PPT-GPU programming Dr. Bernhard

K ainz Overview About myself Motivation GPU hardware and system architecture GPU programming languages GPU programming paradigms Pitfalls and best practice Reduction and tiling examples Stateoftheart . . 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. ITS Research Computing. Lani. Clough, Mark Reed. markreed@unc.edu. . Objectives. Introductory. level MATLAB course for people who want to learn . parallel and GPU computing . in MATLAB.. Help participants . CS 179: GPU Programming 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 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. 5. th. QTAWG meeting, January 17, 2014, B. Auchmann. QTAWG Joint Paper. Author list. : B. . Auchmann, T. Baer, M. . Bednarek. , . G. . Bellodi. , C. . Bracco. , R. Bruce, F. . Cerutti. , V. . Chetvertkova. 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. 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 Impact on . families. . In . special. . regard. . to. . medical. . issues. By. Bernhard Schmid. Capacity. Law - Impact on . Families. (1) . Parents. . often. . remain. . the. . most. . important.