDK
Eclipse OpenJ9
Open Liberty
Eclipse MicroProfile
Java EE
IBM Cloud
Docker
Kubernetes
Enabling everyone to participate
(and offering multiple starting points)

lambda
streams
modules
reactive streams
panama
valhalla
penrose
amber
Giving Java innovation a faster cadence

Tomcat
Glassfish
Open Liberty
…
OpenJDK + Hotspot
OpenJDK + OpenJ9
J2EE
Micro-profile
And a variety of implementations to choose
from

Container
awareness
Re-optimised JITs
Re-tuned GC’s
AOT
Generating New JVM
technologies
Jit As A Service
<your idea here>

Cloud. We do know what to do.
Cloud makes you think differently
but mostly about footprint, resilience
and scaling
Modularity, Lambdas
J2EE going to Eclipse
That’s not really a big change.
How do you do things like…

Imagine creating systems that can
Tailor responses to the personalities of your
customers without meeting a single one of them.
improve themselves
over time, learning
from and adapting to
the world around
them.
identify their own inefficiencies-and address them
automatically-in real time.
Uncover patterns, resources, trends and other
competitive advantages invisible to competitors and
their information systems.

@spoole167Some people ask - Why should we use Java?

IBM support three open runtimes
because between them they cover all
the bases for Cloud: both developer
communities and technical
capabilities

We’re going to take Java to places its never been
before.
And you’re coming too.
Here’s why…

3
1
Scripting Language Modern Native LanguageRuntime Language

3
2
Type Safe Type Safe, with InferenceDynamically Typed
Type Safe means JIT’s or compilers can optimise code
significantly better than a dynamically type language
Since an int is always an int
In Javascript a int is a thing until the very last minute

3
3
Bytecode: JIT Compiled JIT Compiled Pre-Compiled
JIT compilers can optimize as the workload changes.
Pre compiled code can’t do that

3
4
Garbage Collected Garbage Collected Reference Counted
GC can run in the background at the cost of a buffer of memory. Can be
parallelized more effectively and more accurately (no circular
references)

3
5
Concurrent Threaded Single Thread Concurrent Work Pool
Single threaded means no locking or syncronisation needed. But CPU
workload is a major Achilles heel

3
6
Concurrent Threaded Single Thread Concurrent Work Pool
All Platforms All Platforms Apple Platforms and Linux

3
7
Runtime Language
Type Safe
Bytecode: JIT Compiled
Garbage Collected
Concurrent Threaded
All Platforms
These characteristics
let us take the JVM
anywhere.
No other runtime
environment comes
close

Cloud
IoT
AI
Data
Analytics
Real time
?
No other runtime
environment comes close

The biggest challenge for all of us is
learning to solve problems differently

The new problems we face are not ones
we can easily internalize, visualize
or even compute
• The reality of data analytics
• The promise of AI
These drivers are changing the face of computing as
we know it. And it’s barely started

@spoole167
The common challenges
Effective optimization
Visualisation of complex patterns
Extracting meaning from enormous amounts of data.
All things human beings are poor at doing
And so are current computer architectures

@spoole167
Machine Learning etc
• Helps us find reasonable answers to questions.
• No guarantees on it being the best answer.
Organize a group of people at a table.
So that you get the ‘best’ conversation
You decide what
‘best’ means

@spoole167
Two or three people - easy
What about 10? - how many combinations to consider?

@spoole167
What about 10? - how many combinations to consider?
Going to need
some help here
3628800

@spoole167
What about 150?

@spoole167
571338395644585459047893286526105400318
955357860112641825483758331798291248453
983931265744886753111453771078787468542
041626662501986845044663559491959220665
749425920957357789293253572904449624724
054167907221184454371222696755200000000
00000000000000000000000000000
Going to need a lot of help
here

@spoole167
Machine Learning works because you design
and teach it – do you know how to do that?

