A Data Parallel Scientific Modeling Language

The data parallel meta language (DPML) and its associated Fortran source code rewriter (DP77) support architecture independent, high performance climate and weather prediction models. The language allows the data domains over which a program operates, the communication patterns required between elements of those data domains, and some or all of the calculations of a program to be expressed at a very high level. DPML uses explicit data parallelism to express the inherent parallelism of the models, with the result that programs are easily compilable into target machine code. DP77 uses information from the DPML program to translate Fortran routines into the host specific Fortran form required for their parallel execution within the model. This paper describes the general strategy behind the development of DPML, discusses its language features using examples drawn from climate modelling, and provides details of the mechanism it uses for incorporating Fortran into data parallel programs. Encouraging results are reported for DPML versions of the standard weather benchmark models executing on vector, SIMD, and MIMD (shared memory) machines. While the paper is set within the framework of climate modelling, the technique has obvious wider implications.     

Optimizations of a GPU accelerated heat conduction equation by a programming of CUDA Fortran from an analysis of a PTX file

The Fortran language has been commonly used for many kinds of scientific computation. In this paper, we focus on the solution of an unsteady heat conduction equation, which is one of the simplest problems for thermal dynamics. Recently, a GPU (graphics processing unit) has been enhanced with a Fortran programming language capability employing CUDA (compute unified device architecture), known as CUDA Fortran. We find that the speed performance of a system using an ordinary program coding of CUDA Fortran is lower than that of systems using a program coding of CUDA C. We also find that intermediate assembly files PTX (parallel thread execution) of the two languages are not coincident. Therefore, by comparing the PTX files from the two coding programs we could detect the bottleneck that causes the speed reduction. We propose three optimization techniques that can enable the calculated speeds using CUDA Fortran and CUDA C to be coincident. The optimizations can be performed by the Fortran language when improved by an analyzed PTX file. It is thus possible to improve the performance of CUDA Fortran by adding a correction to it, which happens to be at a programming language level.     

Structured Fortran—An Evolution of Standard Fortran

Fortran is 21 years old; many would say that it has not reached adulthood but senility. Yet it remains the language of use in the overwhelming majority of scientific applications of computers and no end to this situation is in sight. Moreover, its evolution through the standards process is very slow, too slow to give any hope that Fortran will ever in this way become a language in which structured programs can be easily and effectively written.     

RATFOR—a preprocessor for a rational fortran

Although Fortran is not a pleasant language to use, it does have the advantages of universality and (usually) relative efficiency. The RATFOR language attempts to conceal the main deficiencies of Fortran while retaining its desirable qualities, by providing decent control flow statements and some ‘syntactic sugar’. RATFOR is implemented as a preprocessor which translates this language into Fortran Once the control flow and cosmetic deficiencies of Fortran are hidden, the resulting language is remarkably pleasant to use. RATFOR programs are markedly easier to write, and to read, and thus easier to debug, maintain and modify than their Fortran equivalents It is readily possible to write RATFOR programs which are portable to other environments. RATFOR is written in itself in this way, so it is also portable; versions of RATFOR are now running on computers of six different manufacturers This paper discusses design criteria for a Fortran preprocessor, the RATFOR language and its implementation, and user experience.     

Coupling distributed Fortran applications using C++ wrappers and the CORBA sequence type

The CORBA standard lacks a mapping of its Interface Definition Language (IDL) to Fortran, which still is an important language of many scientific and engineering applications. Using the given IDL to C++ mapping and a wrapping technique, an effective coupling of Fortran codes can be realized that in most cases avoids data copying. A way to use the IDL sequence type for the data transfer is shown, which allows highly flexible interfaces.     

A Comparison of Co-Array Fortran and OpenMP Fortran for SPMD Programming

Co-Array Fortran, formally called F^––, is a small set of extensions to Fortran 90/95 for Single-Program-Multiple-Data (SPMD) parallel processing. OpenMP Fortran is a set of compiler directives that provide a high level interface to threads in Fortran, with both thread-local and thread-shared memory. OpenMP is primarily designed for loop-level directive-based parallelization, but it can also be used for SPMD programs by spawning multiple threads as soon as the program starts and having each thread then execute the same code independently for the duration of the run. The similarities and differences between these two SPMD programming models are described.Co-Array Fortran can be implemented using either threads or processes, and is therefore applicable to a wider range of machine types than OpenMP Fortran. It has also been designed from the ground up to support the SPMD programming style. To simplify the implementation of Co-Array Fortran, a formal Subset is introduced that allows the mapping of co-arrays onto standard Fortran arrays of higher rank. An OpenMP Fortran compiler can be extended to support Subset Co-Array Fortran with relatively little effort.     

