Optimization for an array computer
ACM SIGPLAN Notices
Compiling Fortran 8x array features for the connection machine computer system
PPEALS '88 Proceedings of the ACM/SIGPLAN conference on Parallel programming: experience with applications, languages and systems
High performance Fortran language specification (part III)
ACM SIGPLAN Fortran Forum
A Language for Array and Vector Processors
ACM Transactions on Programming Languages and Systems (TOPLAS)
Glypnir—a programming language for Illiac IV
Communications of the ACM
IEEE Parallel & Distributed Technology: Systems & Technology
The ILLIAC IV FORTRAN compiler
Proceedings of the conference on Programming languages and compilers for parallel and vector machines
Array processing on an array processor
Proceedings of the conference on Programming languages and compilers for parallel and vector machines
Multiprocessor software design
ACM '80 Proceedings of the ACM 1980 annual conference
Users' experience with the ILLIAC IV system and its programming languages
ACM SIGPLAN Notices
A method for controlling parallelism in programming languages
ACM SIGPLAN Notices
An Approach To Data Distributions in Chapel
International Journal of High Performance Computing Applications
Access and Alignment of Data in an Array Processor
IEEE Transactions on Computers
From FORTRAN 77 to locality-aware high productivity languages for peta-scale computing
Scientific Programming - Fortran Programming Language and Scientific Programming: 50 Years of Mutual Growth
| Hi-index | 48.24 |
As part of an effort to design and implement a Fortran compiler on the ILLIAC IV, an extended Fortran, called IVTRAN, has been developed. This language provides a means of expressing data and control structures suitable for exploiting ILLIAC IV parallelism. This paper reviews the hardware characteristics of the ILLIAC and singles out unconventiona features which could be expected to influence langluage (and compiler) design. The implications of these features for data layout and algorithm structure are discussed, and the conclusion is drawn that data allocation rather than code structuring is the crucial ILLIAC optimization problem. A satisfactory method of data allocation is then presented. Language structures to utilize this storage method and express parallel algorithms are described.