Graph algorithms are used in many big data and analytics workloads. Oracle's SPARC T7 processor based systems provide better performance than x86 systems with the Intel Xeon E7 v2 family of processors.
The SPARC T7-4 server was able to deliver 3.1x better performance than a four chip x86 server running a breadth-first search (BFS) on a large graph.
The problem is identified by "Scale" and the approximate amount of memory used. Results are listed as edge traversals in billions (ETB) per second (bigger is better). The SPARC M7 processor results were run as part of this benchmark effort. The x86 results were taken from a previous benchmark effort.
|Breadth-First Search (BFS)|
|SPARC T7-4||x86 (4xE7 v2)|
Systems Under Test:
Graphs are a core part of many analytics workloads. They are very data intensive and stress computers. This benchmark does a breadth-first search on a randomly generated graph. It reports the number of graph edges traversed (in billions) per second (ETB/sec). To generate the graph, the data generator from the graph500 benchmark was used.
A description of what breadth-first search is taken from Introduction to Algorithms, page 594:
Given a graph G = (V, E) and a distinguished source vertex s, breadth-first search systematically explores the edges of G to "discover" every vertex that is reachable from s. It computes the distance (smallest number of edges) from s to each reachable vertex. It also produces a "breadth-first tree" with root s that contains all reachable vertices. For any vertex reachable from s, the simple path in the breadth-first tree from s to corresponds to a "shortest path" from s to in G, that is, a path containing the smallest number of edges. The algorithm works on both directed and undirected graphs.
Cormen, Thomas H., Leiserson, Charles E., Rivest, Ronald L., Stein, Clifford (2009) . Introduction to Algorithms (3rd ed.). MIT Press and McGraw-Hill. ISBN 0-262-03384-4.
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