SlideShare a Scribd company logo
THREADS & CONCURRENCY
Lecture 23– CS2110 – Fall 2018
Prelim room assignments (not yet posted
elsewhere)
5:30. URHG01: netids lac326 to rzt4
5:30. BKL200: netids sa2229 to zz632
plus all conflicts moving from 7:30 to 5:30 exam
--------------------------------
7:30. URHG01: aa2277 to gyz2
7:30. BKL200: hcm58 to ky356
plus all conflicts moving from 5:30 to 7:30 exam
There will be a homework on concurrency.
2
CPU Central Processing Unit. Simplified
view
The CPU is the part of the
computer that executes
instructions.
Java: x= x + 2;
Suppose variable x is at
Memory location 800,
Instructions at 10
Machine language:
10: load register 1, 800
11: Add register 1, 2
12: Store register 1, 800
3
Basic uniprocessor-CPU computer.
Black lines indicate data flow, red
lines indicate control flow
From wikipedia
Part of Activity Monitor in Gries’s laptop
4
>100 processes are competing for time. Here’s some of them:
Clock rate
 Clock rate “frequency at which CPU is
running”
Higher the clock rate, the faster
instructions
are executed.
 First CPUs: 5-10 Hz
(cycles per second)
 Today MacBook Pro 3.5GHz
 Your OS can control the
clock rate, slow it down when
idle, speed up when more
5
Why multicore?
 Moore’s Law: Computer speeds and memory
densities nearly double each year
6
But a fast computer runs hot
 Power dissipation rises as square of the clock
rate
 Chips were heading toward melting down!
 Put more CPUs on a chip:
with four CPUs on one
chip, even if we run each at
half speed we can perform
more overall computations!
7
Today: Not one CPU but many
Processing Unit is called a core.
 Modern computers have “multiple cores” (processing
units)
 Instead of a single CPU (central processing unit) on
the chip 5-10 common. Intel has prototypes with 80!
 We often run many programs at the same time
 Even with a single core (processing unit), your program
may have more than one thing “to do” at a time
 Argues for having a way to do many things at once
8
Many programs. Each can have several
“threads of execution”
We often run many programs at the same time
And each program may have several “threads of
execution”
9
Example, in a Paint program,
when you click the pencil tool,
a new thread of execution is
started to call the method to
process it:
Main GUI thread
Process pencil
click
Programming a Cluster...
10
• Sometimes you want to write a
program that is executed on
many machines!
• Atlas Cluster (at Cornell):
• 768 cores
• 1536 GB RAM
• 24 TB Storage
• 96 NICs (Network Interface
Controller)
Programming a Cluster...
11
Programs like those that simulate
weather have a big array of
points,
At each step of simulation,
calculates whether at each point
based on info at surrounding
points.
Each is on a separate processor.
Many processes are executed
simultaneously on your computer
12
• Operating system provides support for multiple
“processes”
• Usually fewer processors than processes
• Processes are an abstraction:
at hardware level, lots of multitasking
–memory subsystem
–video controller
–buses
–instruction prefetching
Concurrency
 Concurrency refers to a single program in which several
processes, called threads, are running simultaneously
 Special problems arise
 They reference the same data and can interfere with
each other, e.g. one process modifies a complex
structure like a heap while another is trying to read it
 CS2110: we focus on two main issues:
 Race conditions
 Deadlock
13
Race conditions
 A “race condition” arises if two or more processes
access the same variables or objects concurrently and
at least one does updates
 Example: Processes t1 and t2 x= x + 1; for some
static global x.
Process t1 Process t2
… ...
x= x + 1; x= x + 1;
But x= x+1; is not an “atomic action”: it takes several steps
14
Race conditions
 LOAD x
 ADD 1
 STORE x
 ...
 LOAD x
 ADD 1
 STORE x
Thread t1 Thread t2
15
 Suppose x is initially 5
 ... after finishing, x = 6! We “lost” an update
Race conditions
 Typical race condition: two processes wanting to change
a stack at the same time. Or make conflicting changes
to a database at the same time.
 Race conditions are bad news
 Race conditions can cause many kinds of bugs, not
just the example we see here!
 Common cause for “blue screens”: null pointer
exceptions, damaged data structures
