SCIPHI - Score-P and Cube Extensions for Intel® Xeon Phi™

  • Christian Feld, Jülich Supercomputing Centre

The KNL processors offers unique features concerning memory hierarchy and vectorization capabilities. To improve tool support within these two areas, we present extensions to the Score-P measurement system and the Cube report explorer.

KNL introduced a new memory architecture, utilizing MCDRAM and DDR. To help the user in the decision where to place data structures, we record a MCDRAM candidate metric. In addition we track all MCDRAM allocations through the hbwmalloc API, providing memory metrics like leaked memory or the high-watermark on a per-region basis. For time-line analysis per-process memory statistics are recorded via numastat.

KNL's large vector processing unit needs to be utilized and utilized effectively. The metrics compute-to-data access ratio and VPU intensity are introduced to identify vectorization candidates on a per-region basis.

Taking the hardware structure into account, the distribution of the KNL-specific metrics is visualized in the Cube report explorer.

  • Room:Posters will be on display throughout the entire conference in the main hallway. Attendees can meet the poster authors Saturday Nov 11th, 5:30p.m. - 7:30p.m.
  • Location:South Convention Lobby
  • Session Type:Poster Session
  • Session Executive Summary:To improve KNL-specific tool support within the areas vectorization and memory, we present extensions to the highly scalable Score-P measurement system and the Cube report explorer.
Christian Feld
Jülich Supercomputing Centre