Scientific Components and Frameworks

Transcription

1 High Performance Computing: Concepts, Methods & Means Scientific Components and Frameworks Prof. Daniel S. Katz Department of Electrical and Computer Engineering Louisiana State University April 24 th, 2007 AT LOUISIANA STATE UNIVERSITY

2 Opening Remarks Context: high performance computing May have multiple types of physics May have multiple spatial scales May have multiple time scales May use multiple solvers May need multiple I/O libraries May need multiple visualization interfaces Need to build real, working, complex applications How?

3 Topics Meat Grinder Introduction (slides from Gary Kumfert, part of CCA tutorial) Common Component Architecture (CCA) Cactus Earth System Modeling Framework (ESMF) Summary 3

4 A Pictorial Introduction to Components in Scientific Computing

5 Once upon a time... Input Output Program 5

6 6 As Scientific Computing grew...

7 7 Tried to ease the bottle neck

8 SPMD was born

9 SPMD worked. 1 2 But it isn t easy!!!

10 Meanwhile, corporate computing was growing in a different way Input Input client browser spreadsheet graphics Output editor multimedia Unicode Program database 10

11 This created a whole new set of problems complexity 11 client browser editor multimedia spreadsheet graphics Unicode database Interoperability across multiple languages Interoperability across multiple platforms Incremental evolution of large legacy systems (esp. w/ multiple 3rd party software)

12 Component Technology addresses these problems 12

13 So what s a component??? Implementation : No Direct Access Interface Access : Generated by Tools 13 Matching Connector : Assigned by Framework Hidden from User

14 1. Interoperability across multiple languages C Language & Platform independent interfaces C++ F77 Java 14 Python Automatically generated bindings to working code

15 2. Interoperability Across Multiple Platforms Imagine a company migrates to a new system, OS, etc. 15 What if the source to this one part is lost???

16 Transparent Distributed Computing These wires are very, very smart! internet internet 16

17 3. Incremental Evolution With Multiple 3rd party software v 1.0 v 2.0 v

18 Now suppose you find this bug... v 1.0 v 2.0 v

19 Good news: an upgrade available Bad news: there s a dependency v v 2.0 v

20 Great News: Solvable with Components v

21 Great News: Solvable with Components 2.0 v v

22 Why Components for Scientific Computing Complexity 22 DataFoundry SAMRAI JEEP Sapphire Scientific Viz Ardra Overture nonlinear solvers linear solvers ALPS hypre Interoperability across multiple languages Interoperability across multiple platforms Incremental evolution of large legacy systems (esp. w/ multiple 3rd party software)

23 The Model for Scientific Component Programming Science Industry?CCA 23

24 Topics Meat Grinder Introduction Common Component Architecture (CCA) Cactus Earth System Modeling Framework (ESMF) Summary 24

25 CCA Motivation: Modern Scientific Software Engineering Challenges Productivity Time to first solution (prototyping) Time to solution ( production ) Software infrastructure requirements ( other stuff needed ) Complexity Increasingly sophisticated models Model coupling multi-scale, multi-physics, etc. Interdisciplinarity Performance Increasingly complex algorithms Increasingly complex computers Increasingly demanding applications

26 Motivation: For Library Developers People want to use your software, but need wrappers in languages you don t support Many component models provide language interoperability Discussions about standardizing interfaces are often sidetracked into implementation issues Components separate interfaces from implementation You want users to stick to your published interface and prevent them from stumbling (prying) into the implementation details Most component models actively enforce the separation

27 Motivation: For Application Developers and Users You have difficulty managing multiple third-party libraries in your code You (want to) use more than two languages in your application Your code is long-lived and different pieces evolve at different rates You want to be able to swap competing implementations of the same idea and test without modifying any of your code You want to compose your application with some other(s) that weren t originally designed to be combined

