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GTC ON-DEMAND

Presentation
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Abstract:
We will present a detailed description of how the hardware implements the graphics pipeline. The hardware's pipeline and motivation behind both high- and low-level design choices are described. We provide practical usage scenarios how Vulkan, OpenGL and GLSL are best used and how to avoid performance pitfalls. Through the use of this information and the latest graphics API features, the GPU can be leveraged very efficiently do more work autonomously of the CPU and increase overall throughput.
We will present a detailed description of how the hardware implements the graphics pipeline. The hardware's pipeline and motivation behind both high- and low-level design choices are described. We provide practical usage scenarios how Vulkan, OpenGL and GLSL are best used and how to avoid performance pitfalls. Through the use of this information and the latest graphics API features, the GPU can be leveraged very efficiently do more work autonomously of the CPU and increase overall throughput.  Back
 
Topics:
Real-Time Graphics, Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6138
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Abstract:
We will present the latest OpenGL technology from NVIDIA (NV_command_list) and rendering algorithms to render large scenes, typically found in CAD/DCC applications. Through the use of new powerful OpenGL extensions, the GPU can be leveraged very efficiently to do more work autonomously of the CPU. We provide algorithms and usage scenarios for scenes made out of many parts (millions) including GPU creating its own work for rendering (occlusion culling) and transformation updates. The data management allows to minimize data transfers and a high flexibility to make changes to the scene, so that interactive editing and viewing of large data sets is possible.
We will present the latest OpenGL technology from NVIDIA (NV_command_list) and rendering algorithms to render large scenes, typically found in CAD/DCC applications. Through the use of new powerful OpenGL extensions, the GPU can be leveraged very efficiently to do more work autonomously of the CPU. We provide algorithms and usage scenarios for scenes made out of many parts (millions) including GPU creating its own work for rendering (occlusion culling) and transformation updates. The data management allows to minimize data transfers and a high flexibility to make changes to the scene, so that interactive editing and viewing of large data sets is possible.  Back
 
Topics:
Real-Time Graphics, Performance Optimization, Developer - Algorithms, Rendering & Ray Tracing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5135
Streaming:
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