Jvm memory model

JVM
Memory Model
The examples on Github
https://github.com/yoavaa/jvm-memory-model

Anomalies
• How long does it take to count to 100?
• How long does it take to append to a list?
To sort a list?
• How long does it take to append to a
vector? To sort a vector?
Code: Com.wix.JIT

Dynamic vs Static Compilation
• Static Compilation
– “ahead-of-time” (AOT) compilation
– Source code -> Native executable
– Compiles before executing
• Dynamic compiler (JIT)
– “just-in-time” (JIT) compilation
– Source -> bytecode -> interpreter -> JITed
– Most of compilation happens during executing

JIT Compilation
• Aggressive optimistic optimizations
– Through extensive usage of profiling info
– Limited budget (CPU, Memory)
– Startup speed may suffer
• The JIT
– Compiles bytecode when needed
– Maybe immediately before execution?
– Maybe never?

JVM JIT Compilation
• Eventually JITs bytecode
– Based on profiling
– After 10,000 cycles, again after 20,000 cycles
• Profiling allows focused code-gen
• Profiling allows better code-gen
– Inline what’s hot
– Loop unrolling, range-check elimination, etc.
– Branch prediction, spill-code-gen, scheduling

JVM JIT Compilation
• JVM applications operate in mixed mode
• Interpreted
– Bytecode-walking
– Artificial stack machine
• Compiled
– Direct native operations
– Native register machine

Inlining
int addAll(int max) {
int accum = 0;
for (int i=0; i < max; i++) {
accum = add(accum, i);
}
return accum;
}
int add(int a, int b) {
return a+b;
}
int addAll(int max) {
int accum = 0;
for (int i=0; i < max; i++) {
accum = accum + i;
}
return accum;
}

Loop unrolling
public void foo(int[] arr, int a) {
for (int i=0; i<arr.length; i++) {
arr[i] += a;
}
}
public void foo(int[] arr, int a) {
int limit = arr.length / 4;
for (int i=0; i<limit ; i++){
arr[4*i] += a; arr[4*i+1] += a;
arr[4*i+2] += a; arr[4*i+3] += a;
}
for (int i=limit*4; i<arr.length; i++) {
arr[i] += a;
}
}

Escape Analysis
public int m1() {
Pair p = new Pair(1,2);
return m2(p);
}
public int m2(Pair p) {
return p.first + m3(p);
}
public int m3(Pair p) {
return p.second;
}
// after deep inlining
public int m1() {
Pair p = new Pair(1,2);
return p.first + p.second;
}
// optimized version
public int m1() {
return 3;
}

Monitoring Jit
• Info about compiled methods
– -XX:+PrintCompilation
• Info about inlining
– -xx:+PrintInlining
– Requires also -XX:+UnlockDiagnosticVMOptions
• Print the assembly code
– -XX:+PrintAssembly
– Also requires also -
XX:+UnlockDiagnosticVMOptions
– On Mac OS requires adding hsdis-amd64.dylib
to the LD_LIBRARY_PATH environment variable.

Challenge
• Rerun the benchmarks, this time using
1. -XX:+PrintCompilation
2. -XX:+UnlockDiagnosticVMOptions -XX:+PrintInlining

JVM Memory
The Java Memory Model

Java Memory Model
• The Java Memory Model (JMM) describes
how threads in the Java (Scala)
Programming language interact through
memory.
• Provides sequential consistency for
data race free programs.

Instruction Reordering
• Program Order
int a=1;
int b=2;
int c=3;
int d=4;
int e = a + b;
int f = c - d;
• Execution Order
int d=4;
int c=3;
int f = c - d;
int b=2;
int a=1;
int e = a + b;

Anomaly
• Two threads running
• What will be the result?
i=1, j=1
i=0, j=1
i=1, j=0
i=0, j=0
x=y=0
j=y
x=1
i=x
y=1
Thread 1 Thread 2

Let’s Check
• Let’s build the scenario
val t1 = new Thread(new Runnable {
def run() {
// sleep a little to add some uncertainty
Thread.sleep(1)
x=1
j=y
}
})
• Then run it a few times
• Do we see the anomaly?
Code: Com.wix.MemoryModelOrdering

