Main Page/hybrid prog
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Jump to navigationJump to searchThis is the document page for hybrid programming plan for NekCEM (some notes taken from DOE Exascale workshop).
Approaches
- hybrid/evolutionary: MPI+ ___ ?
- MPI for inter-node prog, since # notes and inter-node concerns not expected to change dramatically
- support for hybrid programming/interoperability
- purer one-sided communications; active messages
- asynchronous collectives
- something else for intra-node
- OpenMP
- introduction of locality-oriented concepts?
- efforts in OpenMP 3.0 ?
- PGAS languages
- already support a notation of locality in a shared namespace
- UPC/CAF need to relax strictly SPMD execution model
- Sequoia
- support a strong notation of vertical locality
- OpenMP
- MPI for inter-node prog, since # notes and inter-node concerns not expected to change dramatically
- unified/holistic: __ ?
- a single notation for inter- and intra-node programming?
- traditional PGAS languages: UPC, CAF, Titanium
- require extension to handle nested parallelism, vertical locality
- HPCS languages: Chapel, X10, Fortress(?)
- designed with locality and post-SPMD parallelism in mind
- other candidates: Charm++, Global Arrays, Parallel X, ...
- others
- mainstream multi-core/GPU language: (sufficient promise to be funded?)
- domain-specific language
- fit your problem?
- should focus on more general solutions
- functional languages
- never heavily adopted in mainstream or HPC
- copy-on-write optimization and alias analysis?
- parallel scripting languages?
Expectation
- parallelism: nested, dynamic, loosely-coupled, data-driven (i.e. post-SPMD programming/execution models)
- to take advantage of architecture
- to better support load balancing and resilience
- locality: concepts for vertical control as well as horizontal (i.e. locality within a node rather than simply between nodes)
Tools: Debuggers, perf. analysis
- challenges
- need aggregation to hide details
- need to report info in user's terms
- good area for innovation (e.g. execution visualization to understand mapping of code to hardware)