November 1999

CHAIMS 1

Compiling High-level AccessInterfaces for Multi-site Software Stanford University

Objective: Investigate revolutionary approaches to large-scale software composition.

Approach: Develop & validate a composition-only language.

Contributions and plans: • Hardware and software platform independence.• Asynchrony by splitting up CALL-statement.• Performance optimization by invocation scheduling.• Potential for multi-site dataflow optimization.

www-db.stanford.edu/CHAIMS

CHAIMS: Mega-Programming Research

CHAIMS

November 1999

CHAIMS 2

Presentation

• Motivation and Objectives

– changes in software production

– basis for new visions and education

• Concepts of CHAIMS

– CHAIMS language

– CHAIMS architecture and composition process

– Scheduling

– Dataflow optimization

• Status, Plans, Conclusions

November 1999

CHAIMS 3

Coding

Integration

1970 1990 2010

Shift in Programming Tasks

November 1999

CHAIMS 4

Hypotheses• After the Y2K effort no large software app-

lications will be written from the ground up. They will always be composed using existing legacy code.

• Composition requires functionalities not available in current mainstream programming languages.

• Large-scale systems enable and require different optimizations.

• Composition programmers will use different tools from base programmers. (type A versus type B -- [Belady]

November 1999

CHAIMS 5

Languages & Interfaces• Large languages intended to support coding

and composition have not been successful– Algol 68– PL/1– Ada– CLOS

• Databases are being successfully composed, using Client-server, Mediator architectures

– distribution -- exploit network capabilities

– heterogeneity -- autonomy creates heterogneity

– simple schemas -- some human interpretation

– service model -- public and commercial sources

in use: C, C++, Fortran, Java

November 1999

CHAIMS 6

Typical Scenario: LogisticsA general has to ship troops and/or equipment

from San Diego NOSC to Washington DC:

– at different times ship different kind of materiel: » criteria for suitable means of transport differ

– not every airport equally suited– congestion, prices– actual weather– certain due or ready dates

Today: call different companies, look up information on the web, make reservations one-by-one

Tomorrow: system proposes shipping methods that take many conditions into account

» hand-coded systems

» composition of processes

November 1999

CHAIMS 7

C H A I M S

Megamodules

Megaprogram for composition, written by domain programmer

CHAIMS system automates generation of client for

distributed system

Megamodules, provided by various megamodule

providers

CHAIMS

November 1999

CHAIMS 8

Megamodules - DefinitionMegamodules are large, autonomous, distributed,

heterogeneous services or processes.• large: computation intensive, data intensive, ongoing

processes (monitoring of the real world, simulation services)

• distributed: remote, available to more than one client

• heterogeneous: a variety of languages and systems accessible by various distribution protocols

• autonomous: maintenance and control over recourses remains with provider, differing ontologies ( ==> SKC)

Examples:– logistics: “find best transportation from A to B”, reservation systems

– genomics: compose various analysis tools (now manual control)

November 1999

CHAIMS 9

Architecture for today: Fat Clients Domain expert

Client computer

Control &Computation

Services

I/O

a bc

de

Wrappers to resolve

differences

I/O

DataResources

November 1999

CHAIMS 10

Service Architecture: Thin Clients Domain expert

Client workstation

ComputationServices

IO module

MEGA modules

IO module

a

b

cd

e

DataResources

Sites RT

S U T

C

November 1999

CHAIMS 11

Issues in Heavy-weight ServicesServices are not free for a client:

• execution time of a service

• transfer time for data

• fees for services ?

What the client applications need:==> monitoring progress of a service

==> allow choice among equivalent services based on estimated waiting time and fees

==> high performance due to parallelism among distributed remote services

==> preliminary overview results, information to select level of accuracy / results size

==> effective optimization techniques

November 1999

CHAIMS 12

Challenge in the new world:Empower Non-technical Domain Experts

Company providing services:• domain experts of domain of service (e.g. weather)

• technical experts for programming for distribution protocols, setting up servers in a middleware system

• marketing experts

“Megaprogrammer”:• is domain expert of domain that uses these services

• is not technical expert of middleware system or experienced programmer,

• wants to focus on problem at hand (=results of using megaprogram)

• e.g. scientist, logistics officer

November 1999

CHAIMS 13

A purely compositional language?

