Name
Abstract | ||
|---|---|---|
Concurrent object-oriented programming (COOP) languages focus the abstraction and encapsulation power of abstract data types on the problem of concurrency control. In particular, pure fine-grained concurrent object-oriented languages (as opposed to hybrid or data parallel) provides the programmer with a simple, uniform, and flexible model while exposing maximum concurrency. While such languages promise to greatly reduce the complexity of large-scale concurrent programming, the popularity of these languages has been hampered by efficiency which is often many orders of magnitude less than that of comparable sequential code. We present a sufficiency set of techniques which enables the efficiency of fine-grained concurrent object-oriented languages to equal that of traditional sequential languages (like C) when the required data is available. These techniques are empirically validated by the application to a COOP implementation of the Livermore Loops. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1145/199448.199524 | POPL |
Keywords | Field | DocType |
sequential efficiency,coop implementation,large-scale concurrent programming,data parallel,abstract data type,fine-grained concurrent object-oriented language,concurrency control,required data,concurrent object-oriented programming,maximum concurrency,comparable sequential code,object oriented language,denotational semantics,constraint programming,reactive systems,concurrent object oriented programming | Fifth-generation programming language,Data structure,Second-generation programming language,Programming language,Comparison of multi-paradigm programming languages,Computer science,Theoretical computer science,Parallel programming model,Control flow analysis,Concurrent object-oriented programming,Third-generation programming language | Conference |
ISBN | Citations | PageRank |
0-89791-692-1 | 22 | 2.26 |
References | Authors | |
24 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Plevyak | 1 | 156 | 19.65 |
| Xingbin Zhang | 2 | 73 | 9.41 |
| Andrew A. Chien | 3 | 3696 | 405.97 |