  We present a graph processing benchmark suite with the goal of helping to
standardize graph processing evaluations. Fewer differences between graph
processing evaluations will make it easier to compare different research
efforts and quantify improvements. The benchmark not only specifies graph
kernels, input graphs, and evaluation methodologies, but it also provides
optimized baseline implementations. These baseline implementations are
representative of state-of-the-art performance, and thus new contributions
should outperform them to demonstrate an improvement.
  The input graphs are sized appropriately for shared memory platforms, but any
implementation on any platform that conforms to the benchmark's specifications
could be compared. This benchmark suite can be used in a variety of settings.
Graph framework developers can demonstrate the generality of their programming
model by implementing all of the benchmark's kernels and delivering competitive
performance on all of the benchmark's graphs. Algorithm designers can use the
input graphs and the baseline implementations to demonstrate their
contribution. Platform designers and performance analysts can use the suite as
a workload representative of graph processing.
