PPT-Lock-free Cuckoo Hashing

Nhan Nguyen amp Philippas Tsigas ICDCS 2014 Distributed Computing and Systems Chalmers University of Technology Gothenburg Sweden Our contributions a concurrent hash table Nhan D Nguyen. The analysis uses only very basic and intuitively understandable concepts of probability theory and is meant to be accessible even for undergraduates taking their 64257rst algorithms course 1 Introduction dictionary is a data structure for storing a Up to this point the greatest drawback of cuckoo hashing appears to be that there is a polynomially small but practically signicant probability that a failure occurs during the insertion of an item requiring an expensive rehashing of all items in th Constant Worst-Case Operations with a Succinct Representation. Yuriy. . Arbitman. . Moni. Naor Gil . Segev. Dynamic Dictionary. Data structure representing a set of words . S. From a Universe . Practically Better Than Bloom. Bin Fan . (CMU/Google). David Andersen (CMU). Michael . Kaminsky. (Intel Labs). Michael . Mitzenmacher. (Harvard). 1. What is Bloom Filter? A Compact Data Structure . Guest lecture: Cuckoo Hashing. Shannon Larson. March 11, 2011. Learning Goals. Describe the cuckoo hashing principle. Analyze the space and time complexity of cuckoo hashing. Apply the insert and lookup algorithms in a cuckoo hash table. On the Interplay of Hardware Transactional Memory and Lock-free Indexing. Justin . Levandoski. Microsoft Research Redmond. Ryan Stutsman. Microsoft Research Redmond. Darko. . Makreshanski. Department of Computer Science. Uri . Zwick. January 2014. Hashing. 2. Dictionaries. D .  . Dictionary() . – Create an empty dictionary. Insert(. D. ,. x. ) . – Insert item . x. into . D. Find(. D. ,. k. ) . – Find an item with key . H. ashing: . Scalable and Flexible Hashing on GPUs. Farzad Khorasani, Mehmet E. . Belviranli. , Rajiv Gupta, . Laxmi. N. . Bhuyan. University of California Riverside. What Stadium hashing addresses. Haim Kaplan . and. Uri . Zwick. January 2013. Hashing. 2. Dictionaries. D .  . Dictionary() . – Create an empty dictionary. Insert(. D. ,. x. ) . – Insert item . x. into . D. Find(. D. ,. k. Xiaozhou Li . (. Princeton. ). David G. Andersen (CMU). Michael Kaminsky (Intel Labs). Michael J. Freedman (Princeton). How to build a fast concurrent hash table. a. lgorithm and data structure engineering. On the Interplay of Hardware Transactional Memory and Lock-free Indexing. Justin . Levandoski. Microsoft Research Redmond. Ryan Stutsman. Microsoft Research Redmond. Darko. . Makreshanski. Department of Computer Science. H. ashing: . Scalable and Flexible Hashing on GPUs. Farzad Khorasani, Mehmet E. . Belviranli. , Rajiv Gupta, . Laxmi. N. . Bhuyan. University of California Riverside. What Stadium hashing addresses. Plan. I spent the last decade advising on numerous cases where hash tables/functions were used. A few observations on . What data structures I’ve seen implemented and where. What do developers think, were they need help. http://www.cse.iitk.ac.in/~mainakc/lockfree.html. Prabhakar. . Misra. and . Mainak. Chaudhuri. Indian Institute of Technology, Kanpur. Sketch. Talk in one slide. Result highlights. Related work. Lock-free data structures.