Happens Before Ordering
• Defines constraints on instruction reordering
• Assignment dependency within a single
thread
• Volatile field reads are after writes
– For non volatile field, this is not necessarily the
case!
• A monitor release
• A matching monitor acquire
• Happens Before ordering is transitive

Anomaly
• Let’s see how far we can count in 100 milli-seconds
var running = true
• Let thread 1 count
var count = 0
while (running)
count = count + 1
println(count)
• Let thread 2 signal thread 1 to stop
Thread.sleep(100)
running = false
println("thread 2 set running to false”)
Code: Com.wix.Visability
jps, jstack

Volatile
• Compilers can reorder instructions
• Compilers can keep values in registers
• Processors can reorder instructions
• Values may be in different caching levels
and not synced to main memory
• JMM is designed for aggressive
optimizations

Volatile
• Modern processor caches
Core 1 Core 2 Core 3 Core 4
L1 L1 L1 L1
L2 L2 L2 L2
L3 L3
Main Memory ~65 ns (DRAM)
~15 ns (40-45 cycles)
~3 ns (10-12 cycles)
~1 ns (3-4 cycles)
< 1 ns

Volatile
• Volatile instructs the compiler and processor
to sync the value to main memory on every
access
– Does not utilize the L1, L2 or L3 cache
• Volatile reads / writes cannot be reordered
• Volatile long and doubles are atomic
– Long and double types are over 32bit – the
processor operates on 32bit atomicity by default.

Resolve the Anomaly
• Let’s see how far we can count in 100 milli-seconds
@volatile var running = true
• Let thread 1 count
var count = 0
while (running)
count = count + 1
println(count)
• Let thread 2 signal thread 1 to stop
Thread.sleep(100)
running = false
println("thread 2 set running to false”)

Anomaly
• Let’s count to 10,000
• But lets use 10 threads, each adding 1,000 to
our count
var count = 0
• Each of the 10 threads does
for (i <- 1 to 1000)
count = count + 1
• What did we get?
Code: Com.wix.Sync101, counter, volatile

Synchronization
• Let’s have another look at the assignment
count = count + 1
count = count + 1
• Is this a single instruction?
• javap
– javap <class> - Print the class signature
– javap -c <class> - Print the class bytecode
javap

Synchronization
• The bytecode for count = count + 1
14: getfield #38 // Field scala/runtime/IntRef.elem:I
17: iconst_1
18: iadd
19: putfield #38 // Field scala/runtime/IntRef.elem:I

Synchronization
• The bytecode for count = count + 1
// Read the current counter value from field 38
// and add it to the stack
14: getfield #38 // Field scala/runtime/IntRef.elem:I
// Add 1 to the stack
17: iconst_1
// Add the first two stack elements as integers,
// and put the result in the stack
18: iadd
// set field 38 to the current top element of the stack
// assuming it is an integer
19: putfield #38 // Field scala/runtime/IntRef.elem:I

Synchronization Tools
Actions by
thread 1
Thread 1
“release”
monitor
Thread 2
“acquire”
monitor
Actions by
thread 2
Happens-before

• Synchronization tools allow grouping
instructions as if “one atomic instruction”
– Only one thread can perform the code at a time
• Some tools
– Synchronized
– ReentrantLock
– CountDownLatch
– Semaphore
– ReentrantReadWriteLock

• Simplest tools – synchronized
// for each thread
for (i <- 1 to 1000)
synchronized {
count = count + 1
}
• Works relative to ‘this’
Code: Com.wix.Sync101, lock counter - synchronized

• Using ReentrantLock
// before the threads
val lock = new ReentrantLock()
// for each thread
for (i <- 1 to 1000) {
lock.lock()
try {
count = count + 1
}
finally {
lock.unlock()
}
}
Code: Com.wix.Sync101, lock counter – re-entrant lock

Atomic Operations
• Containers for simple values or references
with atomic operations
• getAndIncrement
• getAndDecrement
• getAndAdd

Atomic Operations
• All are based on compareAndSwap
– From the unsafe class
– Used to implement spin-locks

Atomic Operations
• Spin Lock
public final int getAndIncrement() {
for (;;) {
int current = get();
int next = current + 1;
if (compareAndSet(current, next))
return current;
}
}
}
public final boolean compareAndSet(int expect, int update) {
return unsafe.compareAndSwapInt(this,
valueOffset, expect, update);
}
Code: Com.wix.Sync101, atomic counter