 Concurrency makes proving programs correct much
harder!
16
Deadlock
 To prevent race conditions, one often requires a process
to “acquire” resources before accessing them, and only
one process can “acquire” a given resource at a time.
 Examples of resources are:
 A file to be read
 An object that maintains a stack, a linked list, a hash
table, etc.
 But if processes have to acquire two or more resources
at the same time in order to do their work, deadlock can
occur. This is the subject of the next slides.
17
Dining philosopher problem
18
Five philosophers
sitting at a table.
Each repeatedly
does this:
1. think
2. eat
What do they
eat?
spaghetti.
Need TWO forks
to eat spaghetti!
Dining philosopher problem
19
Each does
repeatedly :
1. think
2. eat (2 forks)
eat is then:
pick up left fork
pick up right fork
pick up food, eat
put down left fork
put down rght fork
At one point,
they all pick up
their left forks
DEADLOCK!
Dining philosopher problem
20
Simple solution to
deadlock:
Number the forks. Pick
up smaller one first
1. think
2. eat (2 forks)
eat is then:
pick up smaller fork
pick up bigger fork
pick up food, eat
put down bigger fork
put down smallerfork
1
2
4
3
5
Java: What is a Thread?
 A separate “execution” that runs within a single
program and can perform a computational task
independently and concurrently with other threads
 Many applications do their work in just a single thread:
the one that called main() at startup
 But there may still be extra threads...
 ... Garbage collection runs in a “background” thread
 GUIs have a separate thread that listens for events
and “dispatches” calls to methods to process them
 Today: learn to create new threads of our own in Java
21
Thread
 A thread is an object that “independently computes”
 Needs to be created, like any object
 Then “started” --causes some method to be called. It
runs side by side with other threads in the same
program; they see the same global data
 The actual executions could occur on different CPU
cores, but but don’t have to
 We can also simulate threads by multiplexing a
smaller number of cores over a larger number of
threads
22
Java class Thread
 threads are instances of class Thread
 Can create many, but they do consume space & time
 The Java Virtual Machine creates the thread that
executes your main method.
 Threads have a priority
 Higher priority threads are executed preferentially
 By default, newly created threads have initial priority
equal to the thread that created it (but priority can be
changed)
23
Creating a new Thread (Method 1)
24
class PrimeThread extends Thread {
long a, b;
PrimeThread(long a, long b) {
this.a= a; this.b= b;
}
@Override public void run() {
//compute primes between a and b
...
}
}
PrimeThread p= new PrimeThread(143, 195);
p.start();
overrides
Thread.run()
Call run() directly?
no new thread is used:
Calling thread will run it
Do this and
Java invokes run() in new thread
Creating a new Thread (Method 2)
25
class PrimeRun implements Runnable {
long a, b;
PrimeRun(long a, long b) {
this.a= a; this.b= b;
}
public void run() {
//compute primes between a and b
...
}
}
PrimeRun p= new PrimeRun(143, 195);
new Thread(p).start();
Example
26
Thread[Thread-0,5,main] 0
Thread[main,5,main] 0
Thread[main,5,main] 1
Thread[main,5,main] 2
Thread[main,5,main] 3
Thread[main,5,main] 4
Thread[main,5,main] 5
Thread[main,5,main] 6
Thread[main,5,main] 7
Thread[main,5,main] 8
Thread[main,5,main] 9
Thread[Thread-0,5,main] 1
Thread[Thread-0,5,main] 2
Thread[Thread-0,5,main] 3
Thread[Thread-0,5,main] 4
Thread[Thread-0,5,main] 5
Thread[Thread-0,5,main] 6
Thread[Thread-0,5,main] 7
Thread[Thread-0,5,main] 8
Thread[Thread-0,5,main] 9
public class ThreadTest extends Thread {
public static void main(String[] args) {
new ThreadTest().start();
for (int i= 0; i < 10; i++) {
System.out.format("%s %dn",
Thread.currentThread(), i);
}
}
public void run() {
for (int i= 0; i < 10; i++) {
System.out.format("%s %dn",
Thread.currentThread(), i);
}
}
}
Thread name, priority, thread group
Example
27 Thread[main,5,main] 0
Thread[main,5,main] 1
Thread[main,5,main] 2
Thread[main,5,main] 3
Thread[main,5,main] 4
Thread[main,5,main] 5
Thread[main,5,main] 6
Thread[main,5,main] 7
Thread[main,5,main] 8
Thread[main,5,main] 9
