PPT-Harmonica GPU

Chad Kersey and Sudhakar Yalamanchili unless otherwise noted Objectives Detailed look at the implementation of a SIMT GPU Example of the type of information propagated down the pipeline Basis for the next assignment and the default project. Dr A . Sahu. Dept of Comp Sc & . Engg. . . IIT . Guwahati. 1. Outline. Graphics System . GPU Architecture. Memory Model. Vertex Buffer, Texture buffer. GPU Programming Model. DirectX. , OpenGL, . A CUDA Approach. Gary . Resnick. Scott . Badenhorst. Department of Computer Science. University of Cape Town. 17 March, 2010. Introduction. Approach. Plan. Outcomes. Overview. Radio Astronomy. By . Ishtiaq. . Hossain. Venkata. Krishna . Nimmagadda. Application of Jacobi Iteration. Cardiac Tissue is considered as a grid of cells.. Each GPU thread takes care of voltage calculation at one cell. This calculation requires Voltage values of neighboring cells. ITK v4 . . w. inter . meeting. Feb 2. nd. 2011. Won-. Ki. . Jeong. , . Harvard University. (. wkjeong@seas.harvard.edu. ). Overview. Introduction. Current status in GPU ITK v4. GPU managers. GPU image. ITK v4 . . summer . meeting. June 28, 2011. Won-. Ki. . Jeong. Harvard University. Overview. Introduction. Current status. Examples. Future work. 2. GPU Acceleration. GPU as a fast co-processor. Massively parallel. Youngho Kim. CIS665: GPU Programming. Building a Million Particle System: Lutz Latta. UberFlow - A GPU-based Particle Engine: Peter Kipfer et al.. Real-Time Particle Systems on the GPU in Dynamic Environments: Shannon Drone. Condor Week 2012. Bob Nordlund. Grid Computing @The Hartford…. Using Condor in our production environment since 2004. Computing Environment. Two pools (Hartford, CT and Boulder, CO). Linux central managers and schedulers. Patrick Cozzi. University of Pennsylvania. CIS 565 - Fall 2014. Acknowledgements. CPU slides – Varun Sampath, NVIDIA. GPU . slides. Kayvon . Fatahalian. , CMU. Mike Houston, . NVIDIA. CPU and GPU Trends. Lecture 2: more basics. Recap. Can use GPU to solve highly parallelizable problems. Straightforward extension to C++. Separate CUDA code into .cu and .. cuh. files and compile with . nvcc. to create object files (.o files). ©Chad Kersey and Sudhakar Yalamanchili unless otherwise noted. Objectives. Detailed look at the implementation of a SIMT GPU. Example of the type of information propagated down the pipeline. Basis for the next assignment and the default project. Andy Luedke. Halo Development Team. Microsoft Game Studios. Why do Histogram Analysis?. Dynamically adjust post-processing settings based on rendered scene content. Drive tone adjustments by discovering intensity levels and adjusting . ©Chad Kersey and Sudhakar Yalamanchili unless otherwise noted. Objectives. Detailed look at the implementation of a SIMT GPU. Example of the type of information propagated down the pipeline. Basis for the next assignment and the default project. Objectives. Detailed look at the implementation of a SIMT GPU. Example of the type of information propagated down the pipeline. Basis for the next assignment and the default project. Reading. C. Kersey, “HARP Instruction Set Manual”. Add GPUs: Accelerate Science Applications. © NVIDIA 2013. Small Changes, Big Speed-up. Application Code. . GPU. C. PU. Use GPU to Parallelize. Compute-Intensive Functions. Rest of Sequential. CPU Code.