Programming Clusters using Message-Passing Interface (MPI)

1. Programming Clusters using Message-Passing Interface (MPI) Cloud Computing and Distributed Systems (CLOUDS) LaboratoryThe University of MelbourneMelbourne, Australiawww.cloudbus.org Dr. Rajkumar Buyya

2. Outline • Introduction to Message Passing Environments • HelloWorld MPI Program • Compiling and Running MPI programs • Elements of Hello World Program • MPI Routines Listing • Communication in MPI programs • Summary

3. Message-Passing Programming Paradigm • Each processor in a message-passing program runs a sub-program • written in a conventional sequential language • all variables are private • communicate via special subroutine calls M M M Memory P P P Processors/Node Interconnection Network

4. SPMD: A dominant paradigm for writing data parallel applications main(int argc, char **argv) { if(process is assigned Master role) { /* Assign work and coordinate workers and collect results */ MasterRoutine(/*arguments*/); } else /* it is worker process */ { /* interact with master and other workers. Do the work and send results to the master*/ WorkerRoutine(/*arguments*/); } }

5. Messages • Messages are packets of data moving between sub-programs. • The message passing system has to be told the following information • Sending processor • Source location • Data type • Data length • Receiving processor(s) • Destination location • Destination size

6. Messages • Access: • Each sub-program needs to be connected to a message passing system • Addressing: • Messages need to have addresses to be sent to • Reception: • It is important that the receiving process is capable of dealing with the messages it is sent • A message passing system is similar to: • Post-office, Phone line, Fax, E-mail, etc • Message Types: • Point-to-Point, Collective, Synchronous (telephone)/Asynchronous (Postal)

7. Message Passing Systems and MPI - www.mpi-forum.org • Initially each manufacturer developed their own message passing interface • Wide range of features, often incompatible • MPI Forum brought together several Vendors and users of HPC systems from US and Europe – overcome above limitations. • Produced a document defining a standard, called Message Passing Interface (MPI), which is derived from experience or common features/issues addressed by many message-passing libraries. It aimed: • to provide source-code portability • to allow efficient implementation • it provides a high level of functionality • support for heterogeneous parallel architectures • parallel I/O (in MPI 2.0) • MPI 1.0 contains over 115 routines/functions that can be grouped into 8 categories.

8. General MPI Program Structure MPI Include File Initialise MPI Environment Do work and perform message communication Terminate MPI Environment

9. MPI programs • MPI is a library - there are NO language changes • Header Files • C: #include <mpi.h> • MPI Function Format • C: error = MPI_Xxxx(parameter,...); MPI_Xxxx(parameter,...);

10. Example - C #include <mpi.h> /* include other usual header files*/ main(int argc, char **argv) { /* initialize MPI */ MPI_Init(&argc, &argv); /* main part of program */ /* terminate MPI */ MPI_Finalize(); exit(0); }

11. MPI helloworld.c #include <mpi.h> main(int argc, char **argv) { int numtasks, rank; MPI_Init(&argc, &argv); MPI_Comm_size(MPI_COMM_WORLD, & numtasks); MPI_Comm_rank(MPI_COMM_WORLD, &rank); printf("Hello World from process %d of %d\n“, rank, numtasks); MPI_Finalize(); }

12. MPI Programs Compilation and Execution

13. Master Node: mungerabah.csse.unimelb.edu.au 16 core, Xeon 3GHz 32 GB memory > 250 GB integrated storage Gigabit LAN CDROM Drives RedHat Enterprise Linux 5 Worker Nodes(node01b..node20b) Each worker node consists of the following: Dual core Xeon(R) 2.4GHz 2 GB memory > 20 GB harddisk Gigabit LAN RedHat Enterprise Linux 5 Master: node00.cs.mu.oz.au Internal worker nodes: node01b node02b .... node20b Mungerabah/Manjra: Linux Cluster Mungerabah Linux cluster

14. Front View Back View How Manjra cluster looks

15. A snapshot of Manjra cluster

16. Compile and Run Commands • Compile: • mpicc helloworld.c -o helloworld • Run: • manjra> mpirun -np 3 helloworld [hosts picked from configuration file automatically] • manjra> mpirun -np 3 -machinefile machines.list helloworld • NOTE: when you run first time, you need to enter “password” again – due to “customised” (security issue) installation in the cluster . Only students are given this privilege! • The file machines.list contains nodes list: • node01b • .. • node20b • If some nodes don’t work, remove them from the machine file. No of processes

17. Sample Run and Output • A Run with 3 Processes: • manjra> mpirun -np 3 -machinefile machines.list helloworld • Hello World from process 0 of 3 • Hello World from process 1 of 3 • Hello World from process 2 of 3 • A Run by default • manjra> helloworld • Hello World from process 0 of 1

18. Sample Run and Output • A Run with 6 Processes: • manjra> mpirun -np 6 -machinefile machines.list helloworld • Hello World from process 0 of 6 • Hello World from process 3 of 6 • Hello World from process 1 of 6 • Hello World from process 5 of 6 • Hello World from process 4 of 6 • Hello World from process 2 of 6 • Note: Process execution need not be in process number order.

19. Sample Run and Output • A Run with 6 Processes: • manjra> mpirun -np 6 -machinefile machines.list helloworld • Hello World from process 0 of 6 • Hello World from process 3 of 6 • Hello World from process 1 of 6 • Hello World from process 2 of 6 • Hello World from process 5 of 6 • Hello World from process 4 of 6 • Note: Change in process output order. For each run, process mapping can be different. They may run on machines with different load. Hence such difference.

