SC Conference - Activity Details

Tom Peterka  (Argonne National Laboratory)

David Goodell  (Argonne National Laboratory)

Robert Ross  (Argonne National Laboratory)

Han-Wei Shen  (Ohio State University)

Rajeev Thakur  (Argonne National Laboratory)

Large-Scale Applications

Tuesday,  11:00AM - 11:30AM

Room PB255

Collective communication operations can dominate the cost of large scale parallel algorithms. Image compositing in parallel scientific visualization is one such reduction operation where this is the case. We present a new algorithm that in many cases performs better than existing compositing algorithms. It can do this via a set of configurable parameters, the radices, that determine the number of communication partners in each message round. The algorithm embodies and unifies binary swap and direct-send, two of the best-known compositing methods, and enables numerous other configurations via appropriate choices of radices. While general-purpose and not tied to a particular computing architecture or network topology, the selection of radix values allows the algorithm to to take advantage of new supercomputer interconnect features such as multi-porting. We show scalability across image size and system size, including both powers of two and non-powers of two process counts.

The full paper can be found in the ACM Digital Library and IEEE Computer Society