Which languages did succeed?– Algol, ADA: integrated composition and computation

– C, C++ focus on computation

Why a new language?– complexity: not all facilities of a common language

(compare to approach of Java),

– inhibiting traditional computational programming (compare C++ and Smalltalk concerning object-oriented programming)

– focus on issue of composition, parallelism by natural asynchrony, and novel optimizations

November 1999

CHAIMS 14

CHAIMS “Logical” Architecture

Customer

Megaprogramclients(in CHAIMS)

Network/Transport(DCE, CORBA,...)

Megamodules(Wrapped or Native)

November 1999

CHAIMS 15

CHAIMS Physical Architecture

Network CORBA, JAVA RMI,

DCE, DCOM...

MegaprogramClients in CHAIMS

Megamodules (wrapped, native) each supportingsetup, estimate, invoke, examine, extract, and terminate.

November 1999

CHAIMS 16

CALL statements - growth & split

Copying Code sharing

Parameterized computation

Objects with overloaded method names

Remote procedure calls to distributed modules

Constrained (black box) access to encapsulated data

progressin

scale ofcomputing

ExtractInvokeEstimate ExamineSetup

CHAIMSdecomposes CALL functions

CALL gainedfunctionality

November 1999

CHAIMS 17

CHAIMS Primitives

Pre-invocation:SETUP: set up the connection to a megamodule

SET-, GETATTRIBUTES: set global parameters in a megamodule

ESTIMATE: get estimate of execution time for optimization

Invocation and result gathering:INVOKE: start a specific method

EXAMINE: test status of an invoked method

EXTRACT: extract results from an invoked method

Termination:TERMINATE: terminate a method invocation or a connection to

a megamodule

Control: Utility:WHILE, IF GETPARAM: get default parameters

November 1999

CHAIMS 18

Megaprogram Example: Overview

InputOutput- Input- Output

RouteInfo- AllRoutes- CityPairList- ...

AirGround- CostForGround- CostForAir- ...

Routing- BestRoute- ...

RouteOptimizer- Optimum- ...

General I/O-megamodule» Input function takes as parameter a default

data structure containing names, types and default values for expected input

Travel information:» Computing all possible routes between

two cities

» Computing the air and ground cost for each leg given a list of city-pairs and data about the goods to be transported

Two megamodules that offer equivalent functions for calculating optimal routes

» Optimum and BestRoute both calculate the optimum route given routes and costs

» Global variables: Optimization can be done for cost or for time

November 1999

CHAIMS 19

Megaprogram Example: Codeio_mmh = SETUP ("InputOutput")route_mmh = SETUP ("RouteInfo")...best2_mmh.SETATTRIBUTES (criterion = "cost")

cities_default = route_mmh.GETPARAM(Pair_of_Cities)input_cities_ih = io_mmh.INVOKE ("input”, cities_default)WHILE (input_cities_ih.EXAMINE() != DONE) {}cities = input_cities_ih.EXTRACT()...route_ih = route_mmh.INVOKE ("AllRoutes", Pair_of_Cities = cities)WHILE (route_ih.EXAMINE() != DONE) {}routes = route_ih.EXTRACT() …

IF (best1_mmh.ESTIMATE("Best_Route") < best2_mmh.ESTIMATE("Optimum") ) THEN {best_ih = best1_mmh.INVOKE ("Best_Route", Goods = info_goods, Pair_of_Cities = cities, List_of_Routes = routes, Cost_Ground = cost_list_ground, Cost_Air = cost_list_air)}ELSE {best_ih = best2_mmh.INVOKE ("Optimum", Goods = info_goods, …...best2_mmh.TERMINATE()

// Setup connections to megamodules.

// Set global variables valid for all invocations // of this client.

// Get information from the megaprogram user // about the goods to be transported and about// the two desired cities.

// Get all routes between the two cities.

//Get all city pairs in these routes.//Calculate the costs of all the routes.

// Figure out the optimal megamodule for// picking the best route.

//Pick the best route and display the result.

// Terminate all invocations

November 1999

CHAIMS 20

Operation of one Megamodule

• SETUP

• SETATTRIBUTES provides context

• ESTIMATE serves scheduling

• INVOKE initiates remote computation

• EXAMINE checks for completion

• EXTRACT obtains results

• TERMINATE I / ALL

M handle

M handle

M handle

M handle

I handle

I handle

I handle

M handle

I handle

November 1999

CHAIMS 21

CHAIMS Megaprogr. Language

Purely compositional:

– only variety of CALLs and control flow– no primitives for input/output ==> instead use general and

problem-specific I/O megamodules

– no primitives for arithmetic ==> use math megamodules

Splitting up CALL-statement:– parallelism by asynchrony in sequential program

– novel possibilities for optimizations

– reduction of complexity of integrated invoke statements

• higher-level language (assembler => HLLs, HLLs => composition/megamodule paradigm)

