Name
Abstract | ||
|---|---|---|
In the field of parallel computing, the late leader Ken Kennedy, has raised a concern in early 1990s: "Is Parallel Computing Dead?" Now, we have witnessed the tremendous momentum of the "second spring" of parallel computing in recent years. But, what lesson should we learn from the history of parallel computing when we are walking out from the bottom state of the field? To this end, this paper examines the disappointing state of the work in parallel Turing machine models in the past 50 years of parallel computing research. Lacking a solid yet intuitive parallel Turing machine model will continue to be a serious challenge. Our paper presents an attempt to address this challenge - by presenting a proposal of a parallel Turing machine model - the PTM model. We also discuss why we start our work in this paper from a parallel Turing machine model instead of other choices. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-47099-3_16 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Parallel Turing machine,Codelet,Abstract architecture,Parallel computing | Computer science,Artificial intelligence,Distributed computing,Probabilistic Turing machine,Universal Turing machine,NSPACE,Parallel computing,Super-recursive algorithm,Turing machine,Multitape Turing machine,Turing machine examples,Non-deterministic Turing machine,Machine learning | Conference |
Volume | ISSN | Citations |
9966 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 14 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Qu | 1 | 13 | 2.68 |
| Jin Yan | 2 | 1 | 0.36 |
| Guang R. Gao | 3 | 2661 | 265.87 |