Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | GPCE 2015: Proceedings of the 2015 ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences |
| Herausgeber/-innen | Christian Kastner, Aniruddha Gokhale |
| Seiten | 141-150 |
| Seitenumfang | 10 |
| ISBN (elektronisch) | 9781450336871 |
| Publikationsstatus | Veröffentlicht - Okt. 2015 |
| Extern publiziert | Ja |
| Veranstaltung | 14th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, GPCE 2015 - Pittsburgh, USA / Vereinigte Staaten Dauer: 26 Okt. 2015 → 27 Okt. 2015 |
Abstract
Rendering performance is an everlasting goal of computer graphics and significant driver for advances in both, hardware architecture and algorithms. Thereby, it has become possible to apply advanced computer graphics technology even in low-cost embedded appliances, such as car instruments. Yet, to come up with an efficient implementation, developers have to put enormous efforts into hardware/problem-specific tailoring, fine-tuning, and domain exploration, which requires profound expert knowledge. If a good solution has been found, there is a high probability that it does not work as well with other architectures or even the next hardware generation. Generative DSL-based approaches could mitigate these efforts and provide for an efficient exploration of algorithmic variants and hardware-specific tuning ideas. However, in vertically organized industries, such as automotive, suppliers are reluctant to introduce these techniques as they fear loss of control, high introduction costs, and additional constraints imposed by the OEM with respect to software and tool-chain certification. Moreover, suppliers do not want to share their generic solutions with the OEM, but only concrete instances. To this end, we propose a light-weight and incremental approach for meta programming of graphics applications. Our approach relies on an existing formulation of C-like languages that is amenable to meta programming, which we extend to become a lightweight language to combine algorithmic features. Our method provides a concise notation for meta programs and generates easily sharable output in the appropriate C-style target language.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
- Informatik (insg.)
- Software
- Informatik (insg.)
- Angewandte Informatik
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- BibTex
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GPCE 2015: Proceedings of the 2015 ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences. Hrsg. / Christian Kastner; Aniruddha Gokhale. 2015. S. 141-150.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Lightweight, Generative Variant Exploration for High-Performance Graphics Applications
AU - Selgrad, Kai
AU - Lier, Alexander
AU - Köferl, Franz
AU - Stamminger, Marc
AU - Lohmann, Daniel
PY - 2015/10
Y1 - 2015/10
N2 - Rendering performance is an everlasting goal of computer graphics and significant driver for advances in both, hardware architecture and algorithms. Thereby, it has become possible to apply advanced computer graphics technology even in low-cost embedded appliances, such as car instruments. Yet, to come up with an efficient implementation, developers have to put enormous efforts into hardware/problem-specific tailoring, fine-tuning, and domain exploration, which requires profound expert knowledge. If a good solution has been found, there is a high probability that it does not work as well with other architectures or even the next hardware generation. Generative DSL-based approaches could mitigate these efforts and provide for an efficient exploration of algorithmic variants and hardware-specific tuning ideas. However, in vertically organized industries, such as automotive, suppliers are reluctant to introduce these techniques as they fear loss of control, high introduction costs, and additional constraints imposed by the OEM with respect to software and tool-chain certification. Moreover, suppliers do not want to share their generic solutions with the OEM, but only concrete instances. To this end, we propose a light-weight and incremental approach for meta programming of graphics applications. Our approach relies on an existing formulation of C-like languages that is amenable to meta programming, which we extend to become a lightweight language to combine algorithmic features. Our method provides a concise notation for meta programs and generates easily sharable output in the appropriate C-style target language.
AB - Rendering performance is an everlasting goal of computer graphics and significant driver for advances in both, hardware architecture and algorithms. Thereby, it has become possible to apply advanced computer graphics technology even in low-cost embedded appliances, such as car instruments. Yet, to come up with an efficient implementation, developers have to put enormous efforts into hardware/problem-specific tailoring, fine-tuning, and domain exploration, which requires profound expert knowledge. If a good solution has been found, there is a high probability that it does not work as well with other architectures or even the next hardware generation. Generative DSL-based approaches could mitigate these efforts and provide for an efficient exploration of algorithmic variants and hardware-specific tuning ideas. However, in vertically organized industries, such as automotive, suppliers are reluctant to introduce these techniques as they fear loss of control, high introduction costs, and additional constraints imposed by the OEM with respect to software and tool-chain certification. Moreover, suppliers do not want to share their generic solutions with the OEM, but only concrete instances. To this end, we propose a light-weight and incremental approach for meta programming of graphics applications. Our approach relies on an existing formulation of C-like languages that is amenable to meta programming, which we extend to become a lightweight language to combine algorithmic features. Our method provides a concise notation for meta programs and generates easily sharable output in the appropriate C-style target language.
KW - Exploratory programming
KW - General purpose code generation
KW - Prototyping
KW - Ray tracing
UR - http://www.scopus.com/inward/record.url?scp=84963517332&partnerID=8YFLogxK
U2 - 10.1145/2814204.2814220
DO - 10.1145/2814204.2814220
M3 - Conference contribution
AN - SCOPUS:84963517332
SP - 141
EP - 150
BT - GPCE 2015: Proceedings of the 2015 ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences
A2 - Kastner, Christian
A2 - Gokhale, Aniruddha
T2 - 14th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, GPCE 2015
Y2 - 26 October 2015 through 27 October 2015
ER -