28 Some Observations About Software The complexity of software is an essential property, not an accidental one. [Brooks] We can t get rid of complexity Our failure to master the complexity of software results in projects that are late, over budget, and deficient in their stated requirements. [Booch] We must find ways to manage it A complex system that works is invariably found to have evolved from a simple system that worked A complex system designed from scratch never works and cannot be patched up to make it work. [Gall] Build up from simpler pieces The best software is code you don t have to write [Jobs] Reuse code wherever possible

29 Component-Based Software Engineering CBSE methodology is emerging, especially from business and internet areas Software productivity Provides a plug and play application development environment Many components available off the shelf Abstract interfaces facilitate reuse and interoperability of software Software complexity Components encapsulate much complexity into black boxes Plug and play approach simplifies applications Model coupling is natural in component-based approach Software performance (indirect) Plug and play approach and rich off the shelf component library simplify changes to accommodate different platforms

30 A Simple Example: Numerical Integration Components Interoperable components (provide same interfaces) FunctionPort IntegratorPort FunctionPort NonlinearFunction MidpointIntegrator FunctionPort GoPort Driver IntegratorPort LinearFunction FunctionPort IntegratorPort FunctionPort RandomGeneratorPort MonteCarloIntegrator PiFunction RandomGeneratorPort RandomGenerator

31 Many Applications are Possible Dashed lines indicate alternate connections IntegratorPort FunctionPort FunctionPort NonlinearFunction MidpointIntegrator FunctionPort GoPort Driver IntegratorPort LinearFunction FunctionPort Create different applications in "plug-and-play" fashion IntegratorPort FunctionPort RandomGeneratorPort MonteCarloIntegrator PiFunction RandomGeneratorPort RandomGenerator

32 The Sociology of Components Components need to be shared to be truly useful Sharing can be at several levels Source, binaries, remote service Various models possible for intellectual property/licensing Components with different IP constraints can be mixed in a single application Peer component models facilitate collaboration of groups on software development Group decides overall architecture and interfaces Individuals/sub-groups create individual components

33 Who Writes Components? Everyone involved in creating an application can/should create components Domain scientists as well as computer scientists and applied mathematicians Most will also use components written by other groups Allows developers to focus on their interest/specialty Get other capabilities via reuse of other s components Sharing components within scientific domain allows everyone to be more productive Reuse instead of reinvention As a unit of publication, a well-written and tested component is like a high-quality library Often a more appropriate unit of publication/recognition than an entire application code

34 CCA Concepts: Components IntegratorPort FunctionPort FunctionPort MidpointIntegrator NonlinearFunction Components are a unit of software composition Composition is based on interfaces (ports) Components provide/use one or more ports A component with no ports isn t very interesting Components interact via ports; implementation is opaque to the outside world Components include some code which interacts with the CCA framework The granularity of components is dictated by the application architecture and by performance considerations Components are peers Application architecture determines relationships

35 What is a Component Architecture? A set of standards that allows: Multiple groups to write units of software (components) And have confidence that their components will work with other components written in the same architecture These standards define The rights and responsibilities of a component How components express their interfaces The environment in which are composed to form an application and executed (framework) The rights and responsibilities of the framework

36 CCA Concepts: Frameworks The framework provides the means to hold components and compose them into applications The framework is often application s main or program Frameworks allow exchange of ports among components without exposing implementation details Frameworks provide a small set of standard services to components BuilderService allow programs to compose CCA apps Frameworks may make themselves appear as components in order to connect to components in other frameworks Currently: specific frameworks support specific computing models (parallel, distributed, etc.). Future: full flexibility through integration or interoperation

37 CCA Concepts: Ports IntegratorPort FunctionPort FunctionPort MidpointIntegrator NonlinearFunction Components interact through well-defined interfaces, or ports In OO languages, a port is a class or interface In Fortran, a port is a bunch of subroutines or a module Components may provide ports implement the class or subroutines of the port ( Provides Port ) Components may use ports call methods or subroutines in the port ( Uses Port ) Links denote a procedural (caller/callee) relationship, not dataflow! e.g., FunctionPort could contain: evaluate(in Arg, out Result)

