# On-The-Fly parallel decomposition of strongly connected components

@inproceedings{Bloemen2015OnTheFlyPD, title={On-The-Fly parallel decomposition of strongly connected components}, author={Vincent Bloemen}, year={2015} }

Several algorithms exist for decomposing strongly connected components (SCCs). To accommodate recent non-reversible trends in hardware, we focus on utilizing multi-core architectures. Specifically, we consider parallelizing SCC algorithms in the setting of an on-the-fly implementation (to be able to detect SCCs while constructing the graph - which is particularly useful for several verification techniques). We show that the current solutions are not capable of scaling efficiently and we propose…

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## 12 Citations

### Multi-core on-the-fly SCC decomposition

- Computer SciencePPoPP
- 2016

This paper presents a novel parallel, on-the-fly SCC algorithm that preserves the linear-time property by letting workers explore the graph randomly while carefully communicating partially completed SCCs, and develops a concurrent, iterable disjoint set structure.

### Efficient Parallel Graph Trimming by Arc-Consistency

- Computer ScienceJ. Supercomput.
- 2022

This work parallelize the AC-4-based and AC-6-based trimming algorithms to be suitable for shared-memory multi-core machines and proves the correctness and analyze time complexities with the work-depth model.

### An Efficient Implementation of the Transitive Closure Problem on Intel KNL Architecture

- Computer Science
- 2017

An optimized algorithm implementation for the transitive closure problem solution has been developed and the proposed implementation has been studied using different approaches, aimed at demonstrating advantages and disadvantages of Intel KNL architecture in solving graph-processing problems.

### Finding strongly connected components of simple digraphs based on granulation strategy

- Computer ScienceInt. J. Approx. Reason.
- 2020

### Randomized Concurrent Set Union and Generalized Wake-Up

- Computer Science, MathematicsPODC
- 2019

This work designs a randomized algorithm that performs at most O(log n) work per operation, and designs a class of "symmetric algorithms'' that captures the complexities of all the known algorithms for the disjoint set union problem, and proves that the algorithm has optimal total work complexity for this class.

### A Randomized Concurrent Algorithm for Disjoint Set Union

- Computer Science, MathematicsPODC
- 2016

This work extends a known efficient sequential algorithm for joint set union to obtain a simple and efficient concurrent wait-free algorithm running on an asynchronous parallel random access machine (APRAM).

### Variations on parallel explicit emptiness checks for generalized Büchi automata

- Computer ScienceInternational Journal on Software Tools for Technology Transfer
- 2016

These new parallel explicit emptiness checks for LTL model checking are based on a strongly connected component (SCC) enumeration and support generalized Büchi acceptance, and require no synchronization points or recomputing procedures.

### Parallel model checking of ω-automata

- Computer ScienceFM 2016
- 2016

This research focuses on designing and improving parallel graph searching algorithms for emptiness checking on various types of ω-automata and developed a scalable multi-core on-the-fly algorithm for the detection of strongly connected components (SCCs).

### Monte Carlo Tree Search With Reversibility Compression

- Computer Science2021 IEEE Conference on Games (CoG)
- 2021

MCTS with Reversibility Compression is introduced, which uses the notion of action reversibility to compress MCTS trees as they are constructed, without loss of information, which improves search by preventing the duplication of already-explored states, and increasing the attention paid to significant actions.

### Concurrent disjoint set union

- Computer ScienceDistributed Computing
- 2021

It is proved that for a class of symmetric algorithms that includes the authors' DCAS and randomized algorithms, no better step or work bound is possible, making their algorithms truly scalable.

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