@spoole167
Lets do something more real

c c e n t u r y b j
m k h l y t n e w t
t c i g a f n n o y
f d h t u s i a o v
i a w a h o h r v e
d i r n v e n y s i
g a p t u a o e x t
q f e a m o j k b o
y i c h r b y p n a
t t n v a e i z h i
Java
In
The
Twenty
First
Century
Are
you
thinking
far
enough
ahead
IBM
Find
which
one of
these
words is
missing

@spoole167
How do you solve this problem?
For each String in the list.
Visit each element in the grid
Check if the string matches in any of the eight directions.
Record if found
Report which of the strings was not found

r c e n t u r y l m
y q h m y t n e w t
j x v g f a s r h h
f u r t u k h o u q
y a m a h o c e k n
s b r p v e n c a t
a y g e u a j e a d
h z g a m o j i p b
h z a e r b y a n n
d m t f g e i v e i
Java
In
The
Twenty
First
Century
Are
you
thinking
far
enough
ahead
IBM

for(y=0;y<side && dir==null;y++) {
for(x=0;x<side && dir==null;x++) {
char c=p.charAt(x, y);
if(c==w.charAt(0)) {
int l=0,dy=y,dx=x;
while(l<w.length() && dy>0 && p.charAt(x,dy)==w.charAt(l)) { l++;dy--; }
if(l==w.length()) { dir="N";break;}
l=0;dx=x;
while(l<w.length() && dx<side && p.charAt(dx,y)==w.charAt(l)) { l++;dx++; }
if(l==w.length()) { dir="E";break;}
l=0;dx=x;dy=y;
while(l<w.length() && dy<side && p.charAt(x,dy)==w.charAt(l)) { l++;dy++; }
if(l==w.length()) { dir="S";break;}
l=0;dx=x;
while(l<w.length() && dx>0 && p.charAt(dx,y)==w.charAt(l)) { l++;dx--; }
if(l==w.length()) { dir="W";break;}
l=0;dx=x;dy=y;
while(l<w.length() && dy<side && dx<side && p.charAt(dx,dy)==w.charAt(l)) {
l++; dy++;dx++; }
if(l==w.length()) { dir="SE";break;}
l=0;dx=x;dy=y;
while(l<w.length() && dy<side && dx>0 && p.charAt(dx,dy)==w.charAt(l)) {
l++;dy++;dx--; }
if(l==w.length()) { dir="SW";break;}

Certainly inefficient use of a CPU
0
10
20
30
40
50
60
70
80
90
100
Java
CPU %
CPU1 CPU2 CPU3 CPU4
BRUTE FORCE?

IntStream is=IntStream.range(0, side*side);
is.parallel().forEach( i -> {
int x=i % side;
int y=i / side;
<do horrible code checking here..
});
}

Good use of a CPU
What about that code?
0
10
20
30
40
50
60
70
80
90
100
Java
CPU %
CPU1 CPU2 CPU3 CPU4
while( l<w.length() && dy>0
&&
p.charAt(x,dy)==w.charAt(l)) {
l++;dy--; }
BETTER?

c c e n t u r y b j
m k h l y t n e w t
t c i g a f n n o y
f d h t u s i a o v
i a w a h o h r v e
d i r n v e n y s i
g a p t u a o e x t
q f e a m o j k b o
y i c h r b y p n a
t t n v a e i z h i
When searching for
“java” we have to
make sure we don’t
run off the edge
while( l<w.length()
&& dy>0 &&
p.charAt(x,dy)==w.
charAt(l)) { l++;dy--
; }

c c e n t u r y b j
m k h l y t n e w t
t c i g a f n n o y
f d h t u s i a o v
i a w a h o h r v e
d i r n v e n y s i
g a p t u a o e x t
q f e a m o j k b o
y i c h r b y p n a
t t n v a e i z h i
Changing the data
reduces our code
Adding a empty
boarder the width
of the largest word
Means we’ll never run
off the end of the array

We can do better. private static int[][] offsets= {
{ 0 , -1 } , // N
{ 1 , -1 } , // NE
{ 1 , 0 } , // E
{ 1 , 1 } , // SE
{ 0 , 1 } , // S
{ -1 , 1 } , // SW
{ -1 , 0 } , // W
{ -1 , -1 } // NW
};
Turning the direction
problem into a data
driven one
+1-1
-1
+1

IntStream is=IntStream.range(0, (side+buffer)*(side+buffer)*8);
is.parallel().forEach( i -> {
int offsets[]=directions[i % 8];
int r = i / 8;
int x = i % r;
int y = i / r;
// loop through word matching each character
for(int i=0;i<word.length;i++) {
. . .
// move to next char in required direction by simply:
x+= offsets[0];
y+= offsets[1];
}
...

