conduit · 2019. 10. 16. · [email protected] adam kunen [email protected] core team: many other...

LLNL-PRES-697177 This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. Lawrence Livermore National Security, LLC

ConduitAScien-ficDataExchangeLibraryforHPCSimula-onsh?p://soCware.llnl.gov/conduitSciPy2016–The2016Scien0ficCompu0ngwithPythonConference

CyrusHarrison,BrianRyujin,AdamKunenWednesday July 13, 2016 Austin, Texas

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OurConduitprojectisnotfocusedondevelopingavirus(ormalware,adware,etc).

https://software.llnl.gov/conduit

Introduction

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ProjectInfo:§  Languages:C++,Python,C,Fortran

§  Docs:hEps://soGware.llnl.gov/conduit

§  GithubRepo:hEps://github.com/llnl/conduit

§  License:BSDStyle

§  Timeline:—  2011–2013:Neuronsstartfiringanddevelopingconcepts—  November2013:CodedevelopmentstartsataLLNLHackathon—  Fall2014–Spring2015:HarveyMuddClinicProject—  January2015:ReleasedOpenSource—  2015–Present:Earlyuseinapplica0onsatLLNL

Conduitisanopensourceprojectfocusedonsimplifyingin-coredataexchangeintheHPCsimula-onecosystem.

Introduction

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Conduitissmallcollabora-vedevelopmenteffortwithinLLNL’sWeaponsSimula-onandCompu-ng(WSC)program.

Cyrus Harrison [email protected]

Brian Ryujin [email protected]

Adam Kunen [email protected]

CoreTeam:

Manyotherpeoplehavecontributedideasandcode!

Introduction

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Conduitdevelopmentwasboostedbya2014-2015HarveyMuddClinicProjectexploringitsuseinHPCproxyapplica-ons.

TheHarveyMuddClinicprogramhelpedusrefineConduitforimportantusecases

Introduction

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Whatmo-vatedConduit?

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SnapshotofScaleandComplexityofLLNL’sWSCCPProgram:§ DevelopmentEfforts

— ~120Developers(Physicists,Engineers,ComputerScien0sts,SoGwareQuality,etc…)— ~15projectteams— ~15–30+yearapplica0onlife0mes— ~12millionlinesofproduc0oncodeacrossprojects(w/morethan100third-partydependencies)

§ DiversityofProgrammingLanguages— C++/C,Fortran,Python,Lua

§ DiversityofData— Scalars,Arrays,Strings— Tables,Contours— CADGeometry,Computa0onalMeshes

LLNL’sWSCComputa-onalPhysics(CP)programdevelopsproduc-onHPCmul--physicssimula-onapplica-ons.

CP’seffortsareamicrocosmofthebroaderHPCsimula0oncommunity.

Motivation

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ThesoCwareecosystemsuppor-ngHPCmul--physicssimula-onsisverycomplex.

Visualization and Analysis •  Mesh Rendering •  Feature Extraction •  Simulated Diagnostics

Problem Setup •  Computational Geometry •  Mesh Generation •  Mesh Decomposition

Uncertainty Quantification •  Ensemble Generation •  Parametric Studies •  Statistical Models

Workflow Applications

Multi-physics Simulation Applications

CS Infrastructure •  Input Parsing •  Steering •  Communication •  Parallelism Abstractions •  I/O •  In Situ Coupling

Physics Libraries •  Material Properties •  Material Models

Numerical Libraries •  Linear Algebra •  Finite Elements

Physics Packages •  Hydrodynamics •  Chemistry •  Thermal radiation •  {and many more …}

Motivation

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Visualization and Analysis Problem Setup Uncertainty Quantification



CS Infrastructure

Physics Libraries

Numerical Libraries

Physics Packages

AmixofC++,Python,FortranandLuaareusedtodevelopapplica-ons.

C++ Python

C++ Fortran

C++ Fortran

C++ Lua

Python Fortran

C++ Python

Fortran C++ Python

Lua

Python

Motivation

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Visualization and Analysis Problem Setup Uncertainty Quantification



Amixofcustominputlanguages,GUIs,PythonandLuaareusedtorunandscriptapplica-ons.

Python Python GUIs

Custom Input Language

Python

Lua

Python GUIs

Motivation

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In-coredataexchangehasreceivedlessfocusthanfile-baseddataexchange:

§  File-basedI/Olibrarieshaveevolvedintodefactointerfacesbetweencomponents.