20. Setting for automatic login to nodes without password • A quick initial setup is required to enable ssh access without password (copy of rsh keys to the cluster): • $ cd ~ • Takes to you login home directory • $ ssh-keygen • <just type enter every time prompt asks for action> • $ cp .ssh/id_rsa.pub .ssh/authorized_keys • When you run/ssh for a node first time, you have to authorize the host (type “yes”).

21. More on MPI Program Elements and Error Checking

22. Handles • MPI controls its own internal data structures • MPI releases ‘handles’ to allow programmers to refer to these • “C” handles are of distinct typedef‘d types and arrays are indexed from 0 • Some arguments can be of any type - in C these are declared as void *

23. Initializing MPI • The first MPI routine called in any MPI program must be MPI_Init. • The C version accepts the arguments to main • int MPI_Init(int *argc, char ***argv); • MPI_Init must be called by every MPI program • Making multiple MPI_Init calls is erroneous • MPI_INITIALIZED is an exception to first rule

24. MPI_COMM_WORLD • MPI_INIT defines a communicator called MPI_COMM_WORLD for every process that calls it. • All MPI communication calls require a communicator argument • MPI processes can only communicate if they share a communicator. • A communicator contains a group which is a list of processes • Each process has it’s rank within the communicator • A process can have several communicators

25. Communicators • MPI uses objects called Communicators that defines which collection of processes communicate with each other. • Every process has unique integer identifier assigned by the system when the process initialises. A rank is sometimes called process ID. • Processes can request information from a communicator • MPI_Comm_rank(MPI_comm comm, int *rank) • Returns the rank of the process in comm • MPI_Comm_size(MPI_Comm comm, int *size) • Returns the size of the group in comm

26. Finishing up • An MPI program should call MPI_Finalize when all communications have completed. • Once called no other MPI calls can be made • Aborting: MPI_Abort(comm) • Attempts to abort all processes listed in commif comm = MPI_COMM_WORLD the whole program terminates

27. Hello World with Error Check

28. Display Hostname of MPI Process #include <mpi.h> main(int argc, char **argv) { int numtasks, rank; int resultlen; static char mpi_hostname[MPI_MAX_PROCESSOR_NAME]; MPI_Init(&argc, &argv); MPI_Comm_size(MPI_COMM_WORLD, &numtasks); MPI_Comm_rank(MPI_COMM_WORLD, &rank); MPI_Get_processor_name( mpi_hostname, &resultlen ); printf("Hello World from process %d of %d running on %s\n", rank, numtasks, mpi_hostname); MPI_Finalize(); }

29. MPI Routines

30. MPI Routines – C and Fortran • Environment Management • Point-to-Point Communication • Collective Communication • Process Group Management • Communicators • Derived Type • Virtual Topologies • Miscellaneous Routines

31. Environment Management Routines

32. Point-to-Point Communication • A simplest form of message passing • One process sends a message to another • Several variations on how sending a message can interact with execution of the sub-program

33. Point-to-Point variations • Synchronous Sends • provide information about the completion of the message • e.g. fax machines • Asynchronous Sends • Only know when the message has left • e.g. post cards • Blocking operations • only return from the call when operation has completed • Non-blocking operations • return straight away - can test/wait later for completion

34. Point-to-Point Communication

35. Collective Communications • Collective communication routines are higher level routines involving several processes at a time • Can be built out of point-to-point communications • Barriers • synchronise processes • Broadcast • one-to-many communication • Reduction operations • combine data from several processes to produce a single (usually) result

36. Collective Communication Routines

37. Process Group Management Routines

38. Communicators Routines

39. Derived Type Routines

40. Virtual Topologies Routines

41. Miscellaneous Routines

42. MPI Communication Routines and Examples

43. MPI Messages • A message contains a number of elements of some particular data type • MPI data types • Basic Types • Derived types • Derived types can be built up from basic types • “C” types are different from Fortran types

44. MPI Basic Data types - C

45. Point-to-Point Communication • Communication between two processes • Source process sends message to destination process • Communication takes place within a communicator • Destination process is identified by its rank in the communicator • MPI provides four communication modes for sending messages • standard, synchronous, buffered, and ready • Only one mode for receiving

46. Standard Send • Completes once the message has been sent • Note: it may or may not have been received • Programs should obey the following rules: • It should not assume the send will complete before the receive begins - can lead to deadlock • It should not assume the send will complete after the receive begins - can lead to non-determinism • processes should be eager readers - they should guarantee to receive all messages sent to them - else network overload • Can be implemented as either a buffered send or synchronous send

47. Standard Send (cont.) MPI_Send(void *buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Comm comm) buf the address of the data to be sent count the number of elements of datatype buf contains datatype the MPI datatype dest rank of destination in communicatorcomm taga marker used to distinguish different message types commthe communicator shared by sender and receiver ierror the fortran return value of the send

48. Standard Blocking Receive • Note: all sends so far have been blocking (but this only makes a difference for synchronous sends) • Completes when message received MPI_Recv(buf, count, datatype, source, tag, comm, status) source - rank of source process in communicator comm status - returns information about message • Synchronous Blocking Message-Passing • processes synchronise • sender process specifies the synchronous mode • blocking - both processes wait until transaction completed

49. For a communication to succeed • Sender must specify a valid destination rank • Receiver must specify a valid source rank • The communicator must be the same • Tags must match • Message types must match • Receivers buffer must be large enough • Receiver can use wildcards • MPI_ANY_SOURCE • MPI_ANY_TAG • actual source and tag are returned in status parameter

50. Standard/Blocked Send/Receive