Seung-Hoe Ku

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Efficient handling of large volumes of data is a necessity for exascale scientific applications and database systems. To address the growing imbalance between the amount of available storage and the amount of data being produced by high speed (FLOPS) processors on the system, data must be compressed to reduce the total amount of data placed on the file(More)
Exploding dataset sizes from extreme-scale scientific simulations necessitates efficient data management and reduction schemes to mitigate I/O costs. With the discrepancy between I/O bandwidth and computational power, scientists are forced to capture data infrequently, thereby making data collection an inherently lossy process. Although data compression can(More)
Efficient analytics of scientific data from extreme-scale simulations is quickly becoming a top-notch priority. The increasing simulation output data sizes demand for a paradigm shift in how analytics is conducted. In this paper, we argue that <i>query-driven analytics over compressed---rather than original, full-size---data</i> is a promising strategy in(More)
Massively parallel computations consist of a mixture of computation, communication, and I/O. Of these three components, implementing an effective parallel I/O solution has often been overlooked by application scientists and has typically been added to large scale simulations only when existing serial techniques have failed. As scientists’ teams scaled their(More)
The growing gap between the massive amounts of data generated by petascale scientific simulation codes and the capability of system hardware and software to effectively analyze this data necessitates data reduction. Yet, the increasing data complexity challenges most, if not all, of the existing data compression methods. In fact, loss less compression(More)
The controlled production of thermo-nuclear fusion energy is critical for providing an alternative, environmentally friendly, and renewable energy source on our planet. The technical challenge is to stabilize the dynamic turbulent flow of hot plasma in magnetic fields in a fusion energy reactor. More specifically, the issue is how to control fusion plasma(More)
The National Energy Research Scientific Computing Center (NERSC) was originally launched as a computing center for the exclusive support of magnetic confinement fusion research in the US. There is, thus, a long history of computational advances and successes that ties fusion scientists with NERSC and its staff. One example of the numerous computational(More)
XGC1 and M3D-C 1 are two fusion plasma simulation codes being developed at Princeton Plasma Physics Laboratory. XGC1 uses the particle-in-cell method to simulate gyrokinetic neoclassical physics and turbulence (Chang et al. Phys Plasmas 16(5):056108, 2009; Ku et al. Nucl Fusion 49:115021, 2009; Admas et al. J Phys 180(1):012036, 2009). M3D- $$C^1$$ C 1(More)