Cg: a system for programming graphics hardware in a C-like language. The latest real-time graphics architectures include programmable floating-point vertex and fragment processors, with support for data-dependent control flow in the vertex processor. We present a programming language and a supporting system that are designed for programming these stream processors. The language follows the philosophy of C, in that it is a hardware-oriented, general-purpose language, rather than an application-specific shading language. The language includes a variety of facilities designed to support the key architectural features of programmable graphics processors, and is designed to support multiple generations of graphics architectures with different levels of functionality. The system supports both of the major 3D graphics APIs: OpenGL and Direct3D. This paper identifies many of the choices that we faced as we designed the system, and explains why we made the decisions that we did.

This software is also peer reviewed by journal TOMS.

References in zbMATH (referenced in 31 articles )

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  1. Mantas, José Miguel; de la Asunción, Marc; Castro, Manuel J.: An introduction to GPU computing for numerical simulation (2016)
  2. D’Azevedo, E.F.; Nintcheu Fata, S.: On the effective implementation of a boundary element code on graphics processing units using an out-of-core LU algorithm (2012)
  3. Kingyens, Jeffrey; Steffan, J.Gregory: The potential for a GPU-like overlay architecture for FPGAs (2011)
  4. Mittmann, Adiel; Nobrega, Tiago; Comunello, Eros; Pinto, Juliano P.O.; Dellani, Paulo Roberto; Stoeter, Peter; Von Wangenheim, Aldo: Performing real-time interactive fiber tracking (2011)
  5. Cowan, Brent; Kapralos, Bill: GPU-based real-time acoustical occlusion modeling (2010)
  6. Kampolis, I.C.; Trompoukis, X.S.; Asouti, V.G.; Giannakoglou, K.C.: CFD-based analysis and two-level aerodynamic optimization on graphics processing units (2010)
  7. Okitsu, Yusuke; Ino, Fumihiko; Hagihara, Kenichi: High-performance cone beam reconstruction using CUDA compatible GPUs (2010)
  8. Park, Jung-Wook; Yang, Hoon-Mo; Park, Gi-Ho; Kim, Shin-Dug; Weems, Charles C.: An instruction-systolic programmable shader architecture for multi-threaded 3D graphics processing (2010)
  9. Sunarso, Alfeus; Tsuji, Tomohiro; Chono, Shigeomi: GPU-accelerated molecular dynamics simulation for study of liquid crystalline flows (2010)
  10. Su, Yang; Xu, Zhijie: Parallel implementation of wavelet-based image denoising on programmable PC-grade graphics hardware (2010)
  11. Lastra, Miguel; Mantas, José M.; Ureña, Carlos; Castro, Manuel J.; García-Rodríguez, José A.: Simulation of shallow-water systems using graphics processing units (2009)
  12. Lin, Yu-Te; Chen, Peng-Sheng: Compiler support for general-purpose computation on GPUs (2009)
  13. Liu, Hui; Shao, Zili; Wang, Meng; Du, Junzhao; Xue, Chun Jason; Jia, Zhiping: Combining coarse-grained software pipelining with DVS for scheduling real-time periodic dependent tasks on multi-core embedded systems (2009)
  14. Preis, Tobias; Virnau, Peter; Paul, Wolfgang; Schneider, Johannes J.: GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model (2009)
  15. Grabner, Markus; Pock, Thomas; Gross, Tobias; Kainz, Bernhard: Automatic differentiation for GPU-accelerated 2D/3D registration (2008)
  16. Ho, Tze-Yui; Lam, Ping-Man; Leung, Chi-Sing: Parallelization of cellular neural networks on GPU (2008)
  17. Jung, Jin Hyuk; O’leary, Dianne P.: Implementing an interior point method for linear programs on a CPU-GPU system (2008)
  18. Li, Haiyan; Zhang, Chunyuan; Li, Li; Ren, Ju: Transform coding on programmable stream processors (2008)
  19. Liu, Yu; Yuan, Hong-Chun; Liang, Zheng: Study on acceleration technique for ADI-FDTD algorithm based on GPU (2008)
  20. Sanderson, Allen R.; Meyer, Miriah D.; Kirby, Robert M.; Johnson, Chris R.: A framework for exploring numerical solutions of advection-reaction-diffusion equations using a GPU-based approach (2008)

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