  Motivation: Working with a large number of genomes simultaneously is of great
interest in genetic population and comparative genomics research. Bubbles
discovery in multi-genomes coloured de bruijn graph for de novo genome assembly
is a problem that can be translated to cycles enumeration in graph theory.
Cycle enumerations algorithms in big and complex de Bruijn graphs are time
consuming. Specialised fast algorithms for efficient bubble search are needed
for coloured de bruijn graph variant calling applications. In coloured de
Bruijn graphs, bubble paths coverages are used in downstream variants calling
analysis. Results: In this paper, we introduce a fast parallel graph search for
different K-mer cycle sizes. Coloured path coverages are used for SNP
prediction. The graph search method uses a combined multi-node and multi-core
design to speeds up cycles enumeration. The search algorithm uses an index
extracted from the raw assembly of a coloured de Bruijn graph stored in a hash
table. The index is distributed across different CPU-cores, in a shared memory
HPC compute node, to build undirected subgraphs then search independently and
simultaneously specific cycle sizes. This same index can also be split between
several HPC compute nodes to take advantage of as many CPU-cores available to
the user. The local neighbourhood parallel search approach reduces the graph's
complexity and facilitate cycles search of a multi-colour de Bruijn graph. The
search algorithm is incorporated into $\Pi$-cyc application and tested on a
number of Schizosaccharomyces Pombe genomes. Availability: $\Pi$-cyc is an
open-source software available at www.github.com/2kplus2P