§  File-basedI/Oisacceptableasacoarse-grainandlow-frequencydatacouplingsolu0on.

Datacouplingisakeyaspectinsimula-onsoCwaredesignanduserworkflows.

Toachievefine-graineddatacouplingweneedtoolstohelpwithin-coredataexchange.

Motivation

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KeyRequirements:

§  Provideadescrip0onmechanismfornumericprimi0ves—  Scalars,stridedarrays,etcwithexplicitprecision

§  Supportmixedmemoryownershipseman0cs—  Enablezero-copywherefeasible—  Playfriendlywithexis0ngdatastructuresinmul0plelanguages

§  Enablehigherlevelconven0ons—  Hierarchicalcontext(“paths”aregreatinterface…)—  Humanreadabledescrip0ons

Suppor-ngin-coredataexchangethroughoutthesimula-oneco-systemisquitedifferentfromtrivialsinglecomponentusecases.

Motivation

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WhatisConduit?

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Conduit’smul--languagedatamodelprovides:

§  Aflexiblewaytodescribecomplexdata—  AJSON-basedschemafordescribingthelayoutofhierarchicalin-coredata.

§  AsaneAPItoaccesscomplexdata—  DynamicAPIsforrapidconstruc0onandconsump0onofhierarchicalobjects.

Conduitprovidesasetoftoolsfocusedonin-coredatadescrip-ontoaidwithdatacouplingacrosstheHPCecosystem.

Conduitprovidesamul0-languagedatamodel,notamul0-languagewrappingsolu0on.

About Conduit

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ANodeactsasoneoffollowingbasicroles:§  Object:Anorderedassocia0vearraymappingnamestochildren

§  List:Anorderedlistofunnamedchildren

§  Leaf:Scalaror1DArrayofabitwidth-specifiedprimi0ve:—  SignedIntegers:int8,int16,int32,int64—  UnsignedIntegers:uint8,uint16,uint32,uint64—  Floa1ngPointNumbers:float32,float64—  Strings:char8_str

§  Empty:Nodata

TheheartofConduitisahierarchicalvarianttypenamedNode.

About Conduit

ExperiencewithNumPyandJSONmo0vatedConduit’sdatamodel.

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ConduitPythonAPIExample:CreateatreeofNumPydataarrays

import syssys.path.append(".")#-----------

import numpy as npfrom conduit import Node

# create a "Node", the primary actor in conduitn = Node()

# create example numpy datax_coords = np.array(range(3),dtype='float64')y_coords = np.array(range(3),dtype='float64')den = np.ones(4,dtype='float64')

#-----------

# create dynamic a tree hierarchy with a Node by # copying our numpy data into named pathsn["coords/x"] = x_coordsn["coords/y"] = y_coordsn["fields/density/values"] = den# show the treeprint(n)

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ConduitPythonAPIExample:CreateatreeofNumPydataarrays

import syssys.path.append(".")#-----------

import numpy as npfrom conduit import Node

# create a "Node", the primary actor in conduitn = Node()

# create example numpy datax_coords = np.array(range(3),dtype='float64')y_coords = np.array(range(3),dtype='float64')den = np.ones(4,dtype='float64')

#-----------

# create dynamic a tree hierarchy with a Node by # copying our numpy data into named pathsn["coords/x"] = x_coordsn["coords/y"] = y_coordsn["fields/density/values"] = den# show the treeprint(n)

{ "coords": { "x": [0.0, 1.0, 2.0], "y": [0.0, 1.0, 2.0] }, "fields": { "density": { "values": [1.0, 1.0, 1.0, 1.0] } }}

{ "u": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "v": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]}

{ "u": [3.14159, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "v": [2.71828, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]}

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ConduitPythonAPIExample:MixingexternallyallocatedandConduitowneddata

#-----------

# you can mix external and conduit owned data within a# Node hierarchyvel_u = np.ones(9,dtype='float64')vel_v = np.ones(9,dtype='float64')# use set_external() to inits the "u" and "v" nodes of # the tree to point to the same memory location as their# source numpy arraysn["fields/velocity/values/u"].set_external(vel_u)n["fields/velocity/values/v"].set_external(vel_v)

