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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)
SUMMARY 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(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(More)
By exploiting MPI, OpenMP, and CUDA Fortran, the FOR-TRAN fusion simulation code XGC1 achieves excellent weak scalability out to at least 18,624 GPU-CPU XK7 nodes, enabling science studies that have not been possible before. XGC1 is a full-f gyrokinetic particle-in-cell code designed specifically for simulating edge plasmas in tokamaks. XGC1 was recently(More)
The controlled production of thermonuclear 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 coarse-graining procedure ͑CGP͒ ͓Y. is implemented in the GEM code for electrons. While CGP introduces numerical dissipation in the particle-in-cell simulations, it is shown that CGP preserves physical dissipation effects such as the electron-ion collisional effects on the particle flux in ion-temperature-gradient driven turbulence. Kinetic simulation(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)