Thread[Thread-0,4,main] 0
Thread[Thread-0,4,main] 1
Thread[Thread-0,4,main] 2
Thread[Thread-0,4,main] 3
Thread[Thread-0,4,main] 4
Thread[Thread-0,4,main] 5
Thread[Thread-0,4,main] 6
Thread[Thread-0,4,main] 7
Thread[Thread-0,4,main] 8
Thread[Thread-0,4,main] 9
public class ThreadTest extends Thread {
public static void main(String[] args) {
new ThreadTest().start();
for (int i= 0; i < 10; i++) {
System.out.format("%s %dn",
Thread.currentThread(), i);
}
}
public void run() {
currentThread().setPriority(4);
for (int i= 0; i < 10; i++) {
System.out.format("%s %dn",
Thread.currentThread(), i);
}
}
}
Thread name, priority, thread group
Example
28 Thread[main,5,main] 0
Thread[main,5,main] 1
Thread[main,5,main] 2
Thread[main,5,main] 3
Thread[main,5,main] 4
Thread[main,5,main] 5
Thread[Thread-0,6,main] 0
Thread[Thread-0,6,main] 1
Thread[Thread-0,6,main] 2
Thread[Thread-0,6,main] 3
Thread[Thread-0,6,main] 4
Thread[Thread-0,6,main] 5
Thread[Thread-0,6,main] 6
Thread[Thread-0,6,main] 7
Thread[Thread-0,6,main] 8
Thread[Thread-0,6,main] 9
Thread[main,5,main] 6
Thread[main,5,main] 7
Thread[main,5,main] 8
Thread[main,5,main] 9
public class ThreadTest extends Thread {
public static void main(String[] args) {
new ThreadTest().start();
for (int i= 0; i < 10; i++) {
System.out.format("%s %dn",
Thread.currentThread(), i);
}
}
public void run() {
currentThread().setPriority(6);
for (int i= 0; i < 10; i++) {
System.out.format("%s %dn",
Thread.currentThread(), i);
}}}
Thread name, priority, thread group
Example
29
waiting...
running...
waiting...
running...
waiting...
running...
waiting...
running...
waiting...
running...
waiting...
running...
waiting...
running...
waiting...
running...
waiting...
running...
waiting...
running...
done
public class ThreadTest extends Thread {
static boolean ok = true;
public static void main(String[] args) {
new ThreadTest().start();
for (int i = 0; i < 10; i++) {
System.out.println("waiting...");
yield();
}
ok = false;
}
public void run() {
while (ok) {
System.out.println("running...");
yield();
}
System.out.println("done");
}
}
If threads happen to be sharing
a CPU, yield allows other waiting
threads to run.
Terminating Threads is tricky
 Easily done... but only in certain ways
 Safe way to terminate a thread: return from method
run
 Thread throws uncaught exception? whole program
will be halted (but it can take a second or two ... )
 Some old APIs have issues: stop(), interrupt(),
suspend(),
destroy(), etc.
 Issue: Can easily leave application in a “broken”
internal state.
 Many applications have some kind of variable telling
the thread to stop itself.
30
Threads can pause
 When active, a thread is “runnable”.
 It may not actually be “running”. For that, a CPU
must schedule it. Higher priority threads could run
first.
 A thread can pause
 Call Thread.sleep(k) to sleep for k milliseconds
 Doing I/O (e.g. read file, wait for mouse input, open
file) can cause thread to pause
 Java has a form of locks associated with objects.
When threads lock an object, one succeeds at a time.
31
Background (daemon) Threads
 In many applications we have a notion of “foreground”
and “background” (daemon) threads
 Foreground threads are doing visible work, like
interacting with the user or updating the display
 Background threads do things like maintaining data
structures (rebalancing trees, garbage collection, etc.)
 On your computer, the same notion of background
workers explains why so many things are always
running in the task manager.
32
Fancier forms of locking
 Java developers have created various synchronization
abstract data types
 Semaphores: a kind of synchronized counter
(invented by Dijkstra)
 Event-driven synchronization
 The Windows and Linux and Apple O/S have kernel
locking features, like file locking
 But for Java, synchronized is the core mechanism
33
Summary
 Use of multiple processes and multiple threads within
each process can exploit concurrency
 Which may be real (multicore) or “virtual” (an
illusion)
 When using threads, beware!
 Synchronize any shared memory to avoid race
conditions
 Synchronize objects in certain order to avoid
deadlocks
 Even with proper synchronization, concurrent
programs can have other problems such as
“livelock”
 Serious treatment of concurrency is a complex topic
34