38 Interfaces, Interoperability, and Reuse Interfaces define how components interact Therefore interfaces are key to interoperability and reuse of components In many cases, any old interface will do, but General plug and play interoperability requires multiple implementations providing the same interface Reuse of components occurs when they provide interfaces (functionality) needed in multiple applications

39 Designing for Reuse, Implications Designing for interoperability and reuse requires standard interfaces Typically domain-specific Standard need not imply a formal process, may mean widely used Generally means collaborating with others Higher initial development cost (amortized over multiple uses) Reuse implies longer-lived code thoroughly tested highly optimized improved support for multiple platforms

40 Relationships: Components, Objects, and Libraries Components are typically discussed as objects or collections of objects Interfaces generally designed in OO terms, but Component internals need not be OO OO languages are not required Component environments can enforce the use of published interfaces (prevent access to internals) Libraries can not It is possible to load several instances (versions) of a component in a single application Impossible with libraries Components must include some code to interface with the framework/component environment Libraries and objects do not

41 Domain-Specific Frameworks vs Generic Component Architectures Domain-Specific Often known as frameworks Provide a significant software infrastructure to support applications in a given domain Often attempts to generalize an existing large application Often hard to adapt to use outside the original domain Tend to assume a particular structure/workflow for application Relatively common Generic Provide the infrastructure to hook components together Domain-specific infrastructure can be built as components Usable in many domains Few assumptions about application More opportunities for reuse Better supports model coupling across traditional domain boundaries Relatively rare at present Commodity component models often not so useful in HPC scientific context

42 Special Needs of Scientific HPC Support for legacy software How much change required for component environment? Performance is important What overheads are imposed by the component environment? Both parallel and distributed computing are important What approaches does the component model support? What constraints are imposed? What are the performance costs? Support for languages, data types, and platforms Fortran? Complex numbers? Arrays? (as first-class objects) Is it available on my parallel computer?

43 What is the CCA? (User View) A component model specifically designed for high-performance scientific computing Supports both parallel and distributed applications Designed to be implementable without sacrificing performance Minimalist approach makes it easier to componentize existing software

44 What is the CCA? (2) Components are peers Not just a dataflow model A tool to enhance the productivity of scientific programmers Make the hard things easier, make some intractable things tractable Support & promote reuse & interoperability Not a magic bullet

45 Importance of Provides/Uses Pattern for Ports Fences between components Components must declare both what they provide and what they use Components cannot interact until ports are connected No mechanism to call anything not part of a port Ports preserve high performance direct connection semantics While also allowing distributed computing Component 1 Component 2 Component 1 Provides/Uses Port Direct Connection Provides Port Network Connection Component 2 Uses Port

46 CCA Concepts: Framework Stays Out of the Way of Component Parallelism Single component multiple data (SCMD) model is component analog of widely used SPMD model Each process loaded with the same set of components wired the same way Different components in same process talk to each other via ports and the framework Same component in different processes talk to each other through their favorite communications layer (i.e. MPI, PVM, GA) P0 P1 P2 P3 Components: Blue, Green, Red Framework: Gray MCMD/MPMD also supported Other component models ignore parallelism entirely

47 CCA Concepts: MxN Parallel Data Redistribution Share Data Among Coupled Parallel Models Disparate Parallel Topologies (M processes vs. N) e.g. Ocean & Atmosphere, Solver & Optimizer e.g. Visualization (Mx1, increasingly, MxN) Research area -- tools under development

48 CCA Concepts: Language Interoperability Existing language interoperability approaches are pointto-point solutions f77 Babel provides a unified approach in which all languages are considered peers Babel used primarily at interfaces f77 C f90 C f90 C++ Python C++ Babel Python Java Few other component models support all languages and data types important for scientific computing Java

