Parallel Programming with Java

1. Parallel Programming with Java Aamir Shafi National University of Sciences and Technology (NUST) http://hpc.seecs.edu.pk/~aamir http://mpj-express.org

2. Two Important Concepts • Two fundamental concepts of parallel programming are: • Domain decomposition • Functional decomposition

3. Domain Decomposition Image taken from https://computing.llnl.gov/tutorials/parallel_comp/

4. Functional Decomposition Image taken from https://computing.llnl.gov/tutorials/parallel_comp/

5. Message Passing Interface (MPI) • MPI is a standard (an interface or an API): • It defines a set of methods that are used by application developers to write their applications • MPI library implement these methods • MPI itself is not a library—it is a specification document that is followed! • MPI-1.2 is the most popular specification version • Reasons for popularity: • Software and hardware vendors were involved • Significant contribution from academia • MPICH served as an early reference implementation • MPI compilers are simply wrappers to widely used C and Fortran compilers • History: • The first draft specification was produced in 1993 • MPI-2.0, introduced in 1999, adds many new features to MPI • Bindings available to C, C++, and Fortran • MPI is a success story: • It is the mostly adopted programming paradigm of IBM Blue Gene systems • At least two production-quality MPI libraries: • MPICH2 (http://www-unix.mcs.anl.gov/mpi/mpich2/) • OpenMPI (http://open-mpi.org) • There’s even a Java library: • MPJ Express (http://mpj-express.org)

6. Message Passing Model • Message passing model allows processors to communicate by passing messages: • Processors do not share memory • Data transfer between processors required cooperative operations to be performed by each processor: • One processor sends the message while other receives the message

7. Distributed Memory Cluster barq.niit.edu.pk (cluster head node) chenab1 chenab2 chenab3 chenab7 chenab6 chenab4 chenab5

8. Steps involved in executing the “Hello World!” program • Let’s logon to the cluster head node • Write the Hello World program • Compile the program • Write the machines files • Start MPJ Express daemons • Execute the parallel program • Stop MPJ Express daemons

9. Step1: Logon to the head node

10. Step 2: Write the Hello World Program

11. Step 3: Compile the code

12. Step 4: Write the machines file

13. Step 5: Start MPJ Express daemons

14. Step 6: Execute the parallel program aamir@barq:~/projects/mpj-user> mpjrun.sh -np 6 -headnodeip 10.3.20.120 -dport 11050 HelloWorld .. Hi from process <3> of total <6> Hi from process <1> of total <6> Hi from process <2> of total <6> Hi from process <4> of total <6> Hi from process <5> of total <6> Hi from process <0> of total <6> …

15. Step 7: Stop the MPJ Express daemons

16. COMM WORLD Communicator import java.util.*; import mpi.*; .. // Initialize MPI MPI.Init(args); // start up MPI // Get total number of processes and rank size = MPI.COMM_WORLD.Size(); rank = MPI.COMM_WORLD.Rank(); ..

17. What is size? import java.util.*; import mpi.*; .. // Get total number of processes size = MPI.COMM_WORLD.Size(); .. • Total number of processes in a communicator: • The size of MPI.COMM_WORLD is 6

18. What is rank? import java.util.*; import mpi.*; .. // Get total number of processes rank = MPI.COMM_WORLD.Rank(); .. • The “unique” identify (id) of a process in a communicator: • Each of the six processes in MPI.COMM_WORLD has a distinct rank or id

19. Single Program Multiple Data (SPMD) Model import java.util.*; import mpi.*; public class HelloWorld { MPI.Init(args); // start up MPI size = MPI.COMM_WORLD.Size(); rank = MPI.COMM_WORLD.Rank(); if (rank == 0) { System.out.println(“I am Process 0”); } else if (rank == 1) { System.out.println(“I am Process 1”); } MPI.Finalize(); }

20. Single Program Multiple Data (SPMD) Model import java.util.*; import mpi.*; public class HelloWorld { MPI.Init(args); // start up MPI size = MPI.COMM_WORLD.Size(); rank = MPI.COMM_WORLD.Rank(); if (rank%2 == 0) { System.out.println(“I am an even process”); } else if (rank%2 == 1) { System.out.println(“I am an odd process”); } MPI.Finalize(); }

21. Point to Point Communication • The most fundamental facility provided by MPI • Basically “exchange messages between two processes”: • One process (source) sends message • The other process (destination) receives message

