data parallel languages (chapter 4) asc language multic fortran 90 and hpf

Data Parallel Languages

(Chapter 4)

ASC LanguagemultiCFortran 90 and HPF

Parallel & Distributed Computing 2

Contents

ASC Programming Language Multi-C Language Fortran 90 and High Performance Fortran


References for Chapter 4

11. Jerry Potter, Associative Computing - A Programming Paradigm for Massively Parallel Computers, Plenum Publishing Company, 1992

18. Jerry Potter, ASC Primer, 42 pages, posted at parallel website under downloads at http://zserver.cs.kent.edu/PACL/downloads.

19. Ian Foster, Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering, Addison Wesley, 1995, Online at http://www-unix.mcs.anl.gov/dbpp/text/book.html

20. “The multiC Programming Language”, Preliminary Documentation, WaveTracer, PUB-00001-001-00.80, Jan. 1991.

21. “The multiC Programming Language”, User Documentation, WaveTracer, PUB-00001-001-1.02, June 1992.

The ASC Language

Michael C. Scherger & Johnnie BakerDepartment of Computer ScienceKent State UniversityOctober 2003


Contents Software Location and Installation Basic Program Structure Data Types and Variables Operator Notation Control Structures Looping Accessing Values in Parallel Variables Associations and Setscope Input and Output Performance Monitor Subroutines and other topics


Software

Compiler and Emulator DOS/Windows, UNIX

(Linux) WaveTracer Connection Machine

http://zserver.cs.kent.edu/PACL/downloads.htm

Use any text editor. Careful on moving files

between DOS and UNIX!

ASC Compiler

ASC Emulator

Anyprog.asc

Anyprog.iob

Standard I/O File I/O

-e-wt-cm

-e-wt-cm


Software

Example:To compile your program…

% asc1.exe –e shapes.asc

To execute your program… % asc2.exe –e shapes.iob % asc2.exe –e shapes.iob < shapes.dat % asc2.exe –e shapes.iob < shapes.dat > shapes.out


Basic Program Structure

Main program_nameConstants;Variables;Associations;Body;

End;


Basic Program Structure

Example:Consider an ASC Program that computes the

area of various simple shapes (circle, rectangle, triangle).

Here is an example shapes.asc Here is the data shapes.dat Here is the shapes.out

NOTE: Above links are only active during the “slide show”.


Data Types and Variables

ASC has eight data types… int (i.e., integer), real, hex (i.e., base 16), oct (i.e.,

base 8), bin (i.e., binary), card (i.e., cardinal), char (i.e., character), logical, index.

Card is used for unsigned integer data. Variables can either be scalar or parallel.

Scalar variables are in the IS. Parallel variables are in the cells.

Parallel variables have the suffix “[$]” at the end of the identifier.

Can specify the length (in bits) of parallel variables. Default word length works fine for most programs.


Comparison of Logical Parallel and Index Parallel

A index parallel variable selects a single scalar value from a parallel variable.

A logical parallel variable L is normally used to store a logical value resulting from a search such as

L[$] = A[$] .eq. B[$] ASC implementation simplifies usage by not formally

distinguishing between the two. The correct type, based on usage, should be selected

to improve readability.


Array Dimensions

A parallel variable can have up to 3 dimensionsFirst dimension is “$”, the parallel dimension

The array numbering is zero-based, so the declaration

int parallel A[$,2]creates the following 1dimensional variables:

A[$,0], A[$,1], A[$,2]


Mixed Mode Operations Mixed mode operations are supported and their result

has the “natural” mode. For example, given declarationsint scalar a, b, c;int parallel p[$], q[$], r[$], t[$,4];index parallel x[$], y[$];

then c = a + b is a scalar integerq[$] = a + p[$] is a parallel integer variablea + p[x] is a integer valuer[$] = t[x,2]+3*p[$] is a parallel integer variablex[$] = p[$] .eq. r[$] is an index parallel variable

More examples are given on page 9-10 of ASC Primer


Operator Notation

Relational Operators “less than” is denoted by .lt. or < “equal” is denoted .eq. or = “not equal” is denoted by .ne. or !=

Logical Operators “not” is denoted by .not. or ! “or” is denoted by .or. OR || “and” is denoted by .and. or &&

Arithmetic Operators Addition is denoted by + Multiplication is denoted by * Division is denoted by /

For more information, see page 40 of ASC Primer


The IF-THEN-ELSE Control Structure

Scalar version similar to sequential programming languages. Either executes either the body of the IF or the body

of the ELSE. Parallel version normally executes both “bodies”.

First finds the responders for the conditional If there are any responders, the responding PEs

execute the body of the IF. Next identifies the non-responders for the conditional

If there are non-responders, those PEs executes the body of the ELSE.

This control structure is also a masking operation.


Parallel IF-THEN-ELSE Example

if A[$] .eq. 2then A[$] = 5;else A[$] = 0;

endif;

A[$]

BEFORE

MASK

BEFORE

A[$]

AFTER

THEN

MASK

ELSE

MASK

2 1 5 1 0

5 1 0 0 1

3 0 3 0 0

2 1 5 1 0

1 1 0 0 1


IF-THEN-ELSENANY Control Statement Similar to the IF-THEN-ELSE, except that only one of the two bodies

of code is executed. First the logical expression following the “IF’ is evaluated If there is at least one responder, then the responding processors

execute the body of the IF. However, if there were no responders to the logical expression, then

all processors that were initially active at the start of this command execute the body of the ELSENANY

EXAMPLEIF A[$] .GE. 2 and A[$] .LT. 4 THEN

C[$] = 1;

ELSENANY

C[$] = 9;

ENDIF; See page 16-17 of ASC Primer for more information


ANY-ELSENANY Control Statement

If there is at least one responder, then all active processors (i.e., ones active at the start of this command) execute the statements inside the any-block.