49 What the CCA isn t CCA doesn t specify who owns main CCA components are peers Up to application to define component relationships Driver component is a common design pattern CCA doesn t specify a parallel programming environment Choose your favorite Mix multiple tools in a single application CCA doesn t specify I/O But it gives you the infrastructure to create I/O components CCA doesn t specify interfaces But it gives you the infrastructure to define and enforce them CCA Forum supports & promotes standard interface efforts CCA doesn t require (but does support) separation of algorithms/physics from data

50 What the CCA is CCA is a specification for a component environment Fundamentally, a design pattern Multiple reference implementations exist Being used by applications CCA increases productivity Supports and promotes software interoperability and reuse Provides plug-and-play paradigm for scientific software CCA offers the flexibility to architect your application as you think best Doesn t dictate component relationships, programming models, etc. Minimal performance overhead Minimal cost for incorporation of existing software CCA provides an environment in which domain-specific application frameworks can be built While retaining opportunities for software reuse at multiple levels

51 Review of CCA Terms & Concepts Ports Interfaces between components Uses/provides model Framework Allows assembly of components into applications Direct Connection Maintain performance of local inter-component calls Parallelism Framework stays out of the way of parallel components MxN Parallel Data Redistribution Model coupling, visualization, etc. Language Interoperability Babel, Scientific Interface Definition Language (SIDL)

52 CCA Summary Components are a software engineering tool to help address software productivity and complexity Important concepts: components, interfaces, frameworks, composability, reuse Scientific component environments come in domain specific and generic flavors Scientific HPC imposes special demands on component environments which commodity tools may have trouble with The Common Component Architecture is specially designed for the needs of HPC CCA is a research project - intended to be quite general - not heavily used yet in production

53 Topics Meat Grinder Introduction Common Component Architecture (CCA) Cactus (slides from Tom Goodale) Earth System Modeling Framework (ESMF) Summary 53

54 What Is Cactus? Cactus is a framework for developing portable, modular applications, in particular, although not exclusively, highperformance simulation codes. Cactus is designed to allow experts in different fields to develop modules based upon their expertise and to leverage off modules developed by experts in other fields to perform their work, with minimal knowledge of the internals or operation of the other modules. This enables it to be used in large, geographically dispersed, collaborations. Cactus and the Cactus Computational Toolkit are Open Source and freely available.

55 Cactus Goals Portable Modular People can write modules that interact through standard interfaces with other modules without knowing internals of the other modules Modules with same functionality are interchangeable Support legacy codes Make use of existing technologies and tools where appropriate Future proof Not tied to any particular paradigm Parallelism is independent but compatible with MPI or PVM I/O system is independent but compatible with HDF or others Easy to use Maintainable

56 Cactus History First developed in 1997 by Paul Walker, Joan Masso, and others, as a continuation of a long line of numerical relativity codes, such as the NCSA G-code and Paul's Framework In first years, Cactus became progressively more modular, allowing modules for different formulations of Einstein's equations and different physical systems Although in principle Cactus was modular, its history and evolution had left many dependencies between modules and between the core and the modules Cactus 4.0 (current) is complete redesign of core -- moved everything possible out into modules, and put structures in place to enable modules to be far more independent

57 Current Cactus Users Numerical Relativity Used by many groups including: AEI (Germany), UNAM (Mexico), Tuebingen (Germany), Southampton (UK), Sissa (Italy), Valencia (Spain), U. of Thessaloniki (Greece), MPA (Germany), RIKEN (Japan), TAT (Denmark), Penn State, U. of Texas at Austin, U. of Texas at Brownsville, LSU (USA), Wash, U. of Pittsburgh, U. of Arizona, Washburn, UIB (Spain), U. of Maryland, Monash (Australia) Quantum Gravity Coastal and Climate Modeling CFD KISTI DLR looking at flow in turbines Lattice Boltzmann Over 150 Science Papers Over 30 Student Theses

