PPT-1 Lecture: Eyeriss Dataflow

Topics Eyeriss architecture and dataflow digital CNN accelerator We had previously seen basic ANNs that used tilingbuffersNFUs DianNao multiple chips to distribute the work and eliminate memory accesses . via Dataflow Flattening. Bertrand Anckaert. Ghent University/. Boston . Consulting Group. The Third International Conference on Emerging Security. Information, Systems and Technologies. . SECURWARE 2009. Xin Zhang. Georgia Tech. Mayur. . Naik. Georgia Tech. Hongseok. Yang. University of Oxford. A Key Challenge for Static Analysis. Precision. Scalability. Our setting. Query q. Program p. Static Analysis S. Introduction and informal review process 2009-2014. Eva Goossens. Head of Industrial Pollution Group. Air and . Climate. Change Programme. Eionet. NRC workshop on Industrial . Pollution. Copenhagen 4. Peter Alvaro. , . Neil Conway, Joseph M. . Hellerstein. David Maier. UC Berkeley Portland State. D. istributed systems are hard. Asynchrony. Partial Failure. A. synchrony isn’t that hard . Dataflow Architectures. Supervisor: Anthony Steed. Sebastian . Friston. EngD. VEIV. Why Latency?. The time between a user’s action, and the computer’s response to this . action. Must be low to maintain the sense that the world is responding to the user – key to enabling presence. Gradisar. . (531/2010). . Golden . Section Search. . Golden Section Method. Introduction. -Golden Section Method uses constant. Interval of . reduciton. . -Which can be seen in different aspects of proportion from geometry to architecture.. Frank McSherry. , Derek G. Murray,. Rebecca Isaacs, Michael Isard. Microsoft Research, Silicon Valley. Data-parallel dataflow. 1. 2. 3. 4. 5. 1. 4. 2. 3. 6. 6. 5. A. B. C. D. E. k1:. k2:. k3:. Data-parallel dataflow. . for . Petascale. Computing. Justin . M Wozniak. Argonne National Laboratory and University of Chicago. http://swift-lang.org/Swift-T . wozniak@mcs.anl.gov. scientific workflows. Claus Brabrand. IT University of Copenhagen. Universidade Federal de Pernambuco. [ brabrand@itu.dk ]. Márcio Ribeiro. Universidade Federal de Alagoas. Universidade Federal de Pernambuco. [ mmr3@cin.ufpe.br ]. Apache NiFi Presented by: Joe Witt Apache NiFi PPMC Member Apache NiFi’s job: Enterprise Dataflow Management 1 Automate the flow of data from any source …to systems which extract meaning and Ministry (MoHE) Sultanate of Oman FAQ s 1. What is the DataFlow Group? The DataFlow Group is a leading global provider of specialized Primary Source Verification (PSV) solutions, and background scre To perform optimizations like constant propagation or dead code elimination, we must. Analyze program to find opportunities for performing optimizations safely. Transform program. Analysis is called . Shail Dave. 1. , . Youngbin. Kim. 2. , . Sasikanth. Avancha. 3,. Kyoungwoo. Lee. 2. , Aviral Shrivastava. 1. [1] Compiler Microarchitecture Lab, Arizona State University. [2] Department of Computer Science, Yonsei University. SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks. 9 authors @ NVIDIA, MIT, Berkeley, Stanford. ISCA . 2017. Convolution operation. Reuse. Memory: size vs. access energy. Dataflow decides reuse.