If there are no responders, then all active processors execute the statements inside the elsenany block

any can be used alone (without the elsenany) Example

any A[$] .eq. 10B[$] =11;

elsenanyB[$] = 100;

endany; For more information, see pages 17-19 of ASC Primer.


Looping

Sequential looping Loop-Until

See example on page 20 of ASC Primer Sequential looping is an infrequently used operation in ASC

Two types of parallel looping constructs: Parallel For-Loop

Conditional is evaluated only once. Example on page 21.

Parallel While-Loop Conditional is evaluated every iteration. Example on page 21-22.


For construct Often used when a process must be repeated for

each cell that satisfies a certain condition. The index variable is available throughout the

body of the for statement The index value of for is only evalulated initially

Parallel For Loop


For Loop Example Example:

sum = 0;

for x in A[$] .eq. 2

sum = sum + B[$];

endfor x; Trace for example:

A[$] B[$] x loop sum

1 1 0 0

2 2 1 1st 2

2 3 1 2nd 5

1 4 0

2 5 1 3rd 10


While Loop

Unlike the for statement, this construct re-evaluates the logical conditional statement prior to each execution of the body of the while.

The bit array resulting from the evaluation of the conditional statement is assigned to the index parallel variable on each pass.

The index parallel array is available for use within the body each loop.

The body of the while construct will continue to be executed until there are no responders (i.e., all zeros) in the index parallel variable.

Study example and trace in the ASC Primer carefully to make sure you understand the while construct.


Get Statement

Used to retrieve a value from a specific field in a parallel variable satisfying a specific conditional statement.

Example:

get x in tail[$] .eq. 1val[x] = 0;

endget x; Study the trace of this example in on page 24 of ASC

Primer to make sure its action is clear.


Next Statement

Similar to get statement, except next updates the set of responders each time it is called.

Unlike get, two successive calls to next is expected to select two distinct processors (and two distinct association records).

Can be used inside a loop to sequentially process each responder.

See page 22-23 of ASC Primer for more details.


Maximum and Minimum Values

The maxval and minval functions maxval returns the maximum value of the specified

items among the active responders. Similarly, minval returns the minimum value. Example:

if (tail[$] .neq. 1) then k = maxval( weight[$]);

endif; See trace of example on pg 27 of ASC Primer.

The maxdex and mindex functions Returns the index of one processor where a

maximum or minimum occurs. If maximum/minimum value occurs at more than one

location, an arbitrary selection is made as to which index is returned.


The associate statement

Creates an association between parallel variables and a parallel logical variables.There are no “structs” or “classes” in ASC.

See earlier example in sample program. See page 8 of ASC primer for more

information.


Setscope – Endsetscope Commands

Resets the parallel mask register setscope jumps out of current mask setting to another

mask setting. One use is to reactivate currently inactive processors. Also allow an immediate return to a previously

calculated mask, such as an association. Is an unstructured command such as go-to and

jumps from current environment to a new environment.

Use sparingly

endsetscope resets mask to preceding setting. See example on page 15 of ASC Primer.


Input / Output

Parallel read statementSee page 12-13 of ASC Primer Illustrated in earlier example program.Must have an ASSOCIATE statement. Input file must have blank line at end of data

set. Input is from “interactive user input” or from a

data file identified in the command line.


Input / Output

Parallel print statementSee page 13 in the ASC primer Illustrated in earlier example program.Must have an ASSOCIATE statement.Does not output user specified strings.

I.e. User text messages. Only outputs the values of parallel variables.


Input / Output

The msg commandPage 13-14 of ASC PrimerUsed to display user text messages.Used to display values of scalar variables.Used to display a dump of the parallel

variables.


Scalar variable input

Static input can be handled in the code. Also, define or deflog statements can be used to handle static input. Dynamic input is currently not supported directly, but can be

accomplished as follows: Reserve a parallel variable dummy (of desired type) for input. Reserve a parallel index variable used. Values to be stored in scalar variables are first read into dummy

using a parallel-read and then transferred using get or next to the appropriate scalar variable.

Example:

read dummy[$] in used[x];

get x in used[$]

scalar-variable = dummy[x];

endget x; NOTE: Don’t need to use associate statement to associate dummy

with used. Omission causes no problems as no check is currently made.


Dynamic Storage Allocation allocate is used to identify a processor whose association record is

currently unused. Will be used to store a new association record Creates a parallel index that points to the processor selected

release is used to de-allocate storage of specified records in an association Can release multiple records simultaneously.

Example:Example:char parallel node[$], parent[$];logical parallel tree[$];index parallel x[$];associate node[$], level[$], parent[$] with tree[$];......allocate x in tree[$]

node[x] = ‘B’endallocate x;release parent[$] .eq. ‘A’ from tree[$].


Performance Monitor Keeps track of number of scalar and parallel operations. It is turned on and off using the perform statement

PERFORM = 1; PERFORM = 0;

The number of scalar and parallel operations can be printed using the msg command MSG “Number of scalar and parallel operations are”

PA_PERFORM SC_PERFORM; The ASC Monitor is important for evaluation and

comparison of various ASC algorithms and software. See Pg 30-31 of ASC Primer for more information


Additional Features

Restricted subroutine capability is currently available See call and include on pg 25-6 of ASC Primer.

Use of personal pronouns and articles in ASC make code easier to read and shorter. See page 29 of ASC Primer.

data parallel languages (chapter 4) asc language multic fortran 90 and hpf

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