Perspectives form US Department of Energy work on parallel programming models for performance portability
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1 Perspectives form US Department of Energy work on parallel programming models for performance portability Jeremiah J. Wilke Sandia National Labs Livermore, CA IMPACT workshop at HiPEAC Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy s National Nuclear Security Administration under contract DE-AC04-94AL SAND NO XXXXP
2 Art of the deal: How to sell your tools to DOE app developers Jeremiah J. Wilke Sandia National Labs Livermore, CA IMPACT workshop at HiPEAC Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy s National Nuclear Security Administration under contract DE-AC04-94AL SAND NO XXXXP
3 Very diverse set of applications on very diverse set of parallel architectures poses major challenges Highlights from National Energy Research Scientific Computing Center
4 My worldview: find general purpose programming models that enable performance portability Funding goal: Solution to replace MPI-only that gets to exascale Single piece of code should run well, not just correctly, across many different platforms Many hardware trends pushing new programming models GPU, CPU, KNL loop traversal order, optimal data layouts Multi-level memories tiling, caching optimizations to utilize highbandwidth memory, unified memory models with hardware support Communication avoiding algorithms, asynchronous models to hide communication latency Growing number of production apps use OpenMP, Kokkos, Raja for multithreading Next-generation experimental codes are exploring asynchronous many-task models including Legion, Charm++, many more 4
5 DOE and collaborator efforts on performance portability Modern C++ (metaprogramming) ``Regular C++ Directives New languages 5
6 DOE and collaborator efforts on performance portability Modern C++ (metaprogramming) Kokkos (Sandia): Carter Edwards and Christian Trott (array views and executors, loop traversal order, data layouts, lambdas and functors) Raja (Livermore): Jeff Keasler (executors, loop traversal order, data staging) DARMA (Sandia): Janine Bennett (coarse-grain tasks, runtime dep analysis) HPX (LSU): Hartmut Kaiser (futures, tasks, templated sync primitives) ``Regular C++ Directives New languages 6
7 DOE and collaborator efforts on performance portability Modern C++ (metaprogramming) Kokkos (Sandia): Carter Edwards and Christian Trott (array views and executors, loop traversal order, data layouts, lambdas and functors) Raja (Livermore): Jeff Keasler (executors, loop traversal order, data staging) DARMA (Sandia): Janine Bennett (coarse-grain tasks, runtime dep analysis) HPX (LSU): Hartmut Kaiser (futures, tasks, templated sync primitives) ``Regular C++ (not so much metaprogramming) UPC++ (Berkeley): Kathy Yelick (global address space) Legion (Standord, Los Alamos, NVidia): McCormick, Aiken, Bauer (coarsegrain tasks, runtime dep analysis, strong data model) Charm++ (UIUC): Kale (actor model) Directives New languages 7
8 DOE and collaborator efforts on performance portability Modern C++ (metaprogramming) Kokkos (Sandia, Edwards), Raja (Livermore, Keasler): executors, loop traversal order, data layouts, lambdas and functors) DARMA (Sandia): Janine Bennett (coarse-grain tasks, runtime dep analysis) HPX (LSU): Hartmut Kaiser (futures, tasks, templated sync primitives) ``Regular C++ UPC++ (Berkeley): Kathy Yelick (global address space) Legion (Standord, Los Alamos, NVidia): McCormick, Aiken, Bauer (coarsegrain tasks, runtime dep analysis, strong data model) Charm++ (UIUC): Kale (actor model) Directives: OpenMP OmpSs (Barcelona) New languages 8
9 DOE and collaborator efforts on performance portability Modern C++ (metaprogramming) Kokkos (Sandia, Edwards), Raja (Livermore, Keasler): executors, loop traversal order, data layouts, lambdas and functors) DARMA (Sandia): Janine Bennett (coarse-grain tasks, runtime dep analysis) HPX (LSU): Hartmut Kaiser (futures, tasks, templated sync primitives) ``Regular C++ UPC++ (Berkeley): Kathy Yelick (global address space) Legion (Standord, Los Alamos, NVidia): McCormick, Aiken, Bauer (coarsegrain tasks, runtime dep analysis, strong data model) Charm++ (UIUC): Kale (actor model) Directives: OpenMP, OmpSs New languages: Chapel (Cray): global address space language Regent (Stanford): expressive interface to Legion based on Terra, Lua 9