o n c i o s u c d q d v p l a a n u s t c z p a a s h x o o g t r g g f l w v d n s j z o e p e e x
i e h f q u o q p r d m r u r w e p a x a a g k m e z t u u k u h r f w f w b z j n w y r s v t m o
w g j k r g u q h x l i j f f n l y f z r z t r p x a h c n h a s c v r y m w m a d o g g z u y g k
c c v s k l m m v t p v e b z c g b i m c r z o b i r s z o s g y e l f l k q v t v r v w d v i i v
w s g x b w u l y p q e r a t e l t e j u o f a k m i q x z p h b h h l h a j k d u n j y b z z e g
o u n a l o s r m b k f j h z f m e l a u j k w o m o g i v s v c l c i u r o s j b e r o z m z l q
r x y t a k q h u t a y v m b a v z s c a k e v m t c v e b s h c b t i j k t m n c o x o c w z n y
s d a y f h n q g b i o z w s j n o j a o o n y q d b l s q f r x n h g z j u v s w q e f q t e d g
f y u i q v k o q c t o h e t o d w q n f f m o s c t v h r e n o y o g f h j w u v w u n u b a s k
z u y u f r h z h g p j g r i q m l k p e j z g h k w r g k v k k w n w x g v p l g e v c o c e j z
v n f m l b k o m q g t y z d n t s e r i i e b n w w b l q x v s i l q a e p e h r j l r e n z m l
m o n w q j s f r g k s e s k o i j d z k y p t s u d p c f e t p f g t t l s h d x f r z p c c n v
o e u a m w u b i z t b k i b o p l s u e p j z w t j x f s s v r b h j c v h m k d k j t l o z b m
x y i m m j l d c k z f k v b q r c l t q e y n e o x f z m w b d w r b g h r j b u f u g z a m c n
l j l b q q o n h n a f k h s r w p l h i m d l u s i s u l t i o g h v q u k n m h z u z u v l d u
q x y m n u m o o j o u i k i d k l w h z v t o g p u d h s n f u i m j q x m x s y g l k k p p l x
j s s e p a r y t o e x t i d b u s l n l y y t i p g d q p z e d z s j k i p a y i n x i l s y y v
y f d o h n j m n l p g m p a n q p b s u l y d a e j m x q b a f a t f q p r z t t w q n s o f e q
g k d s b j a j g v m r n j w k n c v i r i j t z a r a q r e c l t i q r v r t o a t e u t w s h w
d c x r g m r h k c n y r t t s a i t i y c n s b l f s v n v q z u f c b c g o t b w m k f e p x q
q m y x e x p p c r b v z n y b e p l h n k w i z m u h g a f m s u q m b f n j p s y r n g r r u r
v m s a a f e e p c e m k i k t n c c a i x q e z p i k c c i c h b c k l o m z y e j y x u a y u s
j q k z t o a j g z s q h p w i g f k k o n z m a g k y q u k w h e t a t y v h d q h p q u t m p s
r w x t l f g l k t h b k t j d d u x u w c k u o w j l y d l f i j h k v x x n t g g w r y n g n k
k e m g h v w v j p i p j e h g u u t p a x g i a e l m o h r h a u b d x s a t m y v l e v l n m f
j y c n d w g y i z e t o b e e b x c b z e i g n p q u i u f j r h p z o b b d k f c a r t k y q k
o k g k l l f b g b i z x j n n q h k k l w c q s g m o x y q f r m e f n w j f q h p p c z l y b k
f w p e e i d c m w m r k f a q o f k a i b y a l s j u z m s j z v c q x g m p k m j a o k k n l g
q o y r o p s w z z o v d x u k b u m y l e n x q k k l j r s f f n i k v i c s r e x j q c j a t c
c v l k l h r h k c d p l l j e b w g k t y m z d z k x n j p a q e i k f x x y l z m q h a h h y t
w l t r v c e i y w f f h j j l d w r h h e r f g j h z n b x m c l c i d l j o r b m g n j p c v b
y m d p i p i b z r c z p k p b l o q p f w p n e o d n l g v i h a p t h t f i i z f r u h v q d x
q u l e n a s k q a u a h f e n i v o i i s e k h r y n i u q g y z l o x i h j u p h a r o l s o l
Best?
This is ok when you have a “small” amount of data.
What happens when the word grid is big:
Billions of characters?
Millions of words to find?
Multidimensional?
Or the word is very long (making the buffer too expensive)?

