1. MPI: Portable Parallel Programming for Scientific Computing

2. Portable Parallel Programming
Why Parallel? For performance:
Realtime needs (weather prediction)
Large memory (throughput)
Why Portable?
Lifetime of code >> machine
Performance through algorithms

3. The Message Passing Model
Parallel programs consist of cooperating processes, each with its own memory
Processes send data to one another as messages
Messages may have tags that may be used to sort messages
Messages may be received in any order

4. What is MPI? Message-passing model Standard (specification)
Many implementations
MPICH most widely used
Two phases:
MPI 1: Traditional message-passing
MPI 2: Remote memory, parallel I/O, and dynamic processes

5. Why was MPI needed? Software crisis in parallel computing
Each vendor provided their own, different interface
No “critical mass” of users
Enabling libraries (code sharing)
Turnkey parallel applications
CFD, pharmaceutical design, etc.

6. Quick Tour of MPI Point-to-point Collective
Process groups and topology
Profiling
Other

7. Point-to-point Send/Receive Datatype Contexts Buffering
MPI_Send( A, 10, MPI_DOUBLE, 1, …)
MPI_Recv( B, 20, MPI_DOUBLE, 0, … )
Datatype
Basic for heterogeneity
Derived for non-contiguous
Contexts
Message safety for libraries
Buffering
Robustness and correctness

8. Collective Process groups Categories
Collections of cooperating processes
Hierarchical algorithms need nested collections
Categories
Communication: Broadcast data
Computation: Global sum
Synchronization: Barrier

9. New MPI-2 Features
Remote Memory
Parallel I/O
Dynamic Process
Threads

10. MPI in the World Libraries Applications Papers
At ANL: PETSc, SUMMA3d, etc.
Others: Aztec, PESSL, ScaLAPACK, FFTW, etc.
Applications
Electromagnetic Scattering
Groundwater pollution
Stellar atmospheres
Reactive flows
QCD
Navier-Stokes
Convective flows
Multi-physics in metal forming
Papers