More Related Content

Similar to cs2110Concurrency1.ppt (20)

PPTX
Concurrency with java
Tony Nguyen
 
PPTX
Concurrency with java
Fraboni Ec
 
PDF
Peyton jones-2011-parallel haskell-the_future
Takayuki Muranushi
 
PDF
Simon Peyton Jones: Managing parallelism
Skills Matter
 
PPTX
OS Module-2.pptx
bleh23
 
PPTX
Operating Systems R20 Unit 2.pptx
Prudhvi668506
 
PPTX
Multi Threading
Ferdin Joe John Joseph PhD
 
PPTX
WEEK07operatingsystemdepartmentofsoftwareengineering.pptx
babayaga920391
 
PPT
Multithreading in java programming language.ppt
AutoAuto9
 
PPT
Threads in Java
Gaurav Aggarwal
 
PPT
Slot02 concurrency1
Viên Mai
 
PPT
slides8 SharedMemory.ppt
aminnezarat
 
PPTX
Multi threading
gndu
 
PPTX
Seminar on Parallel and Concurrent Programming
Stefan Marr
 
PDF
Threads lecture slides for operating systems
amirtarek401
 
PPTX
Java-7 Concurrency
Masudul Haque
 
PDF
Ppl for students unit 4 and 5
Akshay Nagpurkar
 
PDF
Ppl for students unit 4 and 5
Akshay Nagpurkar
 
PPTX
Basic Thread Knowledge
Shipra Roy
 
PDF
CH04.pdf
ImranKhan880955
 
Concurrency with java
Tony Nguyen
 
Concurrency with java
Fraboni Ec
 
Peyton jones-2011-parallel haskell-the_future
Takayuki Muranushi
 
Simon Peyton Jones: Managing parallelism
Skills Matter
 
OS Module-2.pptx
bleh23
 
Operating Systems R20 Unit 2.pptx
Prudhvi668506
 
WEEK07operatingsystemdepartmentofsoftwareengineering.pptx
babayaga920391
 
Multithreading in java programming language.ppt
AutoAuto9
 
Threads in Java
Gaurav Aggarwal
 
Slot02 concurrency1
Viên Mai
 
slides8 SharedMemory.ppt
aminnezarat
 
Multi threading
gndu
 
Seminar on Parallel and Concurrent Programming
Stefan Marr
 
Threads lecture slides for operating systems
amirtarek401
 
Java-7 Concurrency
Masudul Haque
 
Ppl for students unit 4 and 5
Akshay Nagpurkar
 
Ppl for students unit 4 and 5
Akshay Nagpurkar
 
Basic Thread Knowledge
Shipra Roy
 
CH04.pdf
ImranKhan880955
 

Recently uploaded (20)

PDF
3rd International Conference on Machine Learning and IoT (MLIoT 2025)
ClaraZara1
 
PPTX
Numerical-Solutions-of-Ordinary-Differential-Equations.pptx
SAMUKTHAARM
 
PPTX
Final Major project a b c d e f g h i j k l m
bharathpsnab
 
PDF
MODULE-5 notes [BCG402-CG&V] PART-B.pdf
Alvas Institute of Engineering and technology, Moodabidri
 
PDF
methodology-driven-mbse-murphy-july-hsv-huntsville6680038572db67488e78ff00003...
henriqueltorres1
 
