Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism
نویسندگان
چکیده
CUDA is an advanced massively parallel computing platform that can provide high performance computing power at much more affordable cost. In this paper, we present a parallel graph-based substructure pattern mining algorithm using CUDA Dynamic Parallelism. The key contribution is a parallel solution to traversing the DFS (Depth First Search) code tree. Furthermore, we implement a parallel frequent subgraph mining algorithm based on the subgraph mining techniques used in gSpan and the entire subgraph mining procedure is executed on GPU to ensure high efficiency. This parallel gSpan is functionally identical to the original gSpan and experiment results show that, with the latest CUDA Dynamic Parallelism techniques, significant speedups can be achieved on benchmark datasets, particularly in traversing a DFS code tree.
منابع مشابه
gSpan: Graph-Based Substructure Pattern Mining
We investigate new approaches for frequent graph-based pattern mining in graph datasets and propose a novel algorithm called gSpan (graph-based Substructure pattern mining), which discovers frequent substructures without candidate generation. gSpan builds a new lexicographic order among graphs, and maps each graph to a unique minimum DFS code as its canonical label. Based on this lexicographic ...
متن کاملA Graph-based Interaction Pattern Discovery for Human Meetings
Mining Human Interaction flow in meetings or general representation of any interaction face to face to meetings is useful to identify the person reaction in dissimilar situation. Activities represent the natural history of the individual and mining methods help to analyze how person delivers their opinion in different ways. Meeting interactions are categorized as propose, comment, acknowledgeme...
متن کاملRGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization
This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services...
متن کاملOpen pit limit optimization using dijkstra’s algorithm
In open-pit mine planning, the design of the most profitable ultimate pit limit is a prerequisite to developing a feasible mining sequence. Currently, the design of an ultimate pit is achieved through a computer program in most mining companies. The extraction of minerals in open mining methods needs a lot of capital investment, which may take several decades. Before the extraction, the p...
متن کاملDynamic Task Parallelism with a GPU Work-Stealing Runtime System
NVIDIA’s Compute Unified Device Architecture (CUDA) and its attached C/C++ based API went a long way towards making GPUs more accessible to mainstream programming. So far, the use of GPUs for high performance computing has been primarily restricted to data parallel applications, and with good reason. The high number of computational cores and high memory bandwidth supported by the device makes ...
متن کامل