Data flow graph optimization in ifi
Proc. of a conference on Functional programming languages and computer architecture
An overview of the RMIT/CSIRO parallel systems architecture project
Australian Computer Journal
Code Optimization for Tagged-Token Dataflow Machines
IEEE Transactions on Computers
A report on the Sisal language project
Journal of Parallel and Distributed Computing - Special issue: data-flow processing
Retire Fortran?: a debate rekindled
Communications of the ACM
On the expressive power of programming languages
ESOP '90 Selected papers from the symposium on 3rd European symposium on programming
Scheduling EPL programs for parallel processing
Languages, compilers and run-time environments for distributed memory machines
The dataflow time and space complexity of FFTs
Journal of Parallel and Distributed Computing - Special issue on dataflow and multithreaded architectures
Concepts and paradigms of object-oriented programming
ACM SIGPLAN OOPS Messenger
Graph transformation algorithms for array memory optimization in applicative languages
Graph transformation algorithms for array memory optimization in applicative languages
| Hi-index | 0.00 |
In this article, we discuss two programming language features that have value for expressibility and efficiency: nonstrictness and nondeterminism. Our work arose while assessing ways to enhance a currently successful language, SISAL [McGraw et al. 1985]. The questions of how best to include these features, if at all, has led not to conclusions but to an impetus to explore the answers in an objective way. We will retain strictness for efficiency reasons and explore the limits it may impose, and we will experiment with a carefully controlled form of nondeterminism to assess its expressive power.