PPTX
OCS353 DATA SCIENCE FUNDAMENTALS- Unit 1 Introduction to Data Science
A R SIVANESH M.E., (Ph.D)
 
PPTX
Water Resources Engineering (CVE 728)--Slide 4.pptx
mohammedado3
 
PDF
methodology-driven-mbse-murphy-july-hsv-huntsville6680038572db67488e78ff00003...
henriqueltorres1
 
PDF
Electrical Engineer operation Supervisor
ssaruntatapower143
 
PPTX
How Industrial Project Management Differs From Construction.pptx
jamespit799
 
PPTX
Mechanical Design of shell and tube heat exchangers as per ASME Sec VIII Divi...
shahveer210504
 
PPTX
Introduction to Internal Combustion Engines - Types, Working and Camparison.pptx
UtkarshPatil98
 
PPT
Footbinding.pptmnmkjkjkknmnnjkkkkkkkkkkkkkk
mamadoundiaye42742
 
PPTX
澳洲电子毕业证澳大利亚圣母大学水印成绩单UNDA学生证网上可查学历
Taqyea
 
PPT
Testing and final inspection of a solar PV system
MuhammadSanni2
 
PPTX
美国电子版毕业证南卡罗莱纳大学上州分校水印成绩单USC学费发票定做学位证书编号怎么查
Taqyea
 
PPTX
fatigue in aircraft structures-221113192308-0ad6dc8c.pptx
aviatecofficial
 
PPTX
What is Shot Peening | Shot Peening is a Surface Treatment Process
Vibra Finish
 
PPTX
Distribution reservoir and service storage pptx
dhanashree78
 
PPTX
Lecture 1 Shell and Tube Heat exchanger-1.pptx
mailforillegalwork
 
3rd International Conference on Machine Learning and IoT (MLIoT 2025)
ClaraZara1
 
Numerical-Solutions-of-Ordinary-Differential-Equations.pptx
SAMUKTHAARM
 
Final Major project a b c d e f g h i j k l m
bharathpsnab
 
MODULE-5 notes [BCG402-CG&V] PART-B.pdf
Alvas Institute of Engineering and technology, Moodabidri
 
methodology-driven-mbse-murphy-july-hsv-huntsville6680038572db67488e78ff00003...
henriqueltorres1
 
OCS353 DATA SCIENCE FUNDAMENTALS- Unit 1 Introduction to Data Science
A R SIVANESH M.E., (Ph.D)
 
Water Resources Engineering (CVE 728)--Slide 4.pptx
mohammedado3
 
methodology-driven-mbse-murphy-july-hsv-huntsville6680038572db67488e78ff00003...
henriqueltorres1
 
Electrical Engineer operation Supervisor
ssaruntatapower143
 
How Industrial Project Management Differs From Construction.pptx
jamespit799
 
Mechanical Design of shell and tube heat exchangers as per ASME Sec VIII Divi...
shahveer210504
 
Introduction to Internal Combustion Engines - Types, Working and Camparison.pptx
UtkarshPatil98
 
