  Random graphs (or networks) have gained a significant increase of interest
due to its popularity in modeling and simulating many complex real-world
systems. Degree sequence is one of the most important aspects of these systems.
Random graphs with a given degree sequence can capture many characteristics
like dependent edges and non-binomial degree distribution that are absent in
many classical random graph models such as the Erd\H{o}s-R\'{e}nyi graph model.
In addition, they have important applications in the uniform sampling of random
graphs, counting the number of graphs having the same degree sequence, as well
as in string theory, random matrix theory, and matching theory. In this paper,
we present an OpenMP-based shared-memory parallel algorithm for generating a
random graph with a prescribed degree sequence, which achieves a speedup of
20.5 with 32 cores. One of the steps in our parallel algorithm requires
checking the Erd\H{o}s-Gallai characterization, i.e., whether there exists a
graph obeying the given degree sequence, in parallel. This paper presents the
first non-trivial parallel algorithm for checking the Erd\H{o}s-Gallai
characterization, which achieves a speedup of 23 using 32 cores.
