PPT-Finding Optimum Abstractions in Parametric Dataflow Analysi

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. All Programmable Abstractions push beyond traditional RTL design methodologies to automate all aspects of system development and algorithm deployment into all programmable FPGAs SoC and 3D ICs Xilinx and its Alliance members are working together to (and the Naiad system). 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. Yuan Lin. 1. , Yoonseo Choi. 1. , Scott Mahlke. 1. , Trevor Mudge. 1. , . Chaitali. Chakrabarti. 2. 1. Advanced Computer Architecture Lab, University of Michigan at Ann Arbor. 2. Department of Electrical Engineering, Arizona State University. Dictionary ADT. : Arrays, Lists and . Trees. Kate Deibel. Summer 2012. June 27, 2012. CSE 332 Data Abstractions, Summer 2012. 1. Where We Are. Studying the absolutely essential ADTs of computer science and classic data structures for implementing them. Master’s . Thesis Defense. Sindhu Gunasekar. Dept. of ECE, Auburn University. Advisory Committee: . Dr.. . Vishwani. D. . Agrawal (chair),. . Dr.. . Victor P. Nelson, . Dr. . Adit. . D. Singh. 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. Disjoint Set Union-Find . and . Minimum Spanning Trees. Kate Deibel. Summer 2012. August 13, 2012. CSE 332 Data Abstractions, Summer 2012. 1. Making Connections. You have a set of nodes (numbered 1-9) on a network. . Finding Optimum Abstractions in Parametric Dataflow Analysis Xin Zhang Georgia Tech Mayur Naik Georgia Tech Hongseok Yang University of Oxford A Key Challenge for Static Analysis Precision Scalability CSE 332 Data Abstractions: A Heterozygous Forest of AVL, Splay, and B Trees Kate Deibel Summer 2012 July 2, 2012 CSE 332 Data Abstractions, Summer 2012 1 From last time… Binary search trees can give us great performance due to providing a structured binary search. Dictionary ADT. : Arrays, Lists and . Trees. Kate Deibel. Summer 2012. June 27, 2012. CSE 332 Data Abstractions, Summer 2012. 1. Where We Are. Studying the absolutely essential ADTs of computer science and classic data structures for implementing them. 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.