Auto-tuning Interactive Ray Tracing using an Analytical GPU Architecture Model
Författare
Summary, in English
This paper presents a method for auto-tuning interactive ray tracing on GPUs using a hardware model. Getting full performance from modern GPUs is a challenging task. Workloads which require a guaranteed performance over several runs must select parameters for the worst performance of all runs. Our method uses an analyti- cal GPU performance model to predict the current frame’s render- ing time using a selected set of parameters. These parameters are then optimised for a selected frame rate performance on the partic- ular GPU architecture. We use auto-tuning to determine parameters such as phong shading, shadow rays and the number of ambient oc- clusion rays. We sample a priori information about the current ren- dering load to estimate the frame workload. A GPU model is run iteratively using this information to tune rendering parameters for a target frame rate. We use the OpenCL API allowing tuning across different GPU architectures. Our auto-tuning enables the render- ing of each frame to execute in a predicted time, so a target frame rate can be achieved even with widely varying scene complexities. Using this method we can select optimal parameters for the cur- rent execution taking into account the current viewpoint and scene, achieving performance improvements over predetermined parame- ters.
Avdelning/ar
Publiceringsår
2012
Språk
Engelska
Publikation/Tidskrift/Serie
The ACM International Conference Proceedings Series
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Dokumenttyp
Konferensbidrag
Ämne
- Computer Science
Nyckelord
- GPU Model
- Ray Tracing
- Auto-tuning
- OpenCL
Conference name
GPGPU5
Conference date
2012-03-03
Conference place
London, United Kingdom
Status
Published
Forskningsgrupp
- Computer Graphics