CPS110: Intro to processes, threads and concurrency Author: Landon Cox
Intro to processes Decompose activities into separate tasks Allow them to run in parallel “Independently” (what does this mean?) “without dependencies” … Key OS abstraction: processes Run independently of each other Don’t have to know about others
Intro to processes Remember, for any area of OS, ask What interface does the hardware provide? What interface/abstraction does the OS provide? What is physical reality? Single computer (CPUs + memory) Execute instructions from many programs What does an application see? Each app “thinks” it has its own CPU + memory
Hardware, OS interfaces Hardware OS Applications Memory CPUs CPU, Mem Job 1 CPU, Mem Job 2 CPU, Mem Job 3
What is a process? Informal A program in execution Running code + things it can read/write Process ≠ program Formal ≥ 1 threads in their own address space (soon threads will share an address space)
Parts of a process Thread Sequence of executing instructions Active: does things Address space Data the process uses as it runs Passive: acted upon by threads
Play analogy Process is like a play performance Program is like the play’s script Threads Address space What are the threads? What is the address space?
What is in the address space? Program code Instructions, also called “text” Data segment Global variables, static variables Heap (where “new” memory comes from) Stack Where local variables are stored
Review of the stack Each stack frame contains a function’s Local variables Parameters Return address Saved values of calling function’s registers The stack enables recursion
const1=1 const2=0 const1=1 const2=0 main Example stack tmp=1 RA=0x804838c tmp=1 RA=0x804838c A RA=0x B const=0 RA=0x const=0 RA=0x C tmp=0 RA=0x tmp=0 RA=0x A 0xfffffff 0x0 Memory void C () { A (0); } void B () { C (); } void A (int tmp){ if (tmp) B (); } int main () { A (1); return 0; } void C () { A (0); } void B () { C (); } void A (int tmp){ if (tmp) B (); } int main () { A (1); return 0; } 0x x x x804838c Code Stack … SP
const1=3 const2=0 const1=3 const2=0 main The stack and recursion bnd=3 RA=0x804838c bnd=3 RA=0x804838c A bnd=2 RA=0x bnd=2 RA=0x A bnd=1 RA=0x bnd=1 RA=0x A bnd=0 RA=0x bnd=0 RA=0x A 0xfffffff 0x0 Memory void A (int bnd){ if (bnd) A (bnd-1); } int main () { A (3); return 0; } void A (int bnd){ if (bnd) A (bnd-1); } int main () { A (3); return 0; } 0x x804838c Code Stack … SP How can recursion go wrong? Can overflow the stack … Keep adding frame after frame
wrd[3] wrd[2] wrd[1] wrd[0] const2=0 wrd[3] wrd[2] wrd[1] wrd[0] const2=0 main The stack and buffer overflows b= 0x00234 RA=0x804838c b= 0x00234 RA=0x804838c cap 0xfffffff 0x0 Memory void cap (char* b){ for (int i=0; b[i]!=‘\0’; i++) b[i]+=32; } int main(char*arg) { char wrd[4]; strcpy(arg, wrd); cap (wrd); return 0; } void cap (char* b){ for (int i=0; b[i]!=‘\0’; i++) b[i]+=32; } int main(char*arg) { char wrd[4]; strcpy(arg, wrd); cap (wrd); return 0; } 0x x804838c Code Stack … SP 0x00234 What can go wrong? Can overflow wrd variable … Overwrite cap’s RA
What is missing? What process state isn’t in the address space? Registers Program counter (PC) General purpose registers Review 104 for more details
Multiple threads in an addr space Several actors on a single set Sometimes they interact (speak, dance) Sometimes they are apart (different scenes)
Private vs global thread state What state is private to each thread? PC (where actor is in his/her script) Stack, SP (actor’s mindset) What state is shared? Global variables, heap (props on set) Code (like lines of a play)
Looking ahead: concurrency Concurrency Having multiple threads active at one time Thread is the unit of concurrency Primary topics How threads cooperate on a single task How multiple threads can share the CPU Subject of Project 1
Looking ahead: address spaces Address space Unit of “state partitioning” Primary topics Many addr spaces sharing physical memory Efficiency Safety (protection) Subject of Project 2
Course administration CS account requests are out Admins should contact you w/i the next day or so Project 0 due 9/7, groups due Friday Post questions to the blackboard message board Once I have your group + you have your CS account, you can submit Project 1: The Big One Will be due in about a month Discussion section F (2:50-4:05) Any other questions?
Thread independence Ideal decomposition of tasks: Tasks are completely independent Remember our earlier definition of independence Is such a pure abstraction really feasible? Word saves a pdf, starts acroread, which reads the pdf? Running mp3 player, while compiling 110 project? Sharing creates dependencies Software resources (file, address space) Hardware resources (CPU, monitor, keyboard)
True thread independence What would pure independence actually look like? (system with no shared software, hardware resources) Multiple computer systems Each running non-interacting programs Technically still share the power grid … “Pure” independence is infeasible Tension between software dependencies,“features” Key question: is the thread abstraction still useful? Easier to have one thread with multiple responsibilities?