22. Point to Point Communication • It is possible to send message for each basic datatype: • Floats (MPI.FLOAT), Integers (MPI.INT), Doubles (MPI.DOUBLE) … • Java Objects (MPI.OBJECT) • Each message contains a “tag”—an identifier Tag1 Tag2

23. Integers Process 4 Tag COMM_WORLD Point to Point Communication Process 1 Process 2 Process 0 message Process 3 Process 7 Process 6 Process 4 Process 5

24. Blocking Send() and Recv() Methods public void Send(Object buf, int offset, int count, Datatype datatype, int dest, int tag) throws MPIException public Status Recv(Object buf, int offset, int count, Datatype datatype, int src, int tag) throws MPIException

25. Blocking and Non-blocking Point-to-Point Comm • There are blocking and non-blocking version of send and receive methods • Blocking versions: • A process calls Send() or Recv(), these methods return when the message has been physically sent or received • Non-blocking versions: • A process calls Isend() or Irecv(), these methods return immediately • The user can check the status of message by calling Test() or Wait() • Non-blocking versions provide overlapping of computation and communication: • Asynchronous communication

26. “Blocking” Sender Receiver Send() Recv() CPU waits CPU waits time “Non Blocking” Sender Receiver Isend() Irecv() CPU does computation CPU does computation time Wait() Wait() CPU waits CPU waits

27. Non-blocking Point-to-Point Comm public Request Isend(Object buf, int offset, int count, Datatype datatype, int dest, int tag) throws MPIException public Request Irecv(Object buf, int offset, int count, Datatype datatype, int src, int tag) throws MPIException public Status Wait() throws MPIException public Status Test() throws MPIException

28. Performance Evaluation of Point to Point Communication • Normally ping pong benchmarks are used to calculate: • Latency: How long it takes to send N bytes from sender to receiver? • Throughput: How much bandwidth is achieved? • Latency is a useful measure for studying the performance of “small” messages • Throughput is a useful measure for studying the performance of “large” messages

29. Latency on Myrinet

30. Throughput on Myrinet

31. Collective communications • Provided as a convenience for application developers: • Save significant development time • Efficient algorithms may be used • Stable (tested) • Built on top of point-to-point communications • These operations include: • Broadcast, Barrier, Reduce, Allreduce, Alltoall, Scatter, Scan, Allscatter • Versions that allows displacements between the data

32. Broadcast, scatter, gather, allgather, alltoall Image from MPI standard doc

33. Broadcast, scatter, gather, allgather, alltoall public void Bcast(Object buf, int offset, int count, Datatype type, int root) throws MPIException public void Scatter(Object sendbuf, int sendoffset, int sendcount, Datatype sendtype, Object recvbuf, int recvoffset, int recvcount, Datatype recvtype, int root) throws MPIException public void Gather(Object sendbuf, int sendoffset, int sendcount, Datatype sendtype, Object recvbuf, int recvoffset, int recvcount, Datatype recvtype, int root) throws MPIException public void Allgather(Object sendbuf, int sendoffset int sendcount, Datatype sendtype, Object recvbuf, int recvoffset, int recvcount, Datatype recvtype) throws MPIException public void Alltoall(Object sendbuf, int sendoffset, int sendcount, Datatype sendtype, Object recvbuf, int recvoffset, int recvcount, Datatype recvtype) throws MPIException

34. Reduce collective operations Processes • MPI.PROD • MPI.SUM • MPI.MIN • MPI.MAX • MPI.LAND • MPI.BAND • MPI.LOR • MPI.BOR • MPI.LXOR • MPI.BXOR • MPI.MINLOC • MPI.MAXLOC

35. Reduce collective operations public void Reduce(Object sendbuf, int sendoffset, Object recvbuf, int recvoffset, int count, Datatype datatype, Op op, int root) throws MPIException public void Allreduce(Object sendbuf, int sendoffset, Object recvbuf, int recvoffset, int count, Datatype datatype, Op op) throws MPIException

36. Collective Communication Performance

37. Summary • MPJ Express is a Java messaging system that can be used to write parallel applications: • MPJ/Ibis and mpiJava are other similar software • MPJ Express provides point-to-point communication methods like Send() and Recv(): • Blocking and non-blocking versions • Collective communications is also supported • Feel free to contact me if you have any queries