PPT-CPU-GPU Collaboration for Output Quality Monitoring

Mehrzad Samadi and Scott Mahlke University of Michigan March 2014 Compilers creating custom processors University of Michigan Electrical Engineering and Computer Science Output Quality Monitoring. Avg Access Time 2 Tokens Number of Controllers Average Access Time clock cyles brPage 16br Number of Tokens vs Avg Access Time 9 Controllers Number of Tokens Average Access Time clock cycles brPage 17br brPage 18br . 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. 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, . 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. 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. using BU Shared Computing Cluster. Scientific Computing and Visualization. Boston . University. GPU Programming. GPU – graphics processing unit. Originally designed as a graphics processor. Nvidia's. Betkaoui, B.; Thomas, D.B.; Luk, W., "Comparing performance and energy efficiency of FPGAs and GPUs for high productivity computing," . Field-Programmable Technology (FPT), 2010 International Conference on. 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 . Evangelia Sitaridi, . Thesis Defense. Columbia University . GPUs for Social Media Analytics. 2. Search terms: . Match . regexp. : “/\B#\w*[a-. zA. -Z] \w*/ . . debate. Filter location. More GPU Data Analytics Use-Cases. 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. Fyodor . Serzhenko. , . Fastvideo. , . Dubna. , Russia. Victor . Podlozhnyuk. , NVIDIA, Santa Clara, CA. © . Fastvideo. , 2011. Key Points. We implemented the fastest JPEG codec. Many applications using JPEG can benefit from our codec. A Tale of Two Cities: GPU Computing and Machine Learning Dr. Xiaowen Chu Department of Computer Science, Hong Kong Baptist University Outline 2 Some Stories of “Two Cities” Evolution of CPUs/ Paris, 2016-01-26. 2. Contents. Introduction . Brief review of ongoing IAC Adaptive Optics projects. Summary of control technologies used . Technologies comparison . C. onclusions. 3. Contents. Introduction. 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.