58 Cactus Structure Cactus source code consists of core part, the Flesh, and set of modules, the Thorns Flesh Independent of all thorns After initialization, acts as a utility and service library that the thorns call to get information or ask for some action to happen Thorns Separate libraries that encapsulate some functionality In order to keep a distinction between functionality and implementation of the functionality, each thorn declares that it provides a certain implementation Different thorns can provide the same implementation, and thorn dependencies are expressed in terms of implementations rather than explicit references to thorns, thus allowing the different thorns providing the same implementation to be interchangeable

59 Structure Plug-In Thorns (modules) driver input/output interpolation parameters Core Flesh error handling extensible APIs ANSI C scheduling make system remote steering Fortran/C/C++ equations of state black holes SOR solver grid variables boundary conditions wave evolvers multigrid coordinates

60 Cactus Flesh Make System API Organizes builds as configurations which hold everything needed to build with a particular set of options on a particular architecture Functions which must be there for thorns to operate Scheduling Sophisticated scheduler which calls thorn-provided functions as and when needed CCL Configuration language which tells the flesh all it needs to know about the thorns

61 Thorn Specification The Flesh finds out about thorns by configuration files in each thorn These files are converted at compile time into a set of routines the Flesh can call to find out about thorns There are three such files Scheduling directives The flesh incorporates a scheduler which is used to call defined routines from different thorns in a particular order Interface definitions All variables which are passed between scheduled routines need to be declared Any thorn-provided functions which other thorns call should be declared Parameter definitions The flesh and thorns are controlled by a parameter file; parameters must be declared along with their allowed values

62 Scheduling Thorns specify which functions are to be called at which time, and in which order Rule-based scheduling system Routines are either before or after other routines (or don't care) Routines can be grouped, and whole group scheduled Functions or groups can be scheduled while some condition is true Flesh sorts all rules and flags an error for inconsistent schedule requests

63 The Driver Layer In principle, drivers are the only thorns which know anything about parallelism Other thorns access parallelism via an API provided by the flesh Underlying parallel layer could be anything from a TCP-socket to Java RMI -- should be transparent to application thorns Could even be a combination of things Can even run with no parallel layer at all Can pick actual driver to use at runtime - no need to recompile code to test differences between parallel layers Can take one executable and use whatever the best layer for any particular environment happens to be

64 Current Drivers There are several drivers available at the moment, both developed by the cactus team and by the community. PUGH a parallel uni-grid driver, which comes as part of the the computational toolkit PAGH a parallel AMR driver which uses the GrACE library for grid hierarchy management Carpet a parallel fixed mesh refinement driver SimpleDriver a simple demonstration driver which illustrates driver development

65 Cactus Computational Toolkit Core thorns which provide many basic utilities, such as: Boundary conditions I/O methods Reduction and Interpolation operations Coordinate Symmetries Parallel drivers Elliptic solvers Web-based interaction and monitoring interface...

66 Current Capabilities: Methods Almost all codes in Cactus are explicit finite difference codes on structured meshes In principle, finite volume or finite element on structured meshes is possible There is now a generic method-of-lines thorn which makes developing thorns using such methods very quick and easy Interface for elliptic solvers and support for generic elliptic solver packages such as PETSc as well as a numericalrelativity-specific multigrid solver written by Bernd Bruegmann However, interface is not as generic as it could be, and it may not be too useful as it stands for solving general implicit problems

67 Current Capabilities: Interaction HTTPD thorn provides interface that allows web browser to connect to running simulation Allows a user to examine state of running simulation and change parameters, such as frequency of I/O or variables to be output, or any other parameter that thorn author declared may be changed during the simulation These capabilities may be extended by any other thorn E.g. the HTTPDExtra thorn allows the user to download any file output by the I/O thorns in the Computational toolkit, and even to view twodimensional slices as jpegs Also, there is helper script for web browsers that allows appropriate visualization tool to be launched when a user requests a file

