PPT-Writing Efficient CUDA Programs
Author : olivia-moreira | Published Date : 2016-12-01
Martin Burtscher Department of Computer Science HighEnd CPUs and GPUs Xeon X7550 Tesla C2050 Cores 8 superscalar 448 simple Active threads 2 per core 48 per core
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Writing Efficient CUDA Programs: Transcript
Martin Burtscher Department of Computer Science HighEnd CPUs and GPUs Xeon X7550 Tesla C2050 Cores 8 superscalar 448 simple Active threads 2 per core 48 per core Frequency 2 GHz 115 GHz. Basically a child CUDA Kernel can be called from within a parent CUDA kernel and then optionally synchronize on the completion of that child CUDA Kernel The parent CUDA kernel can consume the output produced from the child CUDA Kernel all withou t heterogeneous programming. Katia Oleinik. koleinik@bu.edu. Scientific Computing and Visualization. Boston . University. Architecture. NVIDIA Tesla M2070: . Core clock: 1.15GHz . Single instruction . 448 CUDA cores . . 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. © Dan Negrut, . 2012. UW-Madison. Dan Negrut. Simulation-Based Engineering Lab. Wisconsin Applied Computing Center. Department of Mechanical Engineering. Department of . Electrical and Computer Engineering. Martin Burtscher. Department of Computer Science. CUDA Optimization Tutorial. Martin Burtscher. burtscher@txstate.edu. http://www.cs.txstate.edu/~burtscher/. Tutorial slides. http://www.cs.txstate.edu/~burtscher/tutorials/COT5/slides.pptx. What is CUDA?. Data Parallelism. Host-Device model. Thread execution. Matrix-multiplication . GPU revised!. What is CUDA?. C. ompute . D. evice . U. nified . A. rchitecture. Programming interface to GPU. Se-Joon Chung. Background and Key Challenges. The trend in computing hardware is parallel systems.. It is challenging for programmers is to develop applications that transparently scales its parallelism to leverage the increasing number of processor cores.. Cliff Woolley NVIDIADeveloper Technology GroupGPUCPUGPGPU Revolutionizes ComputingLatency Processor Throughput processorLow Latency or High ThroughputCPUOptimized for low-latency access to cached dat 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 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 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
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