Footbinding.pptmnmkjkjkknmnnjkkkkkkkkkkkkkk
mamadoundiaye42742
 
澳洲电子毕业证澳大利亚圣母大学水印成绩单UNDA学生证网上可查学历
Taqyea
 
Testing and final inspection of a solar PV system
MuhammadSanni2
 
美国电子版毕业证南卡罗莱纳大学上州分校水印成绩单USC学费发票定做学位证书编号怎么查
Taqyea
 
fatigue in aircraft structures-221113192308-0ad6dc8c.pptx
aviatecofficial
 
What is Shot Peening | Shot Peening is a Surface Treatment Process
Vibra Finish
 
Distribution reservoir and service storage pptx
dhanashree78
 
Lecture 1 Shell and Tube Heat exchanger-1.pptx
mailforillegalwork
 

cs2110Concurrency1.ppt

  • 1. THREADS & CONCURRENCY Lecture 23– CS2110 – Fall 2018
  • 2. Prelim room assignments (not yet posted elsewhere) 5:30. URHG01: netids lac326 to rzt4 5:30. BKL200: netids sa2229 to zz632 plus all conflicts moving from 7:30 to 5:30 exam -------------------------------- 7:30. URHG01: aa2277 to gyz2 7:30. BKL200: hcm58 to ky356 plus all conflicts moving from 5:30 to 7:30 exam There will be a homework on concurrency. 2
  • 3. CPU Central Processing Unit. Simplified view The CPU is the part of the computer that executes instructions. Java: x= x + 2; Suppose variable x is at Memory location 800, Instructions at 10 Machine language: 10: load register 1, 800 11: Add register 1, 2 12: Store register 1, 800 3 Basic uniprocessor-CPU computer. Black lines indicate data flow, red lines indicate control flow From wikipedia
  • 4. Part of Activity Monitor in Gries’s laptop 4 >100 processes are competing for time. Here’s some of them:
  • 5. Clock rate  Clock rate “frequency at which CPU is running” Higher the clock rate, the faster instructions are executed.  First CPUs: 5-10 Hz (cycles per second)  Today MacBook Pro 3.5GHz  Your OS can control the clock rate, slow it down when idle, speed up when more 5
  • 6. Why multicore?  Moore’s Law: Computer speeds and memory densities nearly double each year 6
  • 7. But a fast computer runs hot  Power dissipation rises as square of the clock rate  Chips were heading toward melting down!  Put more CPUs on a chip: with four CPUs on one chip, even if we run each at half speed we can perform more overall computations! 7
  • 8. Today: Not one CPU but many Processing Unit is called a core.  Modern computers have “multiple cores” (processing units)  Instead of a single CPU (central processing unit) on the chip 5-10 common. Intel has prototypes with 80!  We often run many programs at the same time  Even with a single core (processing unit), your program may have more than one thing “to do” at a time  Argues for having a way to do many things at once 8
  • 9. Many programs. Each can have several “threads of execution” We often run many programs at the same time And each program may have several “threads of execution” 9 Example, in a Paint program, when you click the pencil tool, a new thread of execution is started to call the method to process it: Main GUI thread Process pencil click
  • 10. Programming a Cluster... 10 • Sometimes you want to write a program that is executed on many machines! • Atlas Cluster (at Cornell): • 768 cores • 1536 GB RAM • 24 TB Storage • 96 NICs (Network Interface Controller)
  • 11. Programming a Cluster... 11 Programs like those that simulate weather have a big array of points, At each step of simulation, calculates whether at each point based on info at surrounding points. Each is on a separate processor.
  • 12. Many processes are executed simultaneously on your computer 12 • Operating system provides support for multiple “processes” • Usually fewer processors than processes • Processes are an abstraction: at hardware level, lots of multitasking –memory subsystem –video controller –buses –instruction prefetching
  • 13. Concurrency  Concurrency refers to a single program in which several processes, called threads, are running simultaneously  Special problems arise  They reference the same data and can interfere with each other, e.g. one process modifies a complex structure like a heap while another is trying to read it  CS2110: we focus on two main issues:  Race conditions  Deadlock 13
  • 14. Race conditions  A “race condition” arises if two or more processes access the same variables or objects concurrently and at least one does updates  Example: Processes t1 and t2 x= x + 1; for some static global x. Process t1 Process t2 … ... x= x + 1; x= x + 1; But x= x+1; is not an “atomic action”: it takes several steps 14
  • 15. Race conditions  LOAD x  ADD 1  STORE x  ...  LOAD x  ADD 1  STORE x Thread t1 Thread t2 15  Suppose x is initially 5  ... after finishing, x = 6! We “lost” an update