68 Cactus Summary Used to build apps in NumRel, and starting to be used in other fields Flesh/Thorns distinction Flesh is like CCA Framework + some general components Thorns are like CCA components Production code for certain domains, well-used and well-tested

69 Topics Meat Grinder Introduction Common Component Architecture (CCA) Cactus Earth System Modeling Framework (ESMF) - slides from ESMF tutorial Summary 69

70 ESMF Motivation and Context In climate research and NWP... increased emphasis on detailed representation of individual physical processes; requires many teams of specialists to contribute components to an overall modeling system In computing technology... increase in hardware and software complexity in highperformance computing, as we shift toward the use of scalable computing architectures In software development of first-generation frameworks, such as FMS, GEMS, CCA and WRF, that encourage software reuse and interoperability

71 What is ESMF? ESMF provides tools for turning model codes into components with standard interfaces and standard drivers. ESMF provides data structures and common utilities that components use for routine services such as data communications, regridding, time management and message logging. ESMF Superstructure AppDriver Component Classes: GridComp, CplComp, State User Code ESMF Infrastructure Data Classes: Bundle, Field, Grid, Array Utility Classes: Clock, LogErr, DELayout, Machine ESMF GOALS 1. Increase scientific productivity by making model components much easier to build, combine, and exchange, and by enabling modelers to take full advantage of high-end computers. 2. Promote new scientific opportunities and services through community building and increased interoperability of codes (impacts in collaboration, code validation and tuning, teaching, migration from research to operations)

72 Application Example: GEOS-5 AGCM GEOS-5 coupler Each box is an agcm ESMF component coupler history Every component dynamics physics has a standard coupler coupler interface so that it is swappable gravity_wave_drag fvcore surface Data in and out of coupler components are packaged lake land_ice data_ocean land infrared as state types with user-defined fields coupler New components can be added to the system vegetation catchment Each ESMF application is also a Gridded Component Entire ESMF applications can be nested within larger applications This strategy can be used to systematically compose very large, multicomponent codes. Coupling tools include regridding and redistribution methods chemistry moist_processes radiation turbulence coupler solar

73 Design Strategies Modularity Gridded Components don t have access to the internals of other Gridded Components, and don t store any coupling information Gridded Components pass their States to other components through their argument list. Components can be used standalone or coupled with others into a larger application. Flexibility Users write their own drivers as well as their own Gridded Components and Coupler Components -- Users decide on their own control flow Communication All communication handled within components. If an atmosphere is coupled to an ocean, Coupler Component is defined on both atmosphere and ocean processors. The same programming interface is used for shared memory, distributed memory, and combinations thereof. This buffers the user from variations and changes in the underlying platforms.

74 Elements of Parallelism: Serial vs. Parallel Computing platforms can have multiple processors, some or all of which may share the same memory pools Can be multiple Persistent Execution Threads (PETs) Can be multiple PETs per processor Software like MPI and OpenMP commonly used for parallelization Programs can run in a serial fashion, with one PET, or in parallel, using multiple PETs Often, a PET can be thought of as a processor Sets of PETs are represented by Virtual Machines (VMs)

75 Elements of Parallelism: Sequential vs. Concurrent In sequential mode components run one after the other on the same set of PETs. PETs In concurrent mode components run at the same time on different sets of PETs PETs T i m e AppDriv er ( Main ) Call Run T i m e AppDriver ( Main ) Call Run Run GridComp Hurricane Model Run LOOP Call Run GridComp Hurricane Model Run LOOP Call Run GridComp Atmosphere Run Run Run GridComp Atmosphere GridComp Ocean GridComp Ocean Run Run CplComp Atm-Ocean Coupler CplComp Atm-Ocean Coupler