a e k j c b a o a j
e j a x l o n d
o
d
n
v n a v a a j v i o
i c
m
e
i e t u p a a
t d a t a j a j k l
i t w i q a y a m h
n u e n x v d v g a
g o d g t f f a u i
o a s o g a g t v c
c i a c h j a i b m
PARTITIONING: Executor
node
Executor
node
Executor
node
Executor
nodeHow do you deal with words
split across the boundaries?

a e k j c b a o a j
e j a x l o n d
o
d
n
v n a v a a j v i o
i c
m
e
i e t u p a a
t d a t a j a j k l
i t w i q a y a m h
n u e n x v d v g a
g o d g t f f a u i
o a s o g a g t v c
c i a c h j a i b m
node
Executor
node
Executor
node
Executor
node
Hint: split words into small 3x3
tiles. Find tiles (map) join
together (reduce)

a e k j c b a o a j
e j a x l o n d
o
d
n
v n a v a a j v i o
i c
m
e
i e t u p a a
t d a t a j a j k l
i t w i q a y a m h
n u e n x v d v g a
g o d g t f f a u i
o a s o g a g t v c
c i a c h j a i b m
node
Executor
node
Executor
node
Executor
node
CPU

a e k j c b a o a j
e j a x l o n d
o
d
n
v n a v a a j v i o
i c
m
e
i e t u p a a
t d a t a j a j k l
i t w i q a y a m h
n u e n x v d v g a
g o d g t f f a u i
o a s o g a g t v c
c i a c h j a i b m
node
Executor
node
Executor
node
Executor
node
CPU
GPU

a e k j c b a o a j
e j a x l o n d
o
d
n
v n a v a a j v i o
i c
m
e
i e t u p a a
t d a t a j a j k l
i t w i q a y a m h
n u e n x v d v g a
g o d g t f f a u i
o a s o g a g t v c
c i a c h j a i b m
node
Executor
node
Executor
node
Executor
node
CPU
GPU
FPGA
ASIC

IBM + NVIDIA
Improving Java application
performance with GPU
exploitation is available in IBM
SDK for Java 8 and OpenJDK 9
with Eclipse Open9
Standard SE API optimisation as
well as CUDA4J API for explicit
low level control
+

GPU’s don’t work like CPU’s
They want their data in different forms
They behave differently
You’ll have to think differently too

if(a) {
// do this
} else {
// do this instead
}
On a standard CPU
Each thread runs in parallel
With its own ’program counter’
Independently.if(a) {
// do this
} else {
// do this instead
}
Step 1
Step 1
Step 2
Step 2

if(a) {
// do this
} else {
// do this instead
}
On a GPU
Each thread runs in sync
sharing a program counter
The length of time for the
program to complete is
a factor of all the
paths traveled
GPU’s are best when
data driven!
if(a) {
// do this
} else {
// do this instead
}
Step 1
Step 1
Step 2
Step 3

PC Thread 1 PC Thread 2 PC Thread 3 PC Thread 4 PC Thread 5
Thing 1 Thing 1 Thing 1 Thing 1 Thing 1
Thing 2
Thing 3
Thing 4
Thing 5 Thing 5
Thing 6 Thing 6 Thing 6 Thing 6
PC Thread 1 Thread 2 Thread 3 Thread 4 Thread 5
Thing 1 Thing 1 Thing 1 Thing 1 Thing 1
Thing 2
Thing 3
Thing 4
Thing 5 Thing 5
Thing 6 Thing 6 Thing 6 Thing 6
GPU
CPU

