Programming graphics processing units in the RVC-CAL dataflow language
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | Electronic Proceedings of the 2015 IEEE International Workshop on Signal Processing Systems, SiPS 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Volume | 2015-December |
| ISBN (Electronic) | 9781467396042 |
| DOIs | |
| Publication status | Published - 2 Dec 2015 |
| Publication type | A4 Article in a conference publication |
| Event | IEEE International Workshop on Signal Processing Systems, SiPS 2015 - Hangzhou, China Duration: 14 Oct 2015 → 16 Oct 2015 |
Conference
| Conference | IEEE International Workshop on Signal Processing Systems, SiPS 2015 |
|---|---|
| Country | China |
| City | Hangzhou |
| Period | 14/10/15 → 16/10/15 |
Abstract
The interest towards programming of streaming applications using dataflow models of computation has been increasing steadily in the recent years. Among the numerous dataflow formalisms, the ISO-standardized RVC-CAL dataflow language has offered a solid basis for programming tool development and research. To this date RVC-CAL programming tools have enabled transforming dataflow programs into concurrent executables for multicore processors, as well as for generating synthesizable hardware descriptions. In this paper it is shown how the RVC-CAL dataflow language can be used for programming graphics processing units (GPUs) with high efficiency. Considering the processing architectures of recent mobile and desktop computing devices, this advance is of high importance, as most consumer devices contain a graphics processing unit nowadays. To evaluate the proposed solution, the paper presents a video processing application case study. At best, the solution is shown to provide a speedup of 42× over single-threaded CPU execution.
ASJC Scopus subject areas
Keywords
- Dataflow computing, design automation, parallel processing