GPU Shader Analysis and Power Optimization Model

Authors

  • Guruprasad Konnurmath School of Computer Science and Engineering, KLE Technological University, India
  • Satyadhyan Chickerur School of Computer Science and Engineering, KLE Technological University, India
Volume: 14 | Issue: 1 | Pages: 12925-12930 | February 2024 | https://doi.org/10.48084/etasr.6695

Abstract

With the rapid advancements in 3D game technology, workload characterization has become crucial for each new generation of games. The increased complexity of scenes in 3D games allows for stunning real-time visual quality. However, handling such workloads results in significant power consumption over the GPU rendering pipeline. The focus of the current paper is low power optimization, targeting texture memory, geometry engine, pixel, and rasterization, as these components are significant contributors to the power consumption of a typical GPU. The proposed methodology integrates the Dynamic Voltage Frequency Scaling (DVFS) technique, adjusting voltage and frequency based on the workload analysis of frame rates with respect to the scenes of 3D games. Frame rates of 60 fps and 30 fps are set up to understand and manage the workload on frames. Furthermore, for comparative analysis, various frame-level power analysis schemes such as No DVFS implemented, Frame History Method, Frame Signature Method, and Tiled History-based are introduced. The proposed scheme consistently surpasses these frame-level schemes, with fewer missed deadlines, while having the lowest energy consumption per frame rate. The implementation resulted in a remarkable 65% improvement in quality, indicated by a reduction in deadline misses, along with a substantial 60% energy saving.

Keywords:

3D scene rendering pipeline, frames, GPU, DVFS, geometry, pixel, texture, workload

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How to Cite

[1]
Konnurmath, G. and Chickerur, S. 2024. GPU Shader Analysis and Power Optimization Model. Engineering, Technology & Applied Science Research. 14, 1 (Feb. 2024), 12925–12930. DOI:https://doi.org/10.48084/etasr.6695.

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