o n c i o s u c d q d v p l a a n u s t c z p a a s h x o o g t r g g f l w v d n s j z o e p e e x
i e h f q u o q p r d m r u r w e p a x a a g k m e z t u u k u h r f w f w b z j n w y r s v t m o
w g j k r g u q h x l i j f f n l y f z r z t r p x a h c n h a s c v r y m w m a d o g g z u y g k
c c v s k l m m v t p v e b z c g b i m c r z o b i r s z o s g y e l f l k q v t v r v w d v i i v
w s g x b w u l y p q e r a t e l t e j u o f a k m i q x z p h b h h l h a j k d u n j y b z z e g
o u n a l o s r m b k f j h z f m e l a u j k w o m o g i v s v c l c i u r o s j b e r o z m z l q
r x y t a k q h u t a y v m b a v z s c a k e v m t c v e b s h c b t i j k t m n c o x o c w z n y
s d a y f h n q g b i o z w s j n o j a o o n y q d b l s q f r x n h g z j u v s w q e f q t e d g
f y u i q v k o q c t o h e t o d w q n f f m o s c t v h r e n o y o g f h j w u v w u n u b a s k
z u y u f r h z h g p j g r i q m l k p e j z g h k w r g k v k k w n w x g v p l g e v c o c e j z
v n f m l b k o m q g t y z d n t s e r i i e b n w w b l q x v s i l q a e p e h r j l r e n z m l
m o n w q j s f r g k s e s k o i j d z k y p t s u d p c f e t p f g t t l s h d x f r z p c c n v
o e u a m w u b i z t b k i b o p l s u e p j z w t j x f s s v r b h j c v h m k d k j t l o z b m
x y i m m j l d c k z f k v b q r c l t q e y n e o x f z m w b d w r b g h r j b u f u g z a m c n
l j l b q q o n h n a f k h s r w p l h i m d l u s i s u l t i o g h v q u k n m h z u z u v l d u
q x y m n u m o o j o u i k i d k l w h z v t o g p u d h s n f u i m j q x m x s y g l k k p p l x
j s s e p a r y t o e x t i d b u s l n l y y t i p g d q p z e d z s j k i p a y i n x i l s y y v
y f d o h n j m n l p g m p a n q p b s u l y d a e j m x q b a f a t f q p r z t t w q n s o f e q
g k d s b j a j g v m r n j w k n c v i r i j t z a r a q r e c l t i q r v r t o a t e u t w s h w
d c x r g m r h k c n y r t t s a i t i y c n s b l f s v n v q z u f c b c g o t b w m k f e p x q
q m y x e x p p c r b v z n y b e p l h n k w i z m u h g a f m s u q m b f n j p s y r n g r r u r
v m s a a f e e p c e m k i k t n c c a i x q e z p i k c c i c h b c k l o m z y e j y x u a y u s
j q k z t o a j g z s q h p w i g f k k o n z m a g k y q u k w h e t a t y v h d q h p q u t m p s
r w x t l f g l k t h b k t j d d u x u w c k u o w j l y d l f i j h k v x x n t g g w r y n g n k
k e m g h v w v j p i p j e h g u u t p a x g i a e l m o h r h a u b d x s a t m y v l e v l n m f
j y c n d w g y i z e t o b e e b x c b z e i g n p q u i u f j r h p z o b b d k f c a r t k y q k
o k g k l l f b g b i z x j n n q h k k l w c q s g m o x y q f r m e f n w j f q h p p c z l y b k
f w p e e i d c m w m r k f a q o f k a i b y a l s j u z m s j z v c q x g m p k m j a o k k n l g
q o y r o p s w z z o v d x u k b u m y l e n x q k k l j r s f f n i k v i c s r e x j q c j a t c
c v l k l h r h k c d p l l j e b w g k t y m z d z k x n j p a q e i k f x x y l z m q h a h h y t
w l t r v c e i y w f f h j j l d w r h h e r f g j h z n b x m c l c i d l j o r b m g n j p c v b
y m d p i p i b z r c z p k p b l o q p f w p n e o d n l g v i h a p t h t f i i z f r u h v q d x
q u l e n a s k q a u a h f e n i v o i i s e k h r y n i u q g y z l o x i h j u p h a r o l s o l
What about when you don’t know the words your searching for?
Do you create a list of every possible word?

NEURAL:
a e k j c b a o a j
e j a x l o n d
o
d
n
v n a v a a j v i o
i c
m
e
i e t u p a a
t d a t a j a j k l
i t w i q a y a m h
n u e n x v d v g a
g o d g t f f a u i
o a s o g a g t v c
c i a c h j a i b m
Teach a Neural Net
about how words are
constructed.
Then let it search the grid
Then work out which words
are ‘real’
Don’t think that’s possible?

http://karpathy.github.io/2015/05/21/rnn-effectiveness/

SYNAPSE:
A program to develop a
neuromorphic processor that is a
new kind of cognitive computer
Designed to simulate the neurones
and dendrites of the brain for low
power efficient operation

Event driven, Non Von Neumann Neural Network.
Neural Nets want their data in different forms
They behave differently
You’ll have to think differently too

Now it gets even stranger..

