Evaluation of the Context-Free Path Querying Algorithm Based on Matrix Multiplication

One Algorithm to Evaluate Them All: Unified Linear Algebra Based Approach to Evaluate Both Regular and Context-Free Path Queries

“…Also, it is necessary to evaluate GPGPU-based implementation. Evaluation of Azimov's algorithm shows that it is possible to improve performance by using GPGPU because operations of linear algebra can be efficiently implemented on GPGPU (Mishin et al, 2019;Terekhov et al, 2020). Moreover, for practical reasons, it is interesting to provide a multi-GPU version of the algorithm and to utilize unified memory, which is suitable for linear algebra based processing of out-of-GPGPU-memory data and traversing on large graphs (Chien et al, 2019;Gera et al, 2020).…”

“…Azimov and Grigorev (2018) showed how to reduce CFPQ to matrix multiplication. Later, it was shown by Mishin et al (2019) and Terekhov et al (2020) that by using the appropriate libraries for linear algebra for Azimov's algorithm implementation one can create a practical solution for CFPQ. However, Azimov's algorithm requires transforming of the input grammar to Chomsky Normal Form.…”