PPT-dMazeRunner : Executing Perfectly Nested Loops on Dataflow Accelerators

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. Chapter. 4. Repeated Tasks are for Computers. Think back to any very difficult quantitative problem that you had to solve in some science class. How long did it take?. How many times did you solve it?. Efficient Pipelining of Nested Loops:Unroll-and-SquashDarin S. PetkovSubmitted to the Department of Electrical Engineering and Computer Scienceon December 20, 2000, in partial fulfillment ofthe requir via Dataflow Flattening. Bertrand Anckaert. Ghent University/. Boston . Consulting Group. The Third International Conference on Emerging Security. Information, Systems and Technologies. . SECURWARE 2009. Processing Systems Using Markov Decision. Processes. 1. Georgia . Institute of . Technology, USA. 2. University . of Maryland. , . USA. 3. Tampere . University of Technology, Finland. With contributions from: . Each time the outer loop is repeated, the inner loop starts from the beginning.. 1. WHAT ARE NESTED LOOPS. Dr. Soha S. Zaghloul . 2. . Analysis:. How to calculate the total scores of a single student?. Building Relational Web-Applications. Avraham . Leff. James T. . Rayfield. IBM T.J. Watson Research Center. {. avraham,jtray. }@us.ibm.com. OOPSLA’07. Presented by David Gonzalez. Key Insights:. Derek G. Murray. Michael Isard. Frank McSherry. Paul Barham. Rebecca Isaacs. Martín Abadi. Microsoft Research. 1. Batch processing. Stream processing. Graph processing. Timely dataflow. In. ⋈. #x. 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. 2. A Base-Language. To serve as an intermediate-level language for high-level languages. To serve as a machine language for parallel machines. . - J.B. Dennis. ~ Data Flow Graphs ~. CPEG421-2001-F-Topic-3-II. ITS Research Computing. Mark Reed . Objectives. Learn why computing with accelerators is important. Understand accelerator hardware. Learn what types of problems are suitable for accelerators. Survey the programming models available. One if statement inside another one. An if statement inside a loop. A loop inside an if statement. Control structures can be nested inside each other to any degree you need . Nested loops. The general principle of nesting loops is that the inner loop must completely finish its execution before the next iteration of the outer loop starts. Shamsa. Hassan . Alhassouni. For -G7. . What we will Learn today?. Understand Random concept. Understand for Loops. Understand . Nested Loops. Random. Random. Function. Description. Input(). Print (). 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 ]. 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 .