November 1999

CHAIMS 22

Architecture: Creation Process

d

a

b

c

MEGA modules

CHAIMS Repository

adds information to

MegamoduleProvider

Writes native programs or wraps non-CHAIMS

compliant megamodules

Wrapper Templates

e

November 1999

CHAIMS 23

writes

Architecture: Composition Process

Megaprogrammer

CSRT(compiled megaprogram)

Megaprogram(in CHAIMS language)

CHAIMS Compiler

generates

CHAIMS Repository

information

information

June 1998 CHAIMS 24

Runtime Architecture

Distribution System (CORBA, RMI…)

CSRT(compiled megaprogram)

ed

a

b

cMEGA modules

IO module(s)

November 1999

CHAIMS 25

writes

Architecture: AllActive at different times

e

Megaprogrammer

d

a

b

c

Distribution System (CORBA, RMI…)

CSRT(compiled megaprogram)

Megaprogram(in CHAIMS language)

CHAIMS Compiler

generates

MEGA modules

CHAIMS Repository

adds information to

MegamoduleProvider

wraps non-CHAIMScompliant megamodules

information

information

Wrapper Templates

November 1999

CHAIMS 26

Multiple Transport Protocols

Megaprogrammer

CHAIMS - language

M e g a m o d u l e s

CHAIMS-protocols

CORBA-idl DCE-idl Java-class

CHAIMS API defines interface between megaprogrammer and megaprogram; the megaprogram is

written in the CHAIMS language.

The CHAIMS protocols define the calls the mega-modules have to understand. These protocols are slightly different for the different distribution protocols, and are defined by an idl for CORBA, another idl for DCE, and a Java class for RMI.

Megaprogram

November 1999

CHAIMS 27

Name of Person

Data objects: BlobsMinimal Typing within CHAIMS:

Integer, boolean only for controlAll else is placed into Binary Large OBjects (Blobs),

transparent to compiler :

Alternatives

• ASN.1, with conversion routines

• XML

Example: Person_Information

complex

First Name string Joe Last Name string Smith

Personal Data complex Address

Date of Birth date 6/21/54 Soc.Sec.No string 345-34-345

November 1999

CHAIMS 28

Wrapper: CHAIMS Compliance

CHAIMS protocol - support all CHAIMS primitives

– if not native, achieved by wrapping legacy codes

• State management and asynchrony: » clientId (megamodule handle in CHAIMS language)

» callId (invocation handle in CHAIMS language)

» results must be stored for possible extraction(s) until termination of the invocation

• Data transformation: » BLOBs must be converted into the megamodule

specific data types (coding/decoding routines)

November 1999

CHAIMS 29

Architecture: Three Views

Transport View moving around data blobs and CHAIMS messages

Composition View (megaprogram)

- composition of megamodules

- directing of opaque data blobs

Data View - exchange of data - interpretation of

data - in/between

megamodules

CHAIMS Layer

Distribution Layer

Objective: Clear separation between composition of services, computation of data, and transport

November 1999

CHAIMS 30

execution of a remote method

synchronous

invoke a methodie extract results

setup / set attributes s

s

e

i

tim

e

decomposed(no benefit for one module)

asynchronous

s,i

tim

e

eti

me

available for other methods

e

s,i

Scheduler: Decomposed Execution

November 1999

CHAIMS 31

Optimized Execution of Modules

M1 M4(<M1+M2)

M5

M2

M3 (>M1+M2)

i1

e1

e4e3

e2

i3i4

i5

i2

e5

tim

e

M1

M4

M5

M2

M3

i1

e1

e2

e3

e4

e5

i2

i3

i4

i5

tim

e

data dependenciesexecution of a module

non-optimized

optimized by scheduleraccording to estimates

invoke a methodie extract results

November 1999

CHAIMS 32

Decomposed Parallel Execution

tim

e

M1M4

(<M1+M2)

M5

M2

M3<M1+M2)

optimized by scheduleraccording to estimates

invoke a methodextract results

set up / set attributes

Long setup timesoccur, for instance,when a subset of a large database hasto be loaded for asimple search, sayTransatlantic fightsfor an optimal arrival.

