TY - JOUR
T1 - Preparing for in situ processing on upcoming leading-edge supercomputers
AU - Kress, James
AU - Churchill, Randy Michael
AU - Klasky, Scott
AU - Kim, Mark
AU - Childs, Hank
AU - Pugmire, David
N1 - Publisher Copyright:
© The Authors 2016.
PY - 2016
Y1 - 2016
N2 - High performance computing applications are producing increasingly large amounts of data and placing enormous stress on current capabilities for traditional post-hoc visualization techniques. Because of the growing compute and I/O imbalance, data reductions, including in situ visualization, are required. These reduced data are used for analysis and visualization in a variety of different ways. Many of the visualization and analysis requirements are known a priori, but when they are not, scientists are dependent on the reduced data to accurately represent the simulation in post hoc analysis. The contributions of this paper is a description of the directions we are pursuing to assist a large scale fusion simulation code succeed on the next generation of supercomputers. These directions include the role of in situ processing for performing data reductions, as well as the tradeoffs between data size and data integrity within the context of complex operations in a typical scientific workflow.
AB - High performance computing applications are producing increasingly large amounts of data and placing enormous stress on current capabilities for traditional post-hoc visualization techniques. Because of the growing compute and I/O imbalance, data reductions, including in situ visualization, are required. These reduced data are used for analysis and visualization in a variety of different ways. Many of the visualization and analysis requirements are known a priori, but when they are not, scientists are dependent on the reduced data to accurately represent the simulation in post hoc analysis. The contributions of this paper is a description of the directions we are pursuing to assist a large scale fusion simulation code succeed on the next generation of supercomputers. These directions include the role of in situ processing for performing data reductions, as well as the tradeoffs between data size and data integrity within the context of complex operations in a typical scientific workflow.
KW - Data reductions
KW - Data staging methods
KW - High performance computing
KW - In situ methods
KW - Scientific visualization
UR - http://www.scopus.com/inward/record.url?scp=85027246207&partnerID=8YFLogxK
U2 - 10.14529/jsfi160404
DO - 10.14529/jsfi160404
M3 - Article
AN - SCOPUS:85027246207
SN - 2409-6008
VL - 3
SP - 49
EP - 65
JO - Supercomputing Frontiers and Innovations
JF - Supercomputing Frontiers and Innovations
IS - 4
ER -