Runtime support for scalable programming in Java

The paper research is concerned with enabling parallel, high-performance computation—in particular development of scientific software in the network-aware programming language, Java. Traditionally, this kind of computing was done in Fortran. Arguably, Fortran is becoming a marginalized language, with limited economic incentive for vendors to produce modern development environments, optimizing compilers for new hardware, or other kinds of associated software expected of by today’s programmers. Hence, Java looks like a very promising alternative for the future. The paper will discuss in detail a particular environment called HPJava. HPJava is the environment for parallel programming—especially data-parallel scientific programming—in Java. Our HPJava is based around a small set of language extensions designed to support parallel computation with distributed arrays, plus a set of communication libraries. A high-level communication API, Adlib, is developed as an application level communication library suitable for our HPJava. This communication library supports collective operations on distributed arrays. We include Java Object as one of the Adlib communication data types. So we fully support communication of intrinsic Java types, including primitive types, and Java object types.     

Future scientific programming on parallel machines

A language for large scientific applications should facilitate encoding and debugging of programs at the highest level possible. At the same time it should facilitate generation of efficient code for parallel machines. Often these two requirements are conflicting, and trade-offs must be made. Functional and other declarative languages offer relief on both counts. The use of higher-order functions, especially in carried forms, can raise the level of programming dramatically. In addition, such languages often have straightforward operational semantics, thereby providing tremendous opportunities for parallel execution. Programs written in declarative languages thus eliminate the problem of “detecting parallelism.” This paper illustrates programming in one such language, Id Nouveau, and contrasts it with programming in Fortran. Using an excerpt from an application known as Simple, it is shown how a program can be composed in Id Nouveau from small functions that directly relate to the mathematical and physical concepts of the problem. The difficulty of expressing these concepts in Fortran is discussed. Finally, it is shown that by performing simple transformations, such as in-line substitution of functions, the resulting Id Nouveau code becomes as efficient as an equivalent Fortran program written to run efficiently on a parallel machine.     

A parallel-programming process model

A process model is presented for constructing and executing parallel programs on a shared-memory multiprocessor running under Unix. The model involves some simple extensions to the standard Unix process model, a set of language extensions, runtime library support, and additional operating-system support. The model is easy to use, and it supports several higher-level parallel programming constructs in several languages, including microtasking in C and Fortran and multitasking in Ada and C++. It frees programmers to concentrate on parallel algorithms instead of low-level implementation details, and it yields good performance     

Portable parallelizing Fortran compiler

The Portable Parallelizing Fortran Compiler (PPFC) is an additional component for the portable programming environment developed in Tel-Aviv University for scientific code. This environment supports portable and efficient programming of diverse MIMD multiprocessors, both distributed- and shared-memory. Till now this environment has consisted of two tools: the Virtual Machine for MultiProcessors (VMMP) and the Portable Parallelizing Pascal compiler (P³C). We have added the PPFC which is an automatic parallelizer compiler for the Fortran language. The compiler is fully automatic (does not require additional declarations to assist parallelization), which is characterized by loops operating on regular data structures, and produces efficient and portable code for a variety of multiprocessors from the same serial code. The parallel implementation uses the VMMP, which is a software package that provides a coherent set of services for explicitly parallel application programs running on diverse MIMD multiprocessors. VMMP is intended to simplify parallel program writing and to promote portable and efficient programming. The PPFC parallelized 12 out of the 24 Livermore Loops. It was also applied to parallelize all the 14 Fortran application programs that where parallelized by the P³C and achieved the same speed-ups and efficiencies. In most examples the PPFC achieved high speed-ups and efficiencies on all target multiprocessors. The PPFC emphasizes efficiency and code portability. Although PPFC employs a relatively simple data flow analysis, it produces efficient code for various widely used application programs.     

Compiling High Performance Fortran for distributed-memory architectures

High Performance Fortran (HPF) is a data-parallel language that provides a high-level interface for programming scientific applications, while delegating to the compiler the task of generating explicitly parallel message-passing programs. This paper provides an overview of HPF compilation and runtime technology for distributed-memory architectures, and deals with a number of topics in some detail. In particular, we discuss distribution and alignment processing, the basic compilation scheme and methods for the optimization of regular computations. A separate section is devoted to the transformation and optimization of independent loops with irregular data accesses. The paper concludes with a discussion of research issues and outlines potential future development paths of the language.     

Sequential file processing in fortran IV

The standard I/O facility for sequential disk/tape file handling in a Fortran IV IBM 360/370 Disk Operating System environment has some marked shortcomings, the most serious of which is that blocking of records is not provided for. This paper describes SAMFOR⁴ (Sequential Access Method in Fortran IV), a set of Fortran callable subprograms and a file declaration facility that enables the Fortran programmer to access and create ‘standard’ sequential files. Thus inter language compatibility of files is obtained. A manyfold increase in effectiveness may also be achieved.     

jME元计算环境对Fortran并行程序设计的支持

介绍iME元计算环境对Fortran并行程序设计的支持。分析了Java和Fortran语言对元计算环境的支持及不足，然后论述了iME元计算环境支持Fortran并行程序设计的有关关键技术，包括保证同构性的措施、系统参数的获取、格式化输出和并行编程支持等。     

The advantages of Fortran 90

Fortran 77 is the most widely used language for scientific programming. Its long-awaited revision is now called Fortran 90. It was finalized (down to the last editorial detail) on 11 April 1991, published as an ISO Standard in August 1991, and the first compiler is now on the market. This seems an appropriate moment to review its history and explain its advantages.     