#-----------

# show the elements of the "u" arrayprint(n["fields/velocity/values"])

# change the first element of the u array (via src)vel_u[0] = 3.14159;# change the first element of the v array (via conduit)n["fields/velocity/values/v"][0] = 2.71828

# show the elements of the "u" array againprint(n["fields/velocity/values"])

#-----------

# mixed ownership semantics allow you to organize,# extend, and annotate existing data n["coords/type"] = "uniform"n["fields/density/units"] = "g/cc"n["fields/velocity/units"] = "m/s"# show the entire treeprint(n)

#-----------

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#-----------


#-----------




#-----------


#-----------

#-----------


#-----------




#-----------


#-----------


{ "u": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "v": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]}

{ "u": [3.14159, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "v": [2.71828, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]}


{ "u": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "v": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]}

{ "u": [3.14159, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "v": [2.71828, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]}

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#-----------


#-----------




#-----------


#-----------

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{ "coords": { "x": [0.0, 1.0, 2.0], "y": [0.0, 1.0, 2.0], "type": "uniform" }, "fields": { "density": { "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc" }, "velocity": { "values": { "u": [3.14159, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "v": [2.71828, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] }, "units": "m/s" } }}

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Weareaimingtoprovideintui-veC++,Python,andFortranAPIs.

Conduit Examples

den = np.ones(4,dtype='float64')

n = Node();

n["fields/density/values"] = den;n["fields/density/units"] = "g/cc";

n_density = n["fields/density"]

den_vals = n_density["values"];den_units = n_density["units"];

print(n_density)

print('\nDensity ({}):\n{}'.format(den_units, den_vals))

std::vector<float64> den(4,1.0);

Node n;n["fields/density/values"] = den;n["fields/density/units"] = "g/cc";

Node &n_density = n["fields/density"];

float64 *den_ptr = n_density["values"].value();std::string den_units = n_density["units"].as_string();

n_density.print();

std::cout <<"\nDensity (" << den_units << "):\n";

for(index_t i=0; i < 4; i++){ std::cout << den_ptr[i] << " ";}std::cout << std::endl;

do i = 1,4 den(i) = 1.0enddo

n = conduit_node_obj_create()call n%set_path_ptr("fields/density/values",den,4_8)call n%set_path("fields/density/units","g/cc")

n_den = n%fetch("fields/density")

call n_den%fetch_path_as_float64_ptr("values",d_arr)

n_den_units = n%fetch("fields/density/units")call n_den_units%as_char8_str(units)units_len = n_den_units%number_of_elements()

call n_den%print()print *,print *,"Density (",(units(i),i=1,units_len),"): "

do i = 1,4 write(*,"(f5.2,1x)",advance="no"), d_arr(i)enddoprint *

call conduit_node_obj_destroy(n)

Python C++ Fortran

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Weareaimingtoprovideintui-veC++,Python,andFortranAPIs.

Python

Conduit Examples

C++ Fortran

PY

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}

Density (g/cc):[ 1. 1. 1. 1.]

CPP

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}

Density (g/cc):1 1 1 1

FORTRAN

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}

Density (g/cc): 1.00 1.00 1.00 1.00

PY

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}

Density (g/cc):[ 1. 1. 1. 1.]

CPP

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}


FORTRAN

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}

Density (g/cc): 1.00 1.00 1.00 1.00

PY

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}

Density (g/cc):[ 1. 1. 1. 1.]

CPP

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}


FORTRAN

{ "values": [1.0, 1.0, 1.0, 1.0], "units": "g/cc"}

Density (g/cc): 1.00 1.00 1.00 1.00

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§  Completelyrun0mefocused—  Avoidsincompa0ble(orunsharable)code-genera0onsolu0ons

§  Emphasizesdatadescrip0onasacorecapability—  Doesnotrequirerepacking—  Providesafounda0ononwhichtobuildserializa0on,I/O,andmessagingfeatures

§  Providesamul0-languagedatamodel—  CurrentlyincludesAPIsforC++,Python,C,andFortran—  JSONfriendly

ConduitwasdesignedwithsoCwareengineeringecosystemlogis-csinmind.

Philosophy:Sharedatawithoutmassivecodeinfrastructure.

About Conduit

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Supports shared higher level conventions for using Conduit to represent data.

