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Optimizing your Java Applications for multi-core

hardware

Prashanth K Nageshappaprashanth.k.n@in.ibm.com

Java TechnologiesIBM

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Agenda

• Evolution of Processor Architecture

• Why should I care?

• Think about Scalability

• How to exploit

• Parallelism in Java

• JVM optimizations for multi-core scalability

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As The World Gets Smarter, Demands On IT Will Grow

Smart energy grids

Smart healthcare

Smart food systems

Intelligent oil field technologies

Smart supply chains

Smart retail

•IT infrastructure must grow to meet these demands

global scope, processing scale, efficiency

Digital data is projected to grow tenfold from 2007

to 2011.

Devices will be connected to

the internet by 2011

1 Trillion 70¢ per $1Global trading

systems are under extreme stress,

handling billions of market data

messages each day

25 Billion70% on average is

spent on maintaining current

IT infrastructure versus adding new

capabilities

10x

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Hardware Trends

Increasing transistor density

Clock Speed leveling off

More number of cores

Non-Uniform Memory Access

Main memory getting larger

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In 2010 POWER Systems Brings Massive Parallelism

2001180 nm

2004130 nm

200765 nm

201045 nm

POWER7™ 4 threads/core 8 cores/chip

32 sockets/server

1024 threads

POWER6™ 2 threads/core 2 cores/chip

32 sockets/server

128 threads

POWER5™ 2 threads/core 2 cores/chip

32 sockets/server

128 threads

POWER4™ 1 thread/core 2 cores/chip

16 sockets/server

32 threads

Thre

ads

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Agenda

• Evolution of Processor Architecture

• Why should I care?

• Think about Scalability

• How to exploit

• Parallelism in Java

• JVM optimizations for multi-core scalability

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Why should I care?

Your application may be re-usedBetter performance

Better leverage additional resourcesCores, hardware threads, memory etc

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Think about scalability

• Serial bottlenecks inhibit scalability

• Organize your application into parallel tasks– Consider TaskExecutor API– Too many threads can be just as bad as too few

• Do not rely on JVM to discover opportunities– No automatic parallelization – Java class libraries do not exploit vector

processor capabilities

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Think about scalability

• Load imbalance– Workload not evenly distributed

– Consider breaking large tasks into smaller ones

– Change serial algorithms to parallel ones

• Tracing and I/O– Bottleneck unless infrequent updates or log is

striped (RAID)

– Blocking disk/console I/O inhibit scalability

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Synchronization and locking

• J9's Three-tiered locking– Spin– Yield– OS

• Avoid synchronization in static methods• Consider breaking long synchronized blocks into

several smaller ones– May be bad if results in many context switches

• Java Lock Monitor (JLM) tool can helphttp://perfinsp.sourceforge.net/jlm.html

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Synchronization and locking

• Volatiles– Compiler will not cache the value– Creates memory barrier

• Avoid synchronized container classes– Building scalable data structures is

difficult– Use java.util.concurrent (j/u/c)

• Non-blocking object access– Possible with j/u/c

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Agenda

• Evolution of Processor Architecture

• Why should I care?

• Think about Scalability

• How to exploit

• Parallelism in Java

• JVM optimizations for multi-core scalability

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java.util.concurrent package

• Introduced in Java SE 5 • Alternative strong synchronization• Lighter weight, better scalability

– Comparing to intrinsic locks

• java.util.concurrent.atomic.*• java.util.concurrent.locks.*• ConcurrentCollections• Synchronizers• TaskExecutor

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j/u/c/atomic.*

• Atomic primitives

• Strong form of synchronization

– But does not use lock – non blocking

– Exploit atomic instructions such as compare-and-swap in hardware

• Supports compounded actions• AtomicLongFieldUpdater• AtomicMarkableReference• AtomicReference• AtomicReferenceArray• AtomicReferenceFieldUpdater• AtomicStampedReference

• AtomicBoolean• AtomicInteger• AtomicIntegerArray• AtomicIntegerFieldUpdater• AtomicLong• AtomicLongArray

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j/u/c/atomic.*

• Getter and setters– get

– set

– lazySet

• Updates– getAndSet

– getAndAdd/getAndIncrement/getAndDecrement

– addAndGet/incrementAndGet/decrementAndGet

• CAS– compareAndSet/weakCompareAndSet

• Conversions– toString, intValue, longValue, floatValue, doubleValue

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j/u/c/locks.*

• Problems with intrinsic locks– Impossible to back off from a lock attempt

• Deadlock

– Lack of features• Read vs write• Fairness policies

– Block-structured• Must lock and release in the same method

• j/u/c/locks– Greater flexibility for locks and conditions

• Non-block-structured

– Provides reader-writer locks• Why block other readers?• Better scalability

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j/u/c/locks.*

Interfaces:– Condition

– Lock

– ReadWriteLock

Classes:– ReentrantLock

– ReentrantReadWriteLock

– LockSupport

– AbstractQueuedSynchronizer

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j/u/c.* - Concurrent Collections

