[8-16]From Clarity to Efficiency for Distributed Algorithms
报告题目：From Clarity to Efficiency for Distributed Algorithms
报告人：Yanhong Annie Liu, Stony Brook University
This talk describes a very high-level language for clear description of distributed algorithms and optimizations necessary for generating efficient implementations. The language supports high-level control flows where complex synchronization conditions can be expressed using high-level queries, especially logic quantifications, over message history sequences. Unfortunately, the programs would be extremely inefficient, including consuming unbounded memory, if executed straightforwardly.
We present new optimizations that automatically transform complex synchronization conditions into incremental updates of necessary auxiliary values as messages are sent and received. The core of the optimizations is the first general method for efficient implementation of logic quantifications. We have developed an operational semantics of the language, implemented a prototype of the compiler and the optimizations, and successfully used the language and implementation on a variety of important distributed algorithms.
(Joint work with Scott D. Stoller, Bo Lin, and Jon Brandvein For more information see http://distalgo.cs.stonybrook.edu/)
Annie Liu is Professor of Computer Science at Stony Brook University. Her primary research is in languages and algorithms, especially on systematic methods for design and optimization. The methods are centered around incrementalization---the discrete counterpart of differentiation in calculus. Besides research and service, she also enjoys teaching. She has taught in a wide range of Computer Science areas, and presented over 100 conference and invited talks worldwide. She received her BS from Peking University, MEng from Tsinghua University, and PhD from Cornell University, all in Computer Science.
Annie Liu's Design and Analysis Research Laboratory has projects in modeling and specification, analysis and verification, design and optimization, code generation, and testing. These projects are for optimizing compilers, interactive environments, real-time and embedded systems, database systems, semantic Web, distributed systems, big data analysis, security, and more. Her awards include a State University of New York Chancellor's Award for Excellence in Scholarship and Creative Activities.