•  Computational Meshes •  Multi-Component Arrays

Implements interfaces to Conduit’s in-core data model. •  Core Objects •  JSON parsing •  Basic I/O •  Basic transforms

Provides advanced I/O features built on top of Conduit’s data model. •  HDF5 •  MPI •  WebSockets

Conduit’sRelayandBlueprintlibrariesprovidefeaturesbuiltontopofConduit’scoredatamodel.

Conduit Relay Blueprint

About Conduit

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WhereareweusingConduit?

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Ourcurrentproduc-onsimula-oncodeprojectsdevelopandmaintaintheirownCSinfrastructure.










Uses of Conduit


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LLNL’sASCCSToolkitisanewprojectworkingtorefineandshareCSinfrastructureacrosssimula-onapplica-ons.






CS Infra.




CS Infrastructure •  Data Management •  Communication •  Parallelism Abstractions •  I/O •  In Situ Coupling

ASC CS Toolkit

Uses of Conduit

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Simula-oncomponentswillusetheASCCSToolkitandcommonconven-onstosharedata.

Mesh Fields

Mesh

Physics A

Mesh Fields

Mesh

Hydro B

Tools and Libraries Toolkit Components Physics Packages

Blueprint (“Mesh-aware”

data description)

Conduit (In-core data schemas)

Sidre (Datastore)

(Manages data shared by applications, Toolkit, tools, etc.)

ASC CS Toolkit “Core”

Relay (HDF5 I/O)

Uses of Conduit

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LLNLisdevelopinganewcode,MARBL,whichemploystwomodularhydrodynamicsalgorithms.

BLAST is an unstructured mesh finite element ALE code that uses high-order elements and geometry

MIRANDA is a structured mesh Eulerian code that uses high-order finite difference methods

MARBL will be the first application to incorporate the data management and I/O features of the ASC CS Toolkit.

Uses of Conduit

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Strawmanisanproxyapplica-onforinsiturenderinginmesh-basedHPCsimula-ons.

LULESH Kripke CloverLeaf3D Hydrodynamics Neutron Transport Hydrodynamics

Unstructured Uniform Rectilinear

C++ C++ Fortran

Strawman

Simulation

ConduitIn-CoreDataDescrip0on

In Situ Pipelines

EAVL,VTK-mDataModel+Rendering

MeshData Actions

IceTParallelCompositing

StreamingWebClientImageFilesImageFilesImageFiles

RenderedImages

Publish Execute

Uses of Conduit

Examplerendersfrombuilt-insamplesimula-ons:

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StrawmanusesConduittodescribeandpasssimula-onmeshdatastructurestoMPI+Xrenderingpipelines.

Strawman

Simulation

ConduitIn-CoreDataDescrip0on

In Situ Pipelines

EAVL,VTK-mDataModel+Rendering

MeshData Actions

IceTParallelCompositing

StreamingWebClientImageFilesImageFilesImageFiles

RenderedImages

Publish Execute

Example:DescribingmeshdatausingConduit(C++):

Uses of Conduit

conduit::Node data;data["state/time"].set_external(&time);data["state/cycle"].set_external(&cycle);data["state/domain"] = my_mpi_rank;data["coords/type"] = "explicit";data["coords/x"].set_external(x);data["coords/y"].set_external(y);data["coords/z"].set_external(z);data["topology/type"] = "unstructured";data["topology/coordset"] = "coords";data["topology/elements/shape"] = "hexs";data["topology/elements/connectivity"].set_external(nodelist);data["fields/e/association"] = "element";data["fields/e/type"] = "scalar";data["fields/e/values"].set_external(e);

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Conduitisanopensourceprojectfocusedonsimplifyingin-coredataexchangeintheHPCsimula-onecosystem.ProjectInfo:

§  Docs:hEps://soGware.llnl.gov/conduit

§  Repo:hEps://github.com/llnl/conduit

§  License:BSDStyle

ContactInfo:

§  CyrusHarrison([email protected])

§  BrianRyujin([email protected])

§  AdamKunen([email protected])

Conduitisaworkinprogress!

§  FutureWork:—  UsingConduitinHPCapplica0ons—  ExpandingAPISupport

•  CurrentState:C++>Python>C/Fortran

•  Lua(?)

—  RefiningRelayandBlueprint—  Windowssupport—  Binarydistribu0ons(?)

Conclusion

conduit · 2019. 10. 16. · [email protected] adam kunen [email protected] core team: many other...

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