References
• The examples on Github
https://github.com/yoavaa/jvm-memory-model

JVM Memory
Memory allocation of a JVM
process

Java Memory
• Java runs as a single process
• Each process allocates memory
– Process Heap
• JVM creates a Java Heap
– Part of the process Heap
OS Memory (RAM)
Process Heap
Java Object Heap
Everything else…

Java Process Heap
• On a 32bit Java
– Process heap limited to ~2GB
• If 2GB is the max for a process
– Setting the Java heap to 1800MB – not a good idea
– Using –Xmx1800m –Xms1800m
– Leaves small room for anything else
• On a 64bit Java, this is not an issue

Java Object Heap
• Stores Java Objects
– Instances of classes, primitives and references
• Pre-allocated large blocks of memory
– No fragmentation
– Allocation of small blocks of memory is very fast
• NullPointerException vs. General Access Fault
– NPE is a runtime exception
– GAF crash the process

Java Object Heap
• Tuning the Java Heap
– Only controls the Object Heap, not the Process Heap
• -Xmx – specifies maximum size of the heap
• -Xms – specifies the initial size of the heap
• -XX:MinHeapFreeRatio – how much to allocate
– Default to 40% - allocate another 40% each time
• -XX:MaxHeapFreeRatio – when to free memory
– Default to 70% - when 70% of memory is free,
release memory to the OS

Classic Memory Leak in C
• User does the memory management
void service(int n, char** names) {
for (int i = 0; i < n; i++) {
char* buf = (char*) malloc(strlen(names[i]));
strncpy(buf, names[i], strlen(names[i]));
}
// memory leaked here
}
• User is responsible for calling free()
• User is vulnerable to
– Dangling pointers
– Double frees

Garbage Collection
• Find and reclaim unreachable objects
• Not reachable from the application roots
– thread stacks, static fields, registers
• Traces the heap starting at the roots. Anything
not visited is unreachable and garbage collected
• 80-98% of newly allocated are extremely short
lived. With Scala, the ratio of short lived objects is even
larger

Garbage Collection
Available Collectors (algorithms)
• Serial Collector
• Parallel Collector
• Parallel Compacting Collector
• Concurrent Mark Sweep Collector
• G1 Collector
• Which one is the default on your machine?
java -XX:+PrintCommandLineFlags -version

Memory Generations
• Applies to all collectors except G1
• All new objects are created at the Young Generation, Eden space
• Moved to Old Generation if they survive one or more minor GC
• Survivor Spaces – 2 of them, used during the GC algorithm
• PermGen holds the class files (the bytecode)
Java Object Heap
Young Generation
Eden Space
Tenured (Old) Generation
Survivor Spaces
PermGen

Types of Collectors
• The G1 collector does not use generations
– Heap divided into ~2000 regions
– Objects are moving between regions during collection
Young
Generation
Tenured (Old)
Generation
old unusedyoung
old
unused
old
old
unused
young old
old unused
young old
old young
old old

Everything else
• Code Generation
• Socket Buffers
• Thread Stacks
• Direct Memory Space
OS Memory (RAM)
Process Heap
Java Object Heap
Everything else…
• JNI Code
• Garbage Collection
• JNI Allocated Memory

Thread Stack
• Each thread has a separate memory space
called “thread stack”
• Configured by –Xss
• Default value depends on OS / JVM
– Defaults around 1M - 2M
• As the number of threads increase, the memory
usage increases

Monitoring Memory Usage
Using Java command line args
• -verbose:gc – report each GC event
• -Xloggc:file – report each GC event to file
• -XX:+PrintGCDetails – print GC output
• -XX:+PrintGCTimeStamps –
print GC with timestamps
• -XX:+HeapDumpOnOutOfMemoryError –
create a dump file on out of memory
– The process is suspended while writing the dump file

Using JDK command line tools
• jps to get the pid of java processes
• jinfo to get information about a running java
process – VM flags and system properties
• jmap to take a memory dump
• jhat to view a memory dump
• Jstat to view different stats about the jvm

Using JDK GUI tools
• jconsole
– Monitor a live process
– JMX console
• jvisualvm
– Monitor a live process (more detailed compared to
jconsole)
– Take a memory dump
– View a memory dump file
– Profile a process
– Lots of other great stuff

Jvm memory model

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