PPT-GPU Performance Optimisation

Alan Gray EPCC The University of Edinburgh Hardware Memory Memory NVIDIA accelerated system 2 GPU performance inhibitors Copying data tofrom device Device under utilisation GPU memory latency. . 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. Chris Rossbach, Microsoft Research. Jon Currey, Microsoft Research. Emmett . Witchel. , University of Texas at Austin. HotOS. 2011. Lots of GPUs. Must they be so hard to use?. We need dataflow…. GPU Haiku . 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. . Dianzi. . Liu, . V. assili. . V. . Toropov. , . Osvaldo M. . Querin. University . of Leeds. . Content. Introduction. Topology Optimisation. Parametric Optimisation. 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 . . 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. JISC . Improved Sustainability Across Estates Through The Use of ICT. Continuous Optimisation . – . an Imperial College estates. initiative reducing the carbon consumption of plant & services, and how ICT infrastructure underpins it’s delivery. Shahin Sanaye Hajari . Institute For Research in Fundamental Sciences (IPM), Tehran, Iran. CERN, Geneva, Switzerland. Contents. The physics behind the optimisation. Description of the original model . Voltage optimisation is a generic term given to the managed reduction of voltages received from a supplier down to a value that more closely meets the designed rating for all your . electrical appliances.. Supercomputing. The Next wave of HPC. Presented by Shel Waggener. HP Materials from Marc Hamilton. June. , . 2011. © Copyright 2011 Hewlett-Packard Development Company, L.P.    . GPUs – changing the Economics of Supercomputing. Alex Wade. CAP6938 Final Project. Introduction. GPU based implementation of . A Computational Approach to Edge Detection. by John Canny. Paper presents an accurate, localized edge detection method. Purpose. Scheduling Techniques for GPU Architectures with Processing-In-Memory Capabilities Ashutosh Pattnaik Xulong Tang, Adwait Jog, Onur Kay ı ran, Asit Mishra, Mahmut Kandemir , Onur Mutlu Mark Worrall. Radiation Physics, Ninewells Hospital. Scottish Medical Physics Network (MPNET). Chair of the IPEM paediatric optimisation working party. Overview. Assumed knowledge:. Who are MPNET?. What is optimisation?. Recording the measures on Badgernet. | National Patient Safety Improvement Programmes. 1. Areas of Optimisation 1-3. Place of birth:. . All babies delivered should be delivered in appropriate care setting for gestation (in a care setting with an NICU for singletons <27+0 weeks or <800gms, or all multiples <28+0 weeks.