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Multicore Computing Using Erlang

Art Gittleman California State University Long Beach artg@csulb.edu. Multicore Computing Using Erlang. Motivation. David Patterson – 2006 article The number of processors per chip is expected to double every two years

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Multicore Computing Using Erlang

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  1. Art Gittleman California State University Long Beach artg@csulb.edu Multicore ComputingUsing Erlang

  2. Motivation • David Patterson – 2006 article • The number of processors per chip is expected to double every two years • Educating faculty to train students in concurrency is not a trivial problem

  3. Using Multiple Processors • Most languages • Shared memory – must protect against • simultaneous modification • Erlang • Asynchronous message passing • Create processes • Scheduler uses available processors

  4. Erlang • Functional programming language • Developed at Ericsson -1993 • Open Source, runs on Windows, Linux, Mac • Applications • Amazon SimpleDB • Facebook chat (70 million+ users)

  5. Teaching Erlang • Survey of Programming Languages • Five week module on functional programming • Used machines with two cores • Basic Erlang and some concurrency • Advanced Programming Languages • Ten-week unit • Used Beowulf cluster, 30 processors

  6. Erlang Intro • Binding variables • Uses pattern matching • X = 4. binds X to 4 • Y = X + 2. binds Y to 6 • X = 3. error – X bound to 4 • Z + 1 = Y. binds Z to 5

  7. Data Structures • Tuples – fixed size • X = {hat, cat, fat}. • {A, cat, fat} = X. binds A to hat • Lists – variable size • L = [3, 4, 5, 6]. • [X | Y] = L. binds X to 3, Y to [4,5,6]

  8. Functions • Recursive definition • -module(append). • -export([append/2]). • append([ ] , L) → L; • append([H | T], L) → [H | append(T, L).

  9. Concurrency Primitives • Create a process • Pid = spawn(Fun) % Fun executes • % in new process • Send a process a message • Pid ! Message • Receive a message • receive … end

  10. -module(times2). -export([run/1]). times2() -> % executed in a process receive {From, X} -> From ! 2*X, % send back ans times2() end. run(Num) → % run(10) returns 20 Pid = spawn(fun times2/0), % create Pid ! {self(), Num}, % send receive Result -> Result end.

  11. Three Assignments • 1. Write three recursive functions • Generate a list of squares of random numbers • Sum two lists, element by element • Count the number of items < 1 in a list • 2. Estimate pi. Send number of random trials to a process that computes pi and returns result. • 3. Estimate pi using four processes. Speedup shown with two-core machines

  12. Higher-Order Functions • Map • L = [1,2,3,4]. • lists:map(fun(X) → 2*X end, L). • % returns [2,4,6,8] • List-comprehension • [2*X || X ← L].

  13. Ten most frequent words • From Adam Turoff, Haskell article • Used text of Emma by Jane Austen • Develop simple functions to find the ten most frequent words • Read text as list, split into sublists of equal words, create sublists of [freq, word] pairs, reverse sort, return top ten. • Many functions such as 'sort' are provided.

  14. Strassen Matrix Multiplication • Recursive, more efficient than standard method • NxN matrix requires 7 N/2xN/2 multiplications • Used seven machines on a Beowulf cluster. Compare 14 processors to 1. Time in seconds • 256x256 512x512 1024x102414 | 1.5 10.0 65.7 • 1 | 14.4 102.5 720.1

  15. Conclusions • Erlang was easy to use for concurrency. • The programmer spawns processes and the scheduler uses available processors either on the same machine or distributed. • Erlang fits well in a programing languages course.

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