• Journal of Korean Institute of Industrial Engineers
• /
• v.19 no.3
• /
• pp.59-70
• /
• 1993

This paper presents the results of experiments which compare the software complexity between programming languages, i.e, FORTRAN IV and FORTRAN 77, PASCAL and C language, respectively. Each experiment is performed to compare the complexity between programs of same problems using Halstead's method based on operator, and McCabe's based on data flow. As the results of 25 test programs experiments, FORTRAN 77 languages shows superiority to FORTRAN IV languages, and C than that of PASCAL languages, in the aspect of the global software complexity.

• 전기의세계
• /
• v.25 no.5
• /
• pp.460-460
• /
• 1976

ANSI FORTRAN 표준화 위원회(X3J3)는 새로운 America National Standard Fortran의 초안을 마련하였다. 또한 이 초안은 여러 부분을 취급하였고 전체적으로도 규명하고 있다. 부분적으로는 처리시 최소한의 기억용량 설정 Fortran Processor의 성장을 위한 개발 유지등에 노력했으며 전체적으로는 하나의 언어로 규정하였다. 1975년 8월에 새로운 Fortran을 위하여 아래 사항등이 ANSI X3J3에서 투표되었으며 가결되었다. 그 주요 내용을 현재 사용중인 ZBM 360/370 Fortran Language와 비교하여 열거해 보자.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.271-271
• /
• 2018

그래픽 처리 장치(GPU: Graphic Processing Units)는 그래픽 처리에 특화된 수많은 산술논리연산자 (ALU: Arithmetic Logic Unit)와 이에 관련된 인스트럭션Instruction)으로 인해 중앙 처리 장치(CPU: Central Processing Units) 보다 훨씬 빠른 계산 처리를 수행할 수 있다. 최근에는 FORTRAN에 의해 구현된 많은 수치모형들이 현실적인 모델링 방법의 발달로 인해 더 많은 계산량과 계산시간을 필요로 한다. 이 연구에서는 GPU 상의 범용 계산GPGPU : General-Purpose computing on Graphics Processing Units) 기반 운동파 강우유출모형(Kinematic Wave Rainfall-Runoff Model)이 CUDA(Compute Unified Device Architecture) FORTRAN을 사용하여 구현되었다. CUDA FORTRAN 운동파 강우유출모형의 계산 결과는 검증된 CPU 기반 운동파 강우유출모형의 계산 결과와 비교하여 검증되었으며, 잘 일치함을 보여 주었다. CUDA FORTRAN 운동파 강우유출모형은 CPU 기반 모형에 비해 약 20 배 더 빠른 계산 시간을 보였다. 또한 계산 영역이 커짐에 따라 CPU 버전에 비해 CUDA FORTRAN 버전의 계산 효율이 향상되었다.

• 전기의세계
• /
• v.16 no.4
• /
• pp.24-29
• /
• 1967

이글은 다음과 같은 내용으로 구성되어 있다. 1. 자동 Programming과 FORTRAN 개설 2. FORTRAN해설 3.FORTRAN 규약

• Atmosphere
• /
• v.23 no.2
• /
• pp.231-235
• /
• 2013

We parallelized WRF major physics routines for Nvidia GP-GPUs with CUDA Fortran. GP-GPUs are originally designed for graphic processing, but show high performance with low electricity for calculating numerical models. In the CUDA environment, a data domain is allocated into thread blocks and threads in each thread block are computing in parallel. We parallelized the WRF program to use of thread blocks efficiently. We validated the GP-GPU program with the original CPU program, and the WRF model using GP-GPUs shows efficient speedup.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.7
• /
• pp.379-386
• /
• 2004

We designed a portable parallel library HPCL(High Performance Computing Library) with following objectives: (1) to provide a close relationship between the parallel code and the original sequential code that will help future versions of the sequential code and (2) to enhance performance of the parallel code. The library is an interface written in C and Fortran programming languages between MPI(Message Passing Interface) and parallel programs in Fortran. Performance results were determined on clusters of PC's and IBM SP4.

• Journal of the Korea Society of Computer and Information
• /
• v.4 no.2
• /
• pp.113-119
• /
• 1999

In this thesis Fortran and C Libraries are implemented and applied to the real situation of statistical simulation. They contain the routines of random number generators and for various statistical distributions which often used in stochastic simulation. They also contain the routines for calculating probabilities and upper quantiles of various statistical distributions Each routine of them was tested by the various procedures and proved to be very stable

• Proceedings of the Korean Society of Laser Processing Conference
• /
• 2001.11a
• /
• pp.13-16
• /
• 2001

• Computational Structural Engineering
• /
• v.2 no.3
• /
• pp.26-29
• /
• 1989

두가지 또는 그 이상의 언어를 각각의 언어의 장점만을 취하여 혼합한다면 매우 효율적인 프로그램을 만들 수 있게 된다. 이 글에서는 공학문제 해결에 많이 쓰여온 FORTRAN과 C언어의 PC에서의 Interface에 대해 논하고 구조공학 분야에서의 활용방안의 일단을 제시하고자 한다.

• Journal of Korea Water Resources Association
• /
• v.52 no.11
• /
• pp.887-894
• /
• 2019

We proposed a GPU (Grapic Processing Unit) accelerated kinematic wave model for rainfall runoff simulation and tested the accuracy and speed up performance of the proposed model. The governing equations are the kinematic wave equation for surface flow and the Green-Ampt model for infiltration. The kinematic wave equations were discretized using a finite volume method and CUDA fortran was used to implement the rainfall runoff model. Several numerical tests were conducted. The computed results of the GPU accelerated kinematic wave model were compared with several measured and other numerical results and reasonable agreements were observed from the comparisons. The speed up performance of the GPU accelerated model increased as the number of grids increased, achieving a maximum speed up of approximately 450 times compared to a CPU (Central Processing Unit) version, at least for the tested computing resources.