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Fortran 90 is a modern language that introduces many important new features beneficial for scientific programming. We discuss our experiences in plasma particle simulation and unstructured adaptive mesh refinement on supercomputers, illustrating the features of Fortran 90 that support the object-oriented methodology.
We illustrate how Fortran 90 supports object-oriented concepts by example of plasma particle computations on the IBM SP. Our experience shows that Fortran 90 and object-oriented methodology give high performance while providing a bridge from Fortran 77 legacy codes to modern programming principles. All of our object-oriented Fortran 90 codes execute more quickly thatn the equeivalent C++ versions, yet the abstraction modelling capabilities used for scentific programming are comparably powereful.
Recent progress in distributed object technology has enabled software applications to be developed and deployed easily such that objects or components can work together across the boundaries of the network, different operating systems, and different languages. A distributed object is not necessarily a complete application but rather a reusable, self-contained piece of software that co-operates with other objects in a plug-and-play fashion via a well-defined interface. The Common Object Request Broker Architecture (CORBA), a middleware standard defined by the Object Management Group (OMG), uses the Interface Definition Language (IDL) to specify such an interface for transparent communication between distributed objects. Since IDL can be mapped to any programming language, such as C++, Java, Smalltalk, etc., existing applications can be integrated into a new application and hence the tasks of code re-writing and software maintenance can be reduced. Many scientific applications in aerodynamics and solid mechanics are written in Fortran. Refitting these legacy Fortran codes with CORBA objects can increase the codes reusability. For example, scientists could link their scientific applications to vintage Fortran programs such as Partial Differential Equation(PDE) solvers in a plug-and-play fashion. Unfortunately, CORBA IDL to Fortran mapping has not been proposed and there seems to be no direct method of generating CORBA objects from Fortran without having to resort to manually writing C/C++ wrappers. In this paper, we present an efficient methodology to integrate Fortran legacy programs into a distributed object framework. Issues and strategies regarding the conversion and decomposition of Fortran codes into CORBA objects are discussed. The following diagram shows the conversion and decomposition mechanism we proposed. Our goal is to keep the Fortran codes unmodified. The conversion- aided tool takes the Fortran application program as input and helps programmers generate C/C++ header file and IDL file for wrapping the Fortran code. Programmers need to determine by themselves how to decompose the legacy application into several reusable components based on the cohesion and coupling factors among the functions and subroutines. However, programming effort still can be greatly reduced because function headings and types have been converted to C++ and IDL styles. Most Fortran applications use the COMMON block to facilitate the transfer of large amount of variables among several functions. The COMMON block plays the similar role of global variables used in C. In the CORBA-compliant programming environment, global variables can not be used to pass values between objects. One approach to dealing with this problem is to put the COMMON variables into the parameter list. We do not adopt this approach because it requires modification of the Fortran source code which violates our design consideration. Our approach is to extract the COMMON blocks and convert them into a structure-typed attribute in C++. Through attributes, each component can initialize the variables and return the computation result back to the client. We have tested successfully the proposed conversion methodology based on the f2c converter. Since f2c only translates Fortran to C, we still needed to edit the converted code to meet the C++ and IDL syntax. For example, C++/IDL requires a tag in the structure type, while C does not. In this paper, we identify the necessary changes to the f2c converter in order to directly generate the C++ header and the IDL file. Our future work is to add GUI interface to ease the decomposition task by simply dragging and dropping icons.
An efficient methodology is presented for integrating legacy applications written in Fortran into a distributed object framework. Issues and strategies regarding the conversion and decomposition of Fortran codes into Common Object Request Broker Architecture (CORBA) objects are discussed. Fortran codes are modified as little as possible as they are decomposed into modules and wrapped as objects. A new conversion tool takes the Fortran application as input and generates the C/C++ header file and Interface Definition Language (IDL) file. In addition, the performance of the client server computing is evaluated.
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Legacy software has great value since it is generally well debugged, produces results that are trusted and is actively meeting end-user goals. The amount of hidden expert knowledge embedded in such software can be significant, making its preservation important.
In this paper, applications of the modern Fortran programming language to the field of spacecraft trajectory optimization and design are examined. Modern object-oriented Fortran has many advantages for scientific programming, although many legacy Fortran aerospace codes have not been upgraded to use the newer standards (or have been rewritten in other languages perceived to be more modern). NASA's Copernicus spacecraft trajectory optimization program, originally a combination of Fortran 77 and Fortran 95, has attempted to keep up with modern standards and makes significant use of the new language features. Various algorithms and methods are presented from trajectory tools such as Copernicus, as well as modern Fortran open source libraries and other projects.
Most parallel scientific programs contain compiler directives (pragmas) such as those from OpenMP, explicit calls to runtime library procedures such as those implementing the Message Passing Interface (MPI), or compiler-specific language extensions such as those provided by CUDA. By contrast, the recent Fortran standards empower developers to express parallel algorithms without directly referencing lower-level parallel programming models. Fortran’s parallel features place the language within the Partitioned Global Address Space (PGAS) class of programming models. When writing programs that exploit data-parallelism, application developers often find it straightforward to develop custom parallel algorithms. Problems involving complex, heterogeneous, staged calculations, however, pose much greater challenges. Such applications require careful coordination of tasks in a manner that respects dependencies prescribed by a directed acyclic graph. When rolling one’s own solution proves difficult, extending a customizable framework becomes attractive. The paper presents the design, implementation, and use of the Framework for Extensible Asynchronous Task Scheduling (FEATS), which we believe to be the first task-scheduling tool written in modern Fortran. We describe the benefits and compromises associated with choosing Fortran as the implementation language, and we propose ways in which future Fortran standards can best support the use case in this paper.
