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FORTRAN 90+

FORTRAN 90+. Yetmen Wang. Introduction. FORmula TRANslation Developed by the IBM team led by John Backus The first high-level programming language Mainly intended for mathematical computations Areas of Application Numerical Analysis System Simulation Scientific Computations

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FORTRAN 90+

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  1. FORTRAN 90+ Yetmen Wang

  2. Introduction • FORmula TRANslation • Developed by the IBM team led by John Backus • The first high-level programming language • Mainly intended for mathematical computations • Areas of Application • Numerical Analysis • System Simulation • Scientific Computations • Engineering Procedures

  3. Fortran History • Published by IBM in 1957 • MS PowerStation 4.0 • Sold to Digital with DEC, it developed into Digital Visual Fotran 5.x • Digital was later merged with Compaq; CVF 6.x emerged • CVF development team was purchased by Intel • HP merged with Compaq, introducing HP CVF 6.6a • Intel Fortran, combining CVF, developed Intel Visual Fortran 8.x

  4. Fortran Versions • 1962  FORTRAN IV • 1966  FORTRAN 66 • 1978  FORTRAN 77 • 1992  FORTRAN 90 • Array • Semi-OOP • Resembles MATLAB • 1997  FORTRAN 95 • HPF extension • more OOP • 2003  FORTRAN 2000 • Fully OOP

  5. Strengths • Array language and object-oriented programming • Higher computational speed compared to C/C++ and MATLAB • Maintains plenty of legacy codes • Easy-to-learn compared to C/C++ • The majority of individuals in the numerical computing field still use Fortran to develop program(s)

  6. Weaknesses • File I/O is difficult to modify and comprehend • Low reusability and high cost of code maintenance • Lack of numerical and graphical libraries • Difficult to convert the codes into applications • Platform porting • Interfacing to other language

  7. Program Structure A good description of Fortran programing.

  8. Significant Features • New Source Form • Object-Oriented Programming • Array Programming • Dynamic Memory Allocation • Pointer

  9. New Source Form • Free Format • IMPLICIT NONE • Statements

  10. New Source Form – Free Format • names of variables may consist of up to 31 characters • 132 characters per line • up to 39 continuation lines • blanks are significant • & as line continuation character • ; as statement separator for multiple statements per line • ! as comment symbol

  11. New Source Form - IMPLICIT NONE • The first line after any USE statements • Used to inhibit the old Fortran feature that treats, by default, all variable beginning with the letters I, j, k, l, m, and n as integers and others as real arguments • IMPLICIT NONE should always be used to prevent potential confusion in variable types • Upper and lowercase letters are equivalent

  12. New Source Form - Statements • INCLUDE can be used to include source text from external files • END DO statements are used to complete DO loops • Relational Operator Alternatives • .LT.  < • .LE.  <= • .EQ.  == • .NE.  /= • .GE.  > • .GT.  =>

  13. Object-Oriented Programming • Functionality • TYPE • MODULE • Attributes • INTERFACE • Overload

  14. Object-Oriented Programming - Functionality • Data Abstraction • Data Hiding • Encapsulation • Inheritance • Polymorphism • Reusability

  15. Object-Oriented Programming – TYPE • user-defined TYPE • A new type can be defined in a derived-type statement, which can later be used to describe an object • Example I Create a type COORDS_3D with three REAL components X, Y, and Z. TYPE :: COORDS_3D REAL :: X, Y, Z END TYPE COORDS_3D Create a variable of type COORDS_3D with values 0.0, 1.0, and 5.0. TYPE(COORDS_3D) :: Pt Pt%X = 0.0 Pt%Y = 1.0 Pt%Z = 5.0

  16. Object-Oriented Programming – TYPE • user-defined TYPE • Example II Create a type NONZERO in which nonzero matrix elements are described. TYPE :: NONZERO REAL :: VALUE INTEGER :: ROW, COLUMN END TYPE NONZERO Create a sparse matrix A with 100 nonzero elements. TYPE(NONZERO) :: A(100) Obtain the value of A(10). X = A(10)%Value

  17. Object-Oriented Programming – MODULE • MODULE / MODULE PROCEDURE • A collection of data, type definitions, and procedure definitions which can be exploited by any other program unit attaching it (via the USE statement). • Example MODULE point_module TYPE point REAL :: x, y END TYPE point CONTAINS FUNCTION addpoints(p, q) TYPE (point), INTENT(IN) :: p, q TYPE (point) :: addpoints addpoints%x = p%x + q%x addpoints%y = p%y + q%y END FUNCTION addpointsEND MODULE point_module Main Program . . . USE point_moduleTYPE (point) :: px, py, pz...pz = addpoints(px,py) Accesses the module.