Consider a web server One processor Multiple disks Tasks Receives multiple, simultaneous requests Reads web pages from disk Returns on-disk files to requester
Web server (single thread) Option 1: could handle requests serially Easy to program, but painfully slow (why?) Client 1Client 2 WS R1 arrives Receive R1 R2 arrives Disk request 1a 1a completes R1 completes Receive R2
Web server (event-driven) Option 2: use asynchronous I/O Fast, but hard to program (why?) Client 1 Disk WS R1 arrives Receive R1 Disk request 1a 1a completes R1 completes Receive R2 Client 2 R2 arrives Finish 1a Start 1a
Web server (multi-threaded) Option 3: assign one thread per request Where is each request’s state stored? Client 1Client 2WS1 R1 arrives Receive R1 R2 arrives Disk request 1a 1a completes R1 completes Receive R2 WS2
Threads are useful It cannot provide total independence But it is still a useful abstraction! Threads make concurrent programming easier Thread system manages sharing the CPU (unlike in event-driven case) Apps can encapsulate task state w/i a thread (e.g. web request state)
Where are threads used? When a resource is slow, don’t want to wait on it Windowing system One thread per window, waiting for window input What is slow? Human input, mouse, keyboard Network file/web/DB server One thread per incoming request What is slow? Network, disk, remote user (e.g. ATM bank customer)
Where are threads used? When a resource is slow, don’t want to wait on it Operating system kernel One thread waits for keyboard input One thread waits for mouse input One thread writes to the display One thread writes to the printer One thread receives data from the network card One thread per disk … Just about everything except the CPU is slow
Cooperating threads Assume each thread has its own CPU We will relax this assumption later CPUs run at unpredictable speeds Source of non-determinism Memory CPU Thread A CPU Thread B CPU Thread C
Non-determinism and ordering Time Thread A Thread B Thread C Global ordering Why do we care about the global ordering? Might have dependencies between events Different orderings can produce different results Why is this ordering unpredictable? Can’t predict how fast processors will run
Non-determinism example 1 Thread A: cout << “ABC”; Thread B: cout << “123”; Possible outputs? “A1BC23”, “ABC123”, … Impossible outputs? Why? “321CBA”, “B12C3A”, … What is shared between threads? Screen, maybe the output buffer
Non-determinism example 2 y=10; Thread A: int x = y+1; Thread B: y = y*2; Possible results? A goes first: x = 11 and y = 20 B goes first: y = 20 and x = 21 What is shared between threads? Variable y
Non-determinism example 3 x=0; Thread A: x = 1; Thread B: x = 2; Possible results? B goes first: x = 1 A goes first: x = 2 Is x = 3 possible?
Example 3, continued What if “ x = ; ” is implemented as x := x & 0 x := x | Consider this schedule Thread A: x := x & 0 Thread B: x := x & 0 Thread B: x := x | 1 Thread A: x := x | 2
Atomic operations Must know what operations are atomic before we can reason about cooperation Atomic Indivisible Happens without interruption Between start and end of atomic action No events from other threads can occur
Review of examples Print example (ABC, 123) What did we assume was atomic? What if “print” is atomic? What if printing a char was not atomic? Arithmetic example ( x=y+1, y=y*2 ) What did we assume was atomic?
Atomicity in practice On most machines Memory assignment/reference is atomic E.g.: a=1, a=b Many other instructions are not atomic E.g.: double-precision floating point store (often involves two memory operations)
Virtual/physical interfaces Hardware OS Applications If you don’t have atomic operations, you can’t make one.
Another example Two threads (A and B) A tries to increment i B tries to decrement i Thread A: i = o; while (i < 10){ i++; } print “A done.” Thread B: i = o; while (i > -10){ i--; } print “B done.”
Example continued Who wins? Does someone have to win? Thread A: i = o; while (i < 10){ i++; } print “A done.” Thread B: i = o; while (i > -10){ i--; } print “B done.”
Example continued Will it go on forever if both threads Start at about the same time And execute at exactly the same speed? Yes, if each C statement is atomic. Thread A: i = o; while (i < 10){ i++; } print “A done.” Thread B: i = o; while (i > -10){ i--; } print “B done.”
Example continued What if i++/i-- are not atomic? tmp := i+1 i := tmp ( tmp is private to A and B)
Example continued Non-atomic i++/i-- If A starts ½ statement ahead, B can win How? Thread A: tmpA := i + 1 // tmpA == 1 Thread B: tmpB := i - 1 // tmpB == -1 Thread A: i := tmpA // i == 1 Thread B: i := tmpB // i == -1
Example continued Non-atomic i++/i-- If A starts ½ statement ahead, B can win How? Do you need to worry about this? Yes!!! No matter how unlikely
Debugging non-determinism Requires worst-case reasoning Eliminate all ways for program to break Debugging is hard Can’t test all possible interleavings Bugs may only happen sometimes Heisenbug Re-running program may make the bug disappear Doesn’t mean it isn’t still there!
Constraining concurrency Synchronization Controlling thread interleavings Some events are independent No shared state Relative order of these events don’t matter Other events are dependent Output of one can be input to another Their order can affect program results
Goals of synchronization 1.All interleavings must give correct result Correct concurrent program Works no matter how fast threads run Important for your projects! 2.Constrain program as little as possible Why? Constraints slow program down Constraints create complexity
Conclusion Next class: more cooperation “How do actors interact on stage?” Start Project 0 Simple, designed to help you with C++