In the converging world of High Performance Computing and Big Data, moving data is becoming a critical aspect of performance and energy efficiency. In this paper we present the Advanced DAta Movement Analysis Toolkit (ADAMANT), a set of tools to capture and analyze data movement within an application, and to aid in understanding performance and energy efficiency in current and future systems. ADAMANT identifies all the data objects allocated by an application and uses instrumentation modules to monitor relevant events (e.g. cache misses). Finally, ADAMANT produces a per-object performance profile.

In this paper we demonstrate the use of ADAMANT in analyzing three applications, BT, BFS, and Velvet, and evaluate the impact of different memory technology. With the information produced by ADAMANT we were able to model and compare different memory configurations and object placement solutions. In BFS we devised a placement which outperforms caching, while in the other two cases we were able to point out which data objects may be problematic for the configurations explored, and would require refactoring to improve performance.