SEARCH
In 1996 a search algorithm was
defined by Lov Grover. This
algorithm can transform the
problem into an O(√N) search.
On a traditional computer this
search problem is solved in no fewer
than O(N) evaluations

0 - ish
Z Rotation
or ‘phase’
1 - ish
Y Rotation or ‘pha
X Rotation or ‘phase’

QBIT
Microwave resonators

qubitbit
1
0
SEARCH

r c e n t u r y l m
y q h m y t n e w t
j x v g f a s r h h
f u r t u k h o u q
y a m a h o c e k n
s b r p v e n c a t
a y g e u a j e a d
h z g a m o j i p b
h z a e r b y a n n
d m t f g e i v e i
“Java”
Try 1 3,5 -> NE

r c e n t u r y l m
y q h m y t n e w t
j x v g f a s r h h
f u r t u k h o u q
y a m a h o c e k n
s b r p v e n c a t
a y g e u a j e a d
h z g a m o j i p b
h z a e r b y a n n
d m t f g e i v e i
“Java”
Try 1 3,5 -> NE
No – try again

r c e n t u r y l m
y q h m y t n e w t
j x v g f a s r h h
f u r t u k h o u q
y a m a h o c e k n
s b r p v e n c a t
a y g e u a j e a d
h z g a m o j i p b
h z a e r b y a n n
d m t f g e i v e i
“Java”
Try 2 4,4 -> N

r c e n t u r y l m
y q h m y t n e w t
j x v g f a s r h h
f u r t u k h o u q
y a m a h o c e k n
s b r p v e n c a t
a y g e u a j e a d
h z g a m o j i p b
h z a e r b y a n n
d m t f g e i v e i
“Java”
Try 2 4,4 -> N
No – try again

r c e n t u r y l m
y q h m y t n e w t
j x v g f a s r h h
f u r t u k h o u q
y a m a h o c e k n
s b r p v e n c a t
a y g e u a j e a d
h z g a m o j i p b
h z a e r b y a n n
d m t f g e i v e i
“Java”
Try 3 6,3 -> NW

r c e n t u r y l m
y q h m y t n e w t
j x v g f a s r h h
f u r t u k h o u q
y a m a h o c e k n
s b r p v e n c a t
a y g e u a j e a d
h z g a m o j i p b
h z a e r b y a n n
d m t f g e i v e i
“Java”
Try 3 6,3 -> NW
No – try again

QUANTUM:
a e k j c b a o a j
l g m e e t u p a p
l n a v a a j v i o
p c
m
e
i e t u p a a
r d a t a j a j k l
u t w i q a y a m h
d u e n x v d v g a
j o d g t f f a u i
a a s o g a g t v c
z i a c h j a i b m
www.research.ibm.com/ibm-q/
Real life demo?

Quantum Computers can and will solve linear equations
break cryptographic systems or model new medicines
In times that are a fraction of what existing computers can
achieve now.
Word searches are easy. But you present the data differently
and get a statistical response.
No more 0&1’s

The JVM design means that we can easily
imagine running Java on new forms of processors. It may
not end up being todays Java but it will be close
The challenge is that you have to change how you think!
And as for Cloud?
Containers, fast startups, small memory footprints,
Jit as a Sevice?
That’s happening today. Think about tomorrow.

OPPORTUNITY:
Data flows from every device,
replacing guessing and
approximations with precise
information. Yet 80% of this
data is unstructured; therefore,
invisible to computers and of
limited use to business.
HEALTHCARE DATA GOVERNMENT & EDUCATION DATA
99% 88% 94% 84%
Healthcare data comes from
sources such as:
Government & education data
comes from sources such as:
Patient
Sensors
Electronic
Medical
Records
Test
Results
Vehicle Fleet
Sensors
Traffic
Sensors
Student
Evaluations
UTILITIES DATA MEDIA DATA
93% 84% 97% 82%
Utilities data comes from sources
such as:
Media data comes from sources
such as:
Utility
Sensors
Employee
Sensors
Location
Data
Video
and Film
Images Audio
By 2020,
of new information will
be created every
second for every
human being on
the planet.
growth by 2017 unstructured growth by 2017 unstructured
1.7 MB growth by 2017 unstructured growth by 2017 unstructured

The world is
being reinvented
in code. Java code.
HOW, AND WHY NOW?

Computing is
entering a new
cognitive era.
What do you Think
when you solve a
problem?
HOW, AND WHY NOW?

JVMCON Java in the 21st Century: are you thinking far enough ahead?

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