PPT-GPU Programming

Author : marina-yarberry | Published Date : 2016-12-03

using BU Shared Computing Cluster Scientific Computing and Visualization Boston University GPU Programming GPU graphics processing unit Originally designed as

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "GPU Programming" is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

GPU Programming: Transcript

using BU Shared Computing Cluster Scientific Computing and Visualization Boston University GPU Programming GPU graphics processing unit Originally designed as a graphics processor Nvidias. . Acknowledgement: the lecture materials are based on the materials in NVIDIA teaching center CUDA course materials, including materials from Wisconsin (. Negrut. ), North Carolina Charlotte (. Wikinson. Alan . Gray. EPCC . The University of Edinburgh. Outline. Why do we want/need accelerators such as GPUs?. Architectural reasons for accelerator performance advantages . Latest accelerator Products. NVIDIA and AMD GPUs. 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. Rajat Phull, . Srihari. Cadambi, Nishkam Ravi and Srimat Chakradhar. NEC Laboratories America. Princeton, New Jersey, USA.. www.nec-labs.com. OpenFOAM Overview. OpenFOAM stands for:. ‘. O. pen . F. 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. 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 . CS 179: GPU Programming Lecture 7 Week 3 Goals: Advanced GPU- accelerable algorithms CUDA libraries and tools This Lecture GPU- accelerable algorithms: Reduction Prefix sum Stream compaction Sorting (quicksort) Lecture 7. Last Week. Memory optimizations using different GPU caches. Atomic operations. Synchronization with __. syncthreads. (). Week 3. Advanced GPU-accelerable algorithms. “Reductions” to parallelize problems that don’t seem intuitively parallelizable. Scientific Computing and Visualization. Boston . University. GPU Programming. GPU – graphics processing unit. Originally designed as a graphics processor. Nvidia's. GeForce 256 (1999) – first GPU. Research Computing Services. Boston . University. GPU Programming. Access to the SCC. Login: . tuta#. Password: . VizTut#. GPU Programming. Access to the SCC GPU nodes. # copy tutorial materials: . Patrick Cozzi. University of Pennsylvania. CIS 565 - Fall 2013. Lectures. Monday and Wednesday. 6-7:30pm. Towne . 307. Fall. and . Spring. 2012 lectures were recorded. Attendance is required for guest lectures. The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand

Download Document

Here is the link to download the presentation.
"GPU Programming"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.