  • 16. Race conditions  Typical race condition: two processes wanting to change a stack at the same time. Or make conflicting changes to a database at the same time.  Race conditions are bad news  Race conditions can cause many kinds of bugs, not just the example we see here!  Common cause for “blue screens”: null pointer exceptions, damaged data structures  Concurrency makes proving programs correct much harder! 16
  • 17. Deadlock  To prevent race conditions, one often requires a process to “acquire” resources before accessing them, and only one process can “acquire” a given resource at a time.  Examples of resources are:  A file to be read  An object that maintains a stack, a linked list, a hash table, etc.  But if processes have to acquire two or more resources at the same time in order to do their work, deadlock can occur. This is the subject of the next slides. 17
  • 18. Dining philosopher problem 18 Five philosophers sitting at a table. Each repeatedly does this: 1. think 2. eat What do they eat? spaghetti. Need TWO forks to eat spaghetti!
  • 19. Dining philosopher problem 19 Each does repeatedly : 1. think 2. eat (2 forks) eat is then: pick up left fork pick up right fork pick up food, eat put down left fork put down rght fork At one point, they all pick up their left forks DEADLOCK!
  • 20. Dining philosopher problem 20 Simple solution to deadlock: Number the forks. Pick up smaller one first 1. think 2. eat (2 forks) eat is then: pick up smaller fork pick up bigger fork pick up food, eat put down bigger fork put down smallerfork 1 2 4 3 5
  • 21. Java: What is a Thread?  A separate “execution” that runs within a single program and can perform a computational task independently and concurrently with other threads  Many applications do their work in just a single thread: the one that called main() at startup  But there may still be extra threads...  ... Garbage collection runs in a “background” thread  GUIs have a separate thread that listens for events and “dispatches” calls to methods to process them  Today: learn to create new threads of our own in Java 21
  • 22. Thread  A thread is an object that “independently computes”  Needs to be created, like any object  Then “started” --causes some method to be called. It runs side by side with other threads in the same program; they see the same global data  The actual executions could occur on different CPU cores, but but don’t have to  We can also simulate threads by multiplexing a smaller number of cores over a larger number of threads 22
  • 23. Java class Thread  threads are instances of class Thread  Can create many, but they do consume space & time  The Java Virtual Machine creates the thread that executes your main method.  Threads have a priority  Higher priority threads are executed preferentially  By default, newly created threads have initial priority equal to the thread that created it (but priority can be changed) 23
  • 24. Creating a new Thread (Method 1) 24 class PrimeThread extends Thread { long a, b; PrimeThread(long a, long b) { this.a= a; this.b= b; } @Override public void run() { //compute primes between a and b ... } } PrimeThread p= new PrimeThread(143, 195); p.start(); overrides Thread.run() Call run() directly? no new thread is used: Calling thread will run it Do this and Java invokes run() in new thread
  • 25. Creating a new Thread (Method 2) 25 class PrimeRun implements Runnable { long a, b; PrimeRun(long a, long b) { this.a= a; this.b= b; } public void run() { //compute primes between a and b ... } } PrimeRun p= new PrimeRun(143, 195); new Thread(p).start();
  • 26. Example 26 Thread[Thread-0,5,main] 0 Thread[main,5,main] 0 Thread[main,5,main] 1 Thread[main,5,main] 2 Thread[main,5,main] 3 Thread[main,5,main] 4 Thread[main,5,main] 5 Thread[main,5,main] 6 Thread[main,5,main] 7 Thread[main,5,main] 8 Thread[main,5,main] 9 Thread[Thread-0,5,main] 1 Thread[Thread-0,5,main] 2 Thread[Thread-0,5,main] 3 Thread[Thread-0,5,main] 4 Thread[Thread-0,5,main] 5 Thread[Thread-0,5,main] 6 Thread[Thread-0,5,main] 7 Thread[Thread-0,5,main] 8 Thread[Thread-0,5,main] 9 public class ThreadTest extends Thread { public static void main(String[] args) { new ThreadTest().start(); for (int i= 0; i < 10; i++) { System.out.format("%s %dn", Thread.currentThread(), i); } } public void run() { for (int i= 0; i < 10; i++) { System.out.format("%s %dn", Thread.currentThread(), i); } } } Thread name, priority, thread group