Concurrent, thread safe implementations of several collections

HashMap → ConcurrentHashMap

TreeMap → ConcurrentSkipListMap

ArrayList → CopyOnWriteArrayList

ArraySet → CopyOnWriteArraySet

Queues → ConcurrentLinkedQueue or one of the blocking queues

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Strains on the VM

• Excessive use of temporary memory can lead to increased garbage collector activity– Stop the world GC pauses the application

• Excessive class loading– Updating class hierarchy

– Invalidating JIT optimizations

– Consider creating a “startup” phase

• Transitions between Java and native code– VM access lock

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Memory Footprint

• Little control over object allocation in Java– Small short lived objects are easier to cache

– Large long lived objects likely to cause cache misses

– Memory Analysis Tool (MAT) can help

• Consider using large pages for TLB misses– -Xlp, requires OS support

• Tune your heap settings– Heap lock contention with flat heap

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Affinitizing JVMs

• Can exploit cache hierarchy on a subset of cores

• JVM working set can fit within the physical memory of a single node in a NUMA system

• Linux: taskset, numactl

• Windows: start

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Is my application scalable?

• Low CPU means resources are not maximized– Evaluate if application has too few/many threads

– Locks and synchronization

– Network connections, I/O

– Thrashing • working set is too large for physical memory

• High CPU is generally good, as long as resources are spent in application threads, doing meaningful work

• Evaluate where time is being spent– Garbage collection

– VM/JIT

– OS Kernel functions

– Other processes

• Tune, tune, tune

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Write Once, Tune Everywhere

• HealthCenter, GCMV, MAThttp://www.ibm.com/developerworks/java/jdk/tools/

• Dependence on operating System– Memory allocation– Socket layer

• Tune for hardware capabilities– How many cores? How much memory?– What is the limit on network access?– Are there storage bottlenecks?

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Agenda

• Evolution of Processor Architecture

• Why should I care?

• Think about Scalability

• How to exploit

• Parallelism in Java

• JVM optimizations for multi-core scalability

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IBM Java Execution Model is Built for Parallelism

JIT Compiler

Garbage Collector

Application Threads

• Generates high performance code for application threads• Customizes execution to underlying hardware• Optimizes locking performance• Asynchronous compilation thread

• Java software threads are executed on multiple hardware threads• Thread safe libraries with scalable concurrency support for parallel programming

• Manages memory on behalf of the application• Must balance throughput against observed pauses• Exploits many multiple hardware threads

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Configurable Garbage Collection policies

Multiple policies to match varying user requirements– Pause time, Throughput, Memory footprint and GC overhead

All modes exploit parallel execution– Dynamic adaptation to number of available hardware cores &

threads– GC scalability independent from user application scalability– Very low overhead (<3%) on typical workloads

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How do GC policies compare? - optthruput

Time

Thread 1

Thread 2

Thread 3

Thread n

GCJava

Optimize Throughput•Highly parallel GC + streamlined application thread execution•May cause longer pause times

-Xgcpolicy:optthruput

Picture is only illustrative and doesn’t reflect any particular real-life application. The purpose is to show theoretical differences in pause times between GC policies.

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How do GC policies compare? - optavgpause

Time

GCJava

Concurrent Tracing

Optimize Pause Time•GC cleans up concurrently with application thread execution•Sacrifice some throughput to reduce average pause times

-Xgcpolicy:optavgpause

Picture is only illustrative and doesn’t reflect any particular real-life application. The purpose is to show theoretical differences in pause times between GC policies.

Thread 1

Thread 2

Thread 3

Thread n

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How do GC policies compare? - gencon

Time

Global GCJava

Concurrent Tracing

Scavenge GC

Balanced•Clean up many short-lived objects concurrent with application threads•Some pauses needed to collect longer-lived objects

-Xgcpolicy:gencon

Picture is only illustrative and doesn’t reflect any particular real-life application. The purpose is to show theoretical differences in pause times between GC policies.

Thread 1

Thread 2

Thread 3

Thread n

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How do GC policies compare? - subpools

• Uses multiple free lists•Tries to predict the size of future allocation requests based on earlier allocation requests. •Recreates free lists at the end of each GC based on these predictions. •While allocating objects on the heap, free chunks are chosen using a “best fit” method, as against the “first fit” method used in other algorithms.•Concurrent marking is disabled

Scalable•Scalable GC focused on the larger multiprocessor machines•Improved object allocation algorithm•May not be appropriate for small-to-midsize configurations

–Xgcpolicy:subpool

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JVM optimizations for multi-core scalability

Lock removal across JVM and class libraries

java.util.concurrent package optimizations

Better working set for cache efficiency

Stack allocation

Remove/optimize synchronization

Thread local storage for send/receive buffers

Non-blocking containers

Asynch JIT compilation on a separate thread

Right-sized application runtimes

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Merci

Grazie

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Thank You

Questions?Questions?Email: Email: prashanth.k.n@in.ibm.comprashanth.k.n@in.ibm.com

http://www.ibm.com/developerworks/java/

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© IBM Corporation 2010. All Rights Reserved.

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