10 DOE and collaborator efforts on performance portability Modern C++ (metaprogramming) Kokkos (Sandia, Edwards), Raja (Livermore, Keasler): executors, loop traversal order, data layouts, lambdas and functors) DARMA (Sandia): Janine Bennett (coarse-grain tasks, runtime dep analysis) HPX (LSU): Hartmut Kaiser (futures, tasks, templated sync primitives) ``Regular C++ UPC++ (Berkeley): Kathy Yelick (global address space) Legion (Standord, Los Alamos, NVidia): McCormick, Aiken, Bauer (coarsegrain tasks, runtime dep analysis, strong data model) Charm++ (UIUC): Kale (actor model) Directives: OpenMP, OmpSs New languages: Chapel (Cray): global address space language Regent (Stanford): expressive interface to Legion based on Terra, Lua Some polyhedral work R-stream/OCR, OSU+ Lawrence, Utah 10
11 DOE and collaborator efforts on performance portability Modern C++ (metaprogramming) Kokkos (Sandia, Edwards), Raja (Livermore, Keasler): executors, loop traversal order, data layouts, lambdas and functors) DARMA (Sandia): Janine Bennett (coarse-grain tasks, runtime dep analysis) HPX (LSU,Indiana): Hartmut Kaiser (futures, tasks, templated sync primitives) ``Regular C++ These are all general purpose programming models! UPC++ (Berkeley): Kathy Yelick (global address space) Legion (Standord, Los Alamos, NVidia): McCormick, Aiken, Bauer (coarsegrain tasks, runtime dep analysis, strong data model) Charm++ (UIUC): Kale (actor model) Directives: OpenMP, OmpSs New languages: Chapel (Cray): global address space language Regent (Stanford): expressive interface to Legion based on Terra, Lua Some polyhedral work R-stream + OCR, Ohio State + Lawrence 11
12 Programming models are economics and sociology: Maximize programming productivity and happiness Thought experiment #1: If a single computer architecture existed, would apps teams learn and write assembly? 12
13 Programming models are economics and sociology: Maximize programming productivity and happiness Thought experiment #1: If a single computer architecture existed, would apps teams learn and write assembly? No, compilers are necessary for productivity even without any concerns for portability of code 13
14 Programming models are economics and sociology: Maximize programming productivity and happiness Thought experiment #1: If a single computer architecture existed, would apps teams learn and write assembly? No, compilers are necessary for productivity even without any concerns for portability of code Thought experiment #2: If single parallel architecture existed, would apps teams want polyhedral compilers? 14
15 Programming models are economics and sociology: Maximize programming productivity and happiness Thought experiment #1: If a single computer architecture existed, would apps teams learn and write assembly? No, compilers are necessary for productivity even without any concerns for portability of code Thought experiment #2: If single parallel architecture existed, would apps teams want anything but MPI + OpenMP? Parallel app developers are experts in problem decomposition MPI not really that burdensome to write only annoying if different architecture demands different problem decompositions Kokkos,Raja,OpenMP: Not perfect, but not rate-limiting step in development Vectorization? Need broader survey of what developers find difficult Apps developers like controlling details of execution 15
16 Programming models are economics and sociology: Maximize programming productivity and happiness Thought experiment #1: If a single computer architecture existed, would apps teams learn and write assembly? No, compilers are necessary for productivity even without any concerns for portability of code Thought experiment #2: If single parallel architecture existed, would apps teams want anything but MPI + OpenMP? Parallel app developers are experts in problem decomposition MPI not really that burdensome to write only annoying if different architecture demands different problem decompositions Kokkos,Raja,OpenMP: Not perfect, but not rate-limiting step in development Vectorization? Need broader survey of what developers find difficult Apps developers like controlling details of execution Performance portability changes calculus the ``buzz word that will get app developer s attention 16
17 Conclusions: What are possible outcomes? And what can you do to influence outcomes? Outcome #1: DOE ports all of its codes to new general purpose runtime (might just be MPI + OpenMP) Outcome #2: General purpose loses quicker to just build domain-specific runtimes and models Outcome #1 is programmatically preferred, DOE doesn t want a bunch of ad hoc technologies lumped together Path forward: Sell the product current solutions not breeding mass discontent Don t oversell the product Compare compiler tools to general purpose programming models (particularly Legion, Kokkos, Raja) Use performance portability as an ice-breaker 17
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