76 Elements of Parallelism: DEs Data decomposition represented as set of Decomposition Elements (DEs) Sets of DEs are represented by the DELayout class DELayouts define how data is mapped to PETs In many applications there is one DE per PET Temperature Field T T1 T10 T19 T28 T2 T11 T20 T29 T3 T12 T21 T30 T4 T13 T22 T31 T5 T14 T23 T32 T6 T15 T24 T33 T7 T16 T25 T34 T8 T17 T26 T35 T9 T18 T27 T36 4 x 9 f ield x 9 DELay out DEs VM with 9 PETs PETs

77 Modes of Parallelism: Single vs. Multiple Executable In Single Program Multiple Datastream (SPMD) mode the same program runs across all PETs in the application - components may run sequentially or concurrently. In Multiple Program Multiple Datastream (MPMD) mode the application consists of separate programs launched as separate executables - components may run concurrently or sequentially, but in this mode almost always run concurrently

78 Classes and Objects in ESMF The ESMF Application Programming Interface (API) based on object-oriented programming notion of class A software construct that s used for grouping a set of related variables together with the subroutines and functions that operate on them They help to organize the code, and often make it easier to maintain and understand. A particular instance of a class is an object For example, Field is an ESMF class An actual Field called temperature is an object

79 ESMF Class Structure GridComp Land, ocean, atm, model State Data imported or exported Bundle Collection of fields Field Physical field, e.g. pressure Grid LogRect, Unstruct, etc. CplComp Xfers between GridComps Regrid Computes interp weights Superstructure Infrastructure Array Hybrid F90/C++ arrays PhysGrid Math description DistGrid Grid decomposition DELayout Communications Route Stores comm paths F90 C++ Data Utilities Virtual Machine, TimeMgr, LogErr, IO, ConfigAttr, Base etc. Communications

80 ESMF Superstructure Classes Gridded Component Models, data assimilation systems - real code Coupler Component Data transformations and transfers between Gridded Components State Packages of data sent between Components Can be Bundles, Fields, Arrays, States, or nameplaceholders Application Driver Generic driver

81 ESMF Components Component has two parts One supplied by ESMF - an ESMF derived type that is either a Gridded Component or a Coupler Component One supplied by the user Gridded Component typically represents a physical domain in which data is associated with one or more grids - for example, a sea ice model Coupler Component arranges and executes data transformations and transfers between one or more Gridded Components. Gridded Components and Coupler Components have standard methods, which include initialize, run, and finalize

82 ESMF Infrastructure Data Classes Model data is contained in a hierarchy of multi-use classes The user can reference a Fortran array to an Array or Field, or retrieve a Fortran array out of an Array or Field. Array holds a Fortran array (with other info, such as halo size) Field holds an Array, an associated Grid, and metadata Bundle collection of Fields on the same Grid bundled together for convenience, data locality, latency reduction during communications Supporting these data classes is the Grid class, which represents a numerical grid

83 Application Driver Small, generic program that contains the main for an ESMF application.

84 ESMF Communications Halo Updates edge data for consistency between partitions Redistribution No interpolation, only changes how the data is decomposed Regrid Based on SCRIP package from Los Alamos Methods include bilinear, conservative Bundle, Field, Array-level interfaces

85 ESMF Utilities Time Manager Configuration Attributes (replaces namelists) Message logging Communication libraries Regridding library (parallelized, on-line SCRIP) I/O (barely implemented) Performance profiling (not implemented yet, may simply use Tau)

86 ESMF Summary Developed for and by climate community Sandwich model EMSF provides superstructure and infrastructure, user provides filling Used for some applications, and increasingly, apps are written using it Mostly Fortran-based (user community requirement), and CCA compatible

87 Summary Material for the Test CCA Motivations: slides Component based Software Engineering: slide 29 CCA Concepts: slides What is Cactus: slides 54,55,57 Cactus Architecture: slides Cactus, current capabilities: slides 66,67 What is ESMF: slides 70,71 Design concepts in ESMF: slides ESMF Architectural Components: slides 78-85

88 URLs Common Component Architecture (CCA) Cactus Earth System Modeling Framework (ESMF) 88

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