UC: A Set-Based Language for Data-Parallel Programming

UC is a data-parallel extension of C designed for scientific computations on synchronous and asynchronous parallel architectures. The primary constructs of the language include sets, reductions, and parallel and asynchronous composition. Its communication model is that of a globally addressable memory, with no syntactic distinction between local and remote data references, Unlike most existing data-parallel languages, UC programs may be synchronized at multiple levels of granularity, from a strict expression-level synchronization to a coarser statement or function-level synchronization. This paper describes the language and its implementation on the Connection Machine CM-2. Experimental measurements that compare the performance of the UC compiler with that of programs written in commercial parallel languages such as CM Fortran, C*, and *Lisp are also presented.     

Specifying and Automatically Generating a Specialization Tool for Fortran 90

Partial evaluation is an optimization technique traditionally used in compilation. We have adapted this technique to the understanding of scientific application programs during their maintenance. We have implemented a tool that analyzes Fortran 90 application programs and performs an interprocedural pointer analysis. This paper presents a dynamic semantics of Fortran 90 and manually derives a partial evaluator from this semantics. The tool implementing the specifications is also detailed. The partial evaluator has been implemented in a generic programming environment and a graphical interface has been developed to visualize the information computed during the partial evaluation (values of variables, already analyzed procedures, scope of variables, removed statements, etc.).     

The Interval-Enhanced GNU Fortran Compiler

Compiler support for intervals as intrinsic data types is essential for promoting the development and wide-spread use of interval software. It also plays an important role in encouraging the development of hardware support for interval arithmetic. This paper describes modifications made to the GNU Fortran Compiler to provide support for interval arithmetic. These modifications are based on a recently proposed Fortran 77 Interval Arithmetic Specification, which provides a standard for supporting interval arithmetic in Fortran. This paper also describes the design of the compiler's interval runtime libraries and the methodology used to test the compiler. The compiler and runtime libraries are designed to be portable to platforms that support the IEEE 754 floating point standard.     

Fei Teng 64 Stream Processing System: Architecture, Compiler, and Programming

The stream architecture is a novel microprocessor architecture with wide application potential. It is critical to study how to use the stream architecture to accelerate scientific computing programs. However, existing stream processors and stream programming languages are not designed for scientific computing. To address this issue, we design and implement a 64-bit stream processor, Fei Teng 64 (FT64), which has a peak performance of 16 Gflops. FT64 supports two kinds of communications, message passing and stream communications, based on which, an interconnection architecture is designed for a FT64-based high-performance computer. This high-performance computer contains multiple modules, with each module containing eight FT64s. We also design a novel stream programming language, Stream Fortran 95 (SF95), together with the compiler SF95Compiler, so as to facilitate the development of scientific applications. We test nine typical scientific application kernels on our FT64 platform to evaluate this design. The results demonstrate the effectiveness and efficiency of FT64 and its compiler for scientific computing.     

Runtime and language support for compiling adaptive irregular programs on distributed-memory machines

In many scientific applications, arrays containing data are indirectly indexed through indirection arrays. Such scientific applications are called irregular programs and are a distinct class of applications that require special techniques for parallelization. This paper presents a library called CHAOS, which helps users implement irregular programs on distributed-memory message-passing machines, such as the Paragon, Delta, CM-5 and SP-1. The CHAOS library provides efficient runtime primitives for distributing data and computation over processors; it supports efficient index translation mechanisms and provides users high-level mechanisms for optimizing communication. CHAOS subsumes the previous PARTI library and supports a larger class of applications. In particular, it provides efficient support for parallelization of adaptive irregular programs where indirection arrays are modified during the course of computation. To demonstrate the efficacy of CHAOS, two challenging real-life adaptive applications were parallelized using CHAOS primitives: a molecular dynamics code, CHARMM, and a particle-in-cell code, DSMC. Besides providing runtime support to users, CHAOS can also be used by compilers to automatically parallelize irregular applications. This paper demonstrates how CHAOS can be effectively used in such a framework. By embedding CHAOS primitives in the Syracuse Fortran 90D/HPF compiler, kernels taken from the CHARMM and DSMC codes have been automatically parallelized.     

The regeneration of Fortran software

There is a substantial body of existing Fortran software that has considerable scientific and commercial value, but whose potential is sometimes difficult to exploit to the full because of a lack of structure and internal documentation. This article discusses, by means of an example, how the OLYMPUS COMPOSITOR can be used to regenerate such software semi-automatically so that it meets improved documentation standards. Comments and headings can be edited in on-line, using a free format, and the COMPOSITOR then produces a clear standard layout in which the Fortran statement numbers are correlated with the decimally numbered sections and subsections of an individual routine, and the meaning of the code is clarified by appropriate indentation and cross-referencing. Using the OLYMPUS GENERATOR one can also restructure the COMMON blocks and construct indexes of variables. It is suggested that such techniques can materially enhance the usefulness of a great deal of Fortran software, including some of the programs already included in the CPC Program Library.