Is System X for Me

1
Is System X for Me?

• Cal Ribbens
• Computer Science Department
• Lab. For Adv. Scientific Comput. Applications
  (LASCA)

2
Outline

• System X configuration
• Programming model and environment
• Problems most suited for System X
• Next steps
• Take-away messages

3
System X Configuration

• A cluster multiple computers used as a single,
  unified resource.'' (Pfister, 1998)
• 1100 Apple G5 Xserves
• CPU PPC970, 2GHz, 64 bit.
• Node 2 CPUs, 4 GB RAM, 160 GB disk
• Primary interconnect InfiniBand
• Secondary interconnect Gigabit Ethernet
• Peak theoretical speed 17.6 TF
• Linpack benchmark 10.3 TF

4
Key Architectural Features

• Distributed memory
• Both physically and logically distributed
• As opposed to SMP or DSM/VSM
• Standard OS on each node --- unix
• High-performance interconnection network
• NFS over fast Ethernet for file i/o, data
  staging, etc.

5
Programming Model Environment

• Automagic compiler/IDE? Sorry.
• New programming language? Maybe if you are
  writing new code from scratch.
• Commercial or community codes? Slowly emerging
  in some areas.
• Existing languages (Fortran, C, C) plus MPI?
  Most common. Possibly threads within a node.

6
MPI Message Passing Interface

• Programming model multiple processes (usually
  each an instance of the same program),
  communicating by explicit message passing.
• MPI is a de facto standard API.
• Several implementations available for tcp/ip and
  for fast networks, e.g., Myrinet, InfiniBand.
• Goals of MPI
• Portable, high-performance parallel codes
• Support for writing parallel libraries

7
MPI Hello World
include 'mpif.h' integer myid, ierr,
token, status(mpi_status_size) call
mpi_init (ierr) call mpi_comm_rank
(mpi_comm_world, myid, ierr ) if (myid
.eq. 0) then print , "hello"
call mpi_send (token, 1, mpi_integer, 1, 0,
mpi_comm_world, ierr) else call
mpi_recv (token, 1, mpi_integer, 0, 0,
mpi_comm_world, status, ierr) print ,
"world" endif call mpi_finalize
(ierr) stop end
8
Code Development Environment

• Standard editors, compilers, Unix tools. Work
  done on a front-end node.
• Job startup Batch system or command-line, e.g.,
  mpirun np 4 myexecutable
• Debugging? Usual tools within node. Totalview
  for MPI.
• Performance debugging? Tau

9
What will run well on X (and be worth the
trouble)?

• Large-scale computations 100s GB RAM, months
  of compute time.
• Regular computations where work and data is
  easily decomposed into many large, uniform
  chunks.
• Dense vs. sparse matrices
• Regular vs. irregular meshes
• Molecular statics vs. molecular dynamics

10
What runs well? (continued)

• Scalable computations
• (work / communication) stays away from zero
• Load stays balanced
• Number of independent tasks scales up (and down)
• Reasonable interprocess communication
  requirements
• Too much ? communication will be bottleneck
• Too little ? not a problem but maybe consider
  grid computing.

11
Next Steps

• Basic MPI short-course Feb 17, 19, 24, 26.
• Future LASCA short-courses likely
• Consulting grad student office hours or meet
  with LASCA faculty (lasca_at_cs.vt.edu)
• Summer FDI on parallel programming
• CS 4234 in F04, CS 5984 or 6404 in S05.
• Refs
• Gropp, Lusk, Skjellum, Using MPI, (2nd ed.), MIT
  Press, 1999.
• www-unix.mcs.anl.gov/mpi
• research.cs.vt.edu/lasca

12
Last Comments

• HPC is hard
• Models, machines, algorithms, software
• Students should get credit
• Collaboration is required
• System X
• will make a huge difference for a few
• will make a big difference for many
• will be a success if we do great research,
  leverage the visibility, and build a community.