Name
Abstract | ||
|---|---|---|
Modern Datalog engines are employed in industrial applications such as graph databases, networks, and static program analysis. To cope with the vast amount of data in these applications, Datalog engines must employ specialized parallel data structures. In this paper, we introduce the Brie, a specialized data structure for high-density relations storing large data volumes. It effectively compresses dense data in a lock-free fashion and obtains up to 15× higher performance in parallel insertion benchmarks compared to state-of-the-art alternatives. Furthermore, when integrated into a Datalog engine running an industrial points-to analysis, runtime improves by a factor of 4× with a compression ratio of up to 3.6× are obtained.
|
Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3303084.3309490 | PPoPP '19: 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Washington
DC
USA
February, 2019 |
Keywords | Field | DocType |
Datalog, Data Structures, Concurrency | Static program analysis,Data structure,Graph database,Concurrency,Computer science,Parallel computing,Compression ratio,Datalog,Trie | Conference |
ISBN | Citations | PageRank |
978-1-4503-6290-0 | 2 | 0.36 |
References | Authors | |
28 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Herbert Jordan | 1 | 70 | 11.83 |
| Pavle Subotic | 2 | 47 | 5.93 |
| David Zhao | 3 | 185 | 14.67 |
| Bernhard Scholz | 4 | 104 | 10.59 |