CS 5220

Grumpy Old Man Warning!

• Lots of opinions ahead
• I can be wrong!

I have said…

• Use libraries! And frameworks! And tools!
• Use high-level languages (Lua, Python)!
• Lots of cool new tools! UPC++, SYCL, …
• Languages evolve, prefer modern C/C++/Fortran/Python
• You just need to tweak the Makefile.in files

Why Johnny Can’t Build

• Libraries aren’t installed
• How do I call Fortran from C++?
• How do I build with Lua, Python, etc?
• What about accelerators?
• How do I link everything?

Today

• Tool pragmatics
• Languages: big and little
• Some major frameworks

What is a compiler?

C/Fortran build flow

• Compiler maps source to assembly
  • Or to something else
• Assembler maps to object files
• Librarian produces
  • Static *archives (.a)
  • Dynamic libraries (.dylib) / shared objects (.so)
• Linker combines objects, resolves symbols
• Loader brings executables into memory

Compilation issues

• Language issues
  • Old compiler? (common, alas)
  • Specific extensions?
• Missing header files?

Assembler issues?

AARGH! (but not so common)

Static linker issues?

• Problems with name mangling
  • Know: extern "C" and iso_c_binding
• Can’t find libraries?
  • Esp language support libraries

Dynamic linking issues?

• Dynamic libraries resolve at load time
  • Need to have them on search paths!
• Classic problem: “DLL hell”
  • Versioning on libraries helps
  • Still can run into issues

Building

• Lowest: compile/link
• Next: Makefiles
• Next: CMake/autoconf/etc
• Use package managers if possible!

Autoconf

• configure; make; make install
• Behind the scenes: shell scripts and M4
• Finds libraries / platform specifics
• Generates build system for you

CMake

• Commercial tool (Kitware)
  • Pay for documentation
• Configure and build all in one
• Improvement on autotools?

Package managers

• Common on single node
  • Linux: apt, yum
  • MacOS: brew, macports
  • Cross: conda
• Spack, EasyBuild
  • Support environment modules
  • Allow multiple build toolchains

A step back

The mountain of abstraction

Consider class trajectory:

• Started very low-level
• Up to general ideas/kernels
• Up to parallel concepts, applications
• Nirvana: performance “just happens”?

Low-level frameworks and languages

• OpenMP and MPI
• Intel TBB
• Global arays
• Newer(?) parallel languages, extensions

Libraries

One thing (or a few) done fast:

• BLAS (MKL, OpenBLAS, ATLAS, etc)
• LAPACK and successors
• FFTW
• Sparse direct solvers

Key challenge: linking (esp across languages)

Framework libraries

• Many in PDE land
  • PETSc, SLEPc, TAO, etc
  • Trilinos
  • Overture
  • deal.ii
• More complicated interfaces
• Effectively defines embedded solver lang

Framework libraries

Renaissance thanks to ML!

• TensorFlow, PyTorch, JAX, etc
• Often define embedded DSLs
  • Build expression in Python, etc
  • Separate compile/optimize/execute

Scripting languages and PSEs

• MATLAB, Octave, R, Python, Julia
• “High productivity” vs “high performance”?
• Not necessarily slow! Extensions, libs, JIT
• Performance strategies transfer
• Bottlenecks may not be where you expect

Domain specific languages

Great opportunities from limited scope!

• Classic example: SQL
• PDE domain: finite element compilers
  • Dolfin framework
  • Sundance
• Embedded languages/specializers
• Modern: SimIt, GraphIt, Halide, etc

Simulation codes

• Typical pattern
  • Cusom lang/preproc for problem input
  • Scripting language to describe analysis
  • User-defined elements/modules in compiled lang
• Great for some classes of problems
• Can be torturned into covering other types!

Role of scripting languages

• Often interpreted
• Great for “high-level”
• Python is the default (or Lua?)
• Interface with C/Fortran for perf

Issues in mixing languages

• How do languages communicate?
• How are extensions compiled/linked?
• What support libraries are needed?
• Who owns main loop?
• Who owns program objects?
• How are exceptions handled?

Cross-language calls?

• Via pipes (pre-/post-processors)
• Inter-process communication
• Remote procedure call
• Linked together (with wrapper gen?)

Mixed language: tech issues

Primary pain points:

• Cross-language communication
• Building and deployment
• Debugging and run-time issues

Mixed language: social issues

• Availability of docs
• Availability of tools/libraries
• Active user base
• Open-ness of code base?
• Longevity

Best advice

• Conservative re general-purpose lang
  • (Modern) C++ and Fortran
  • Otherwise, look for C-compatible calling
  • Python on top
• More adventurous for DSLs

Also like Julia (yes, I’m inconsistent)

Concluding thought

I don’t know what the programming languge of the year 2000 will look like, but I know it will be called FORTRAN. – C.A.R. Hoare