  • 27. Example 27 Thread[main,5,main] 0 Thread[main,5,main] 1 Thread[main,5,main] 2 Thread[main,5,main] 3 Thread[main,5,main] 4 Thread[main,5,main] 5 Thread[main,5,main] 6 Thread[main,5,main] 7 Thread[main,5,main] 8 Thread[main,5,main] 9 Thread[Thread-0,4,main] 0 Thread[Thread-0,4,main] 1 Thread[Thread-0,4,main] 2 Thread[Thread-0,4,main] 3 Thread[Thread-0,4,main] 4 Thread[Thread-0,4,main] 5 Thread[Thread-0,4,main] 6 Thread[Thread-0,4,main] 7 Thread[Thread-0,4,main] 8 Thread[Thread-0,4,main] 9 public class ThreadTest extends Thread { public static void main(String[] args) { new ThreadTest().start(); for (int i= 0; i < 10; i++) { System.out.format("%s %dn", Thread.currentThread(), i); } } public void run() { currentThread().setPriority(4); for (int i= 0; i < 10; i++) { System.out.format("%s %dn", Thread.currentThread(), i); } } } Thread name, priority, thread group
  • 28. Example 28 Thread[main,5,main] 0 Thread[main,5,main] 1 Thread[main,5,main] 2 Thread[main,5,main] 3 Thread[main,5,main] 4 Thread[main,5,main] 5 Thread[Thread-0,6,main] 0 Thread[Thread-0,6,main] 1 Thread[Thread-0,6,main] 2 Thread[Thread-0,6,main] 3 Thread[Thread-0,6,main] 4 Thread[Thread-0,6,main] 5 Thread[Thread-0,6,main] 6 Thread[Thread-0,6,main] 7 Thread[Thread-0,6,main] 8 Thread[Thread-0,6,main] 9 Thread[main,5,main] 6 Thread[main,5,main] 7 Thread[main,5,main] 8 Thread[main,5,main] 9 public class ThreadTest extends Thread { public static void main(String[] args) { new ThreadTest().start(); for (int i= 0; i < 10; i++) { System.out.format("%s %dn", Thread.currentThread(), i); } } public void run() { currentThread().setPriority(6); for (int i= 0; i < 10; i++) { System.out.format("%s %dn", Thread.currentThread(), i); }}} Thread name, priority, thread group
  • 29. Example 29 waiting... running... waiting... running... waiting... running... waiting... running... waiting... running... waiting... running... waiting... running... waiting... running... waiting... running... waiting... running... done public class ThreadTest extends Thread { static boolean ok = true; public static void main(String[] args) { new ThreadTest().start(); for (int i = 0; i < 10; i++) { System.out.println("waiting..."); yield(); } ok = false; } public void run() { while (ok) { System.out.println("running..."); yield(); } System.out.println("done"); } } If threads happen to be sharing a CPU, yield allows other waiting threads to run.
  • 30. Terminating Threads is tricky  Easily done... but only in certain ways  Safe way to terminate a thread: return from method run  Thread throws uncaught exception? whole program will be halted (but it can take a second or two ... )  Some old APIs have issues: stop(), interrupt(), suspend(), destroy(), etc.  Issue: Can easily leave application in a “broken” internal state.  Many applications have some kind of variable telling the thread to stop itself. 30
  • 31. Threads can pause  When active, a thread is “runnable”.  It may not actually be “running”. For that, a CPU must schedule it. Higher priority threads could run first.  A thread can pause  Call Thread.sleep(k) to sleep for k milliseconds  Doing I/O (e.g. read file, wait for mouse input, open file) can cause thread to pause  Java has a form of locks associated with objects. When threads lock an object, one succeeds at a time. 31
  • 32. Background (daemon) Threads  In many applications we have a notion of “foreground” and “background” (daemon) threads  Foreground threads are doing visible work, like interacting with the user or updating the display  Background threads do things like maintaining data structures (rebalancing trees, garbage collection, etc.)  On your computer, the same notion of background workers explains why so many things are always running in the task manager. 32
  • 33. Fancier forms of locking  Java developers have created various synchronization abstract data types  Semaphores: a kind of synchronized counter (invented by Dijkstra)  Event-driven synchronization  The Windows and Linux and Apple O/S have kernel locking features, like file locking  But for Java, synchronized is the core mechanism 33
  • 34. Summary  Use of multiple processes and multiple threads within each process can exploit concurrency  Which may be real (multicore) or “virtual” (an illusion)  When using threads, beware!  Synchronize any shared memory to avoid race conditions  Synchronize objects in certain order to avoid deadlocks  Even with proper synchronization, concurrent programs can have other problems such as “livelock”  Serious treatment of concurrency is a complex topic 34