This report describes a database routine called DB90 which is intended for use with scientific and engineering computer programs. The software is written in the Fortran 90/95 programming language standard with file input and output routines written in the C programming language. These routines should be completely portable to any computing platform and operating system that has Fortran 90/95 and C compilers. DB90 allows a program to supply relation names and up to 5 integer key values to uniquely identify each record of each relation. This permits the user to select records or retrieve data in any desired order.
Several common higher level program languages are described. FORTRAN, ALGOL, COBOL, PL/1, and LISP 1.5 are summarized and compared. FORTRAN is the most widely used scientific programming language. ALGOL is a more powerful language for scientific programming. COBOL is used for most commercial programming applications. LISP 1.5 is primarily a list-processing language. PL/1 attempts to combine the desirable features of FORTRAN, ALGOL, and COBOL into a single language.
We will explore our experiences and evaluate the performance impact this hardware introduces for our system.
An approach for modernizing legacy scientific software, based on the new features of Fortran 90/95, is presented.
Fortran has largely enjoyed prominence for the past few decades as the computer programming language of choice for numerically intensive scientific, engineering, and process control applications. Fortran's well understood static language syntax has allowed resulting parsers and compiler optimizing technologies to often generate among the most efficient and fastest run-time executables, particularly on high-end scalar and vector supercomputers. Computing architectures and paradigms have changed considerably since the last ANSI/ISO Fortran release in 1978, and while FORTRAN 77 has more than survived, it's aged features provide only partial functionality for today's demanding computing environments. The simple block procedural languages have been necessarily evolving, or giving way, to specialized supercomputing, network resource, and object-oriented paradigms. To address these new computing demands, ANSI has worked for the last 12-years with three international public reviews to deliver Fortran 90. Fortran 90 has superseded and replaced ISO FORTRAN 77 internationally as the sole Fortran standard; while in the US, Fortran 90 is expected to be adopted as the ANSI standard this summer, coexisting with ANSI FORTRAN 77 until at least 1996. The development path and current state of Fortran will be briefly described highlighting the many new Fortran 90 syntactic and semantic additions which support (among others): free form source; array syntax; new control structures; modules and interfaces; pointers; derived data types; dynamic memory; enhanced I/O; operator overloading; data abstraction; user optional arguments; new intrinsics for array, bit manipulation, and system inquiry; and enhanced portability through better generic control of underlying system arithmetic models. Examples from dynamical astronomy, signal and image processing will attempt to illustrate Fortran 90's applicability to today's general scalar, vector, and parallel scientific and engineering requirements and object oriented programming paradigms. Time permitting, current work proceeding on the future development of Fortran 2000 and collateral standards will be introduced.
Fortran and C++ are the dominant programming languages used in scientific computation. Consequently, extensions to these languages are the most popular for programming massively parallel computers. We discuss two such approaches to parallel Fortran and one approach to C++. The High Performance Fortran Forum has designed HPF with the intent of supporting data parallelism on Fortran 90 applications. HPF works by asking the user to help the compiler distribute and align the data structures with the distributed memory modules in the system. Fortran-S takes a different approach in which the data distribution is managed by the operating system and the user provides annotations to indicate parallel control regions. In the case of C++, we look at pC++ which is based on a concurrent aggregate parallel model.
Issues involved in the continuing development of an advanced simulation complex are discussed. This approach provides the capability to perform the majority of tests on advanced systems, non-destructively. The controlled test environments can be replicated to examine the response of the systems under test to alternative treatments of the system control design, or test the function and qualification of specific hardware. Field tests verify that the elements simulated in the laboratories are sufficient. The digital computer is hosted by a Digital Equipment Corp. MicroVAX computer with an Aptec Computer Systems Model 24 I/O computer performing the communication function. An Applied Dynamics International AD100 performs the high speed simulation computing and an Evans and Sutherland PS350 performs on-line graphics display. A Scientific Computer Systems SCS40 acts as a high performance FORTRAN program processor to support the complex, by generating numerous large files from programs coded in FORTRAN that are required for the real time processing. Four programming languages are involved in the process, FORTRAN, ADSIM, ADRIO, and STAPLE. FORTRAN is employed on the MicroVAX host to initialize and terminate the simulation runs on the system. The generation of the data files on the SCS40 also is performed with FORTRAN programs. ADSIM and ADIRO are used to program the processing elements of the AD100 and its IOCP processor. STAPLE is used to program the Aptec DIP and DIA processors.
A compiler and runtime support mechanism is described and demonstrated. The methods presented are capable of solving a wide range of sparse and unstructured problems in scientific computing. The compiler takes as input a FORTRAN 77 program enhanced with specifications for distributing data, and the compiler outputs a message passing program that runs on a distributed memory computer. The runtime support for this compiler is a library of primitives designed to efficiently support irregular patterns of distributed array accesses and irregular distributed array partitions. A variety of Intel iPSC/860 performance results obtained through the use of this compiler are presented.
The Charon toolkit for piecemeal development of high-efficiency parallel programs for scientific computing is described. The portable toolkit, callable from C and Fortran, provides flexible domain decompositions and high-level distributed constructs for easy translation of serial legacy code or design to distributed environments. Gradual tuning can subsequently be applied to obtain high performance, possibly by using explicit message passing. Charon also features general structured communications that support stencil-based computations with complex recurrences. Through the separation of partitioning and distribution, the toolkit can also be used for blocking of uni-processor code, and for debugging of parallel algorithms on serial machines. An elaborate review of recent parallelization aids is presented to highlight the need for a toolkit like Charon. Some performance results of parallelizing the NAS Parallel Benchmark SP program using Charon are given, showing good scalability.