  18. Object-Oriented Programming – ATTRIBUTES • PUBLIC and PRIVATE attributes • PRIVATE – variables/subroutines/functions defined can only be used in the specified module • PUBLIC – variables/subroutines/functions defined can be used publicly • Example MODULE bank PRIVATE money PUBLIC SaveMoney integer :: money = 1000000 CONTAINS     SUBROUTINE SaveMoney(num)         integer :: num         money = money+num         return END SUBROUTINE END MODULE

  19. Object-Oriented Programming – INTERFACE • INTERFACE • A way to specify information for an external procedure • Name of the procedure • Types of passed and returned parameters • Whether an argument may be changed • INTERFAXE detects incorrect calls at compile time • Example INTERFACE REAL FUNCTION DISTANCE( A, B) REAL, INTENT(IN) :: A, B END FUNCTION DISTANCE END INTERFACE

  20. Object-Oriented Programming – Overload • Overload Operators • Operators can be overloaded to clarify unambiguous definitions • Intrinsic operators can be overloaded to apply to all types in a program • Overloading is encapsulated in a module • generic operator symbol in an INTERFACE OPERATOR statement • overload set in a generic interface • Example INTERFACE OPERATOR(-) FUNCTION DIFF(A,B) TYPE(POINT) :: DIFF, A, B END FUNCTION END INTERFACE

  21. Array Programming • Whole Array • Array Section • Intrinsic Functions

  22. Array Programming – Whole Array • Assignment • All arrays must conform • The operation is applied to each element of the array • Scalars broadcast • Declarations REAL, DIMENSION(5, 5) :: A, B OR REAL :: A(5,5), B(5,5)

  23. Array Programming – Whole Array • Operation • Example Assume A and B to be two 2D arrays of the same shape. Multiply them and assign the result to array C. = x FORTRAN 77 REAL A(5, 5), B(5, 5), C(5, 5) ... i LOOP j LOOP C(j, i) = A(j, i) * B(j, i) END i LOOP END j LOOP FORTRAN 90+ REAL, DIMENSION (5, 5) :: A, B, C ... C = A * B

  24. Array Programming – Array Section • Declaration REAL, DIMENSION(10, 10) :: A • Subscript Notation • ( [row lower bound] : [row upper bound] : [row stride], [column lower bound] : [column upper bound] : [column stride] )

  25. Array Programming – Array Section • Example REAL :: A(10, 10) A(2:6, 4:8) A(:, 1:3)

  26. Array Programming – Array Section INTRODUCTION • Example REAL :: A(10, 10) A(4:10, 5) A(1:10:2, 1:10:2)

  27. Array Programming – Intrinsic Functions • Functions • array manipulations CSHIFT and EOSHIFT for shifts along array axis TRANSPOSE for the transpose of a matrix • reduction functions SUM , PRODUCT , MAXVAL , MINVAL , COUNT , ALL , and ANY • inquiry functions SHAPE , SIZE, ALLOCATED, LBOUND, and UBOUND • array constructor functions MERGE, SPREAD, RESHAPE, PACK and UNPACK

  28. Array Programming – Intrinsic Functions • Example - CSHIFT FORTRAN 77 REAL :: A(0:99), B(0:99) DO i = 0, 99 B(i) = ( A( mod(i+99, 100) ) + A( mod(i+1, 100) ) ) / 2 ENDDO FORTRAN 90+ REAL :: A(100), B(100) B = ( CSHIFT(A, +1) + CSHIFT(A, -1) ) / 2

  29. Pointer • Introduction • Association Status • Example

  30. Pointer - Introduction • A pointer has the POINTER attribute and may point to another data object of the same type, which has the TARGET attribute or an area of dynamically allocated memory. • Uses • Alternative to allocatable arrays • A tool to create and manipulate dynamic data structures • Declarations REAL, POINTER :: Ptr(:, :) REAL, TARGET :: TA(:, :)

  31. Pointer – Association Status • Status • Undefined – initially specified in a type declaration statement • Associated – points to a target • Null – nullified by a NULLIFY or a DEALLOCATE statement • NULLIFY(Ptr) • DEALLOCATE(Ptr, STAT = ierr) ? Pointer Pointer Target Pointer NULL

  32. Pointer - Example • Example REAL, TARGET :: A REAL, POINTER :: P, Q A = 3.14 P => A Q => P A = 2.718 WRITE(*,*) Q Q outputs 2.718 Q => P and P => A Therefore, Q => A, whose value has changed from 3.14 to 2.718

  33. Dynamic Storage • Allocatable Array • Pointer

  34. Dynamic Storage – Allocatable Array • Acquire and return a storage area in HEAP MEMORY for an array with attributes • Example REAL, DIMENSION(:), ALLOCATABLE :: A ALLOCATE( A(5:5) ) A(j) = q ! assignment of the array CALL sub(A) ! Use of the array in a subroutine • Deallocation occurs automatically reaching RETURNor END in the program • To prevent memory leak, allocatable arrays should be explicitly deallocated DEALLOCATE (A)

  35. Dynamic Storage - Pointer • Use a pointer • Can be passed to a procedure in an unallocated state • An explicit INTERFACE is required when passing a pointer to a procedure

  36. Dynamic Storage - Pointer • Use a pointer • Example Subroutine Procedure: SUBROUTINE SUB(B) REAL, DIMENSION (:,:), POINTER :: B INTEGER M, N ! Assign M and N ALLOCATE (B(M,N)) ! Allocate B as a matrix END SUBROUTINE SUB Main Program: INTERFACE SUBROUTINE SUB(B) REAL, DIMENSION (:,:), POINTER :: B END SUBROUTINE SUB END INTERFACE REAL, DIMENSION (:,:), POINTER :: A CALL SUB(A) ! matrix A is called and allocated in the subroutine

  37. THANK YOU!

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