November 1999

CHAIMS 33

M1M4

(<M1+M2)

M5

M2

M3 (>M1+M2)

Decomposed Optimized Execution

M1

M4(<M1+M2)

M5

M2

M3 (>M1+M2)

optimized by scheduleraccording to estimates

invoke a methodextract results

set up / set attributes

tim

e

pri

or

tim

e

November 1999

CHAIMS 34

Scheduling: Simple Example

1 cost_ground_ih = cost_mmh.INVOKE ("Cost_for_Ground", 1 List_of_City_Pairs = city_pairs,Goods = info_goods)

2 WHILE (cost_ground_ih.EXAMINE() != DONE) {} 3cost_list_ground = cost_ground_ih.EXTRACT()

3 cost_air_ih = cost_mmh.INVOKE ("Cost_for_Air", 2 List_of_City_Pairs = city_pairs,Goods = info_good)

4 WHILE (cost_air_ih.EXAMINE() != DONE) {} 4cost_list_air = cost_air_ih.EXTRACT()

order inunscheduledmegaprogram

order in automaticallyprescheduled megaprogram

June 1998 CHAIMS 35

Iterated Invocations

invoke a methodextract results

set up / set attributes

pri

or

tim

e

M6.1

M6.2

M6.3

M6.4

M6.5

M6.1

M6.2

M6.3

M6.5

M6.4

Avoid repeatedsetups

tim

e

June 1998 CHAIMS 36

& Repeated Extractions

invoke a methodextract resultspartial for iteratingfull for presentation

set up / set attributes

pri

or

tim

e, d

isib

ct in

voct

ion

s

M6.1

M6.2

M6.3

M6.4

M6.5

M6.1

M6.2

M6.3

M6.5

M6.4

tim

e, s

har

ed s

etu

p

M6.1

M6.2

M6.3

M6.5

M6.4

t

i m e

,sh

ared

set

up

& p

arti

al e

xtra

ct

Avoid largeexactsuntilsatisfied

November 1999

CHAIMS 37

Scheduling: HeuristicsINVOKES: call INVOKE’s as soon as possible

» may depend on other data

» moving it outside of an if-block: depending on cost-function (ESTIMATE of this and following functions concerning execution time, dataflow and fees (resources).

EXTRACT: move EXTRACT’s to where the result is actually needed

» no sense of checking/waiting for results before they are needed

» instead of waiting, polling all invocations and issue next possible invocation as soon as data could be extracted

TERMINATE: terminate invocations that are no longer needed (save resources)

» not every method invocation has an extract (e.g. print-like functions)

November 1999

CHAIMS 38

Compiling into a Network

Mega Program

Module A

Module B

Module CModule E

Module DModule F

current CHAIMS systemMega Program

Module DModule F

control flow data flow

with distribution dataflow optimization

Mega Program

Module A

Module B

Module C Module E

Module DModule F

November 1999

CHAIMS 39

CHAIMS Implementation• Specify minimal language

– minimal functions: CALLs, While, If *

– minimal typing {boolean, integer, string, handles, object}

» objects encapsulated using ASN.1 standard

– type conversion in wrappers, service modules*

• Compiler for multiple protocols (one-at-time, mixed*)

• Wrapper generation for multiple protocols

• Native modules for I/O, simple mathematics*, other

• Implement API for CORBA, Java RMI, DCE usage

• Wrap / construct several programs for simple demos

• Schedule optimization *

• Demonstrate use in heterogeneous setting

• Define full-scale demonstration * in process

November 1999

CHAIMS 40

CHAIMS

Conclusion: Research Questions

• Is a Megaprogramming language focusing only on composition feasible?

• Can it exploit on-going progress in client-server models and be protocol independent?

• Can natural parallelism for distributed services be effectively scheduled?

• Can high-level dataflow among distributed modules be optimized?

• Can CHAIMS express clearly a high-level distributed SW architecture?

• Can the approach affect SW process concepts and practice?

November 1999

CHAIMS 41

Conclusion: Questions not addressed

• Will one Client/Server protocol subsume all others?

– distributed optimization remains an issue

• Synchronization / Concurrency Control

– autonomy of sources negates current concepts

– if modules share databases, then database locks may span setup/terminate all for a megaprogram handle.

• Will software vendors consider moving to a service paradigm?

– need CHAIMS demonstration for evaluation

November 1999

CHAIMS 42

Integration Science

IntegrationScience

IntegrationScience

ArtificialIntelligence

knowledge mgmtmodels

uncertainty

ArtificialIntelligence

knowledge mgmtmodels

uncertainty

Systems Engineering

analysisdocumentation

costing

Systems Engineering

analysisdocumentation

costing

Databasesaccessstoragealgebras

Databasesaccessstoragealgebras

November 1999

CHAIMS 43

CHAIMS