Compressed In-memory Graphs for Accelerating GPU-based Analytics.
Noushin AzamiMartin BurtscherPublished in: IA3@SC (2022)
Keyphrases
- limited memory
- graph matching
- learning analytics
- memory requirements
- data structure
- memory usage
- compressed data
- graph theory
- big data
- graph representation
- times faster
- graph theoretic
- data management
- memory space
- collision detection
- graph partitioning
- graph mining
- data compression
- graph structure
- parallel processing
- main memory
- directed graph
- business intelligence
- cloud computing
- database systems
- case study
- graphics processors
- memory size
- weighted graph
- graph search
- predictive modeling
- random graphs
- graph clustering
- random access
- spanning tree
- graph model
- real time
- neural network