Theme: Fast and Big Data, Fast and Big Computation
Challenge: Exposing and Expressing Massive Parallelism in Scientific Problems to Exploit Heterogeneous Parallelism in High Performance Computers
Scientific computing is about solving application problems, and there are two major focuses: extreme scaling of computation and deriving knowledge from massive amounts of data. These two aspects are closely coupled: large computations consume and generate massive amounts of data, and processing of big data requires large amounts of computational power, which increasingly depends on parallel computation.
The PASC18 theme Fast and Big Data, Fast and Big Computation emphasizes our vision of the close coupling of data and computation. Exposing and expressing massive and irregular parallelism in computational problems are key challenges for exploiting the massive and heterogeneous parallelism available in current, and expected in future, HPC systems, as well as to find new ways of generating scientific insight from data and models. Through its rich and interactive program, PASC18 aims to highlight the computational approaches that computational scientists, computer scientists, and practitioners employ today and will employ over the next decades to address these challenges.
The PASC Conference provides three days of stimulating and thought-provoking technical sessions, including keynote presentations, minisymposia, peer-reviewed papers, panels and poster sessions. The conference is co-sponsored by ACM SIGHPC, and full papers are published in the ACM Digital Library. The program will provide an exhibition space.
PASC18 seeks to engage participants from academia, research labs and industry to address important issues in HPC and computational science. PASC18 is inviting researchers from diverse scientific backgrounds to promote interdisciplinary collaboration and exchange of expertise. The conference is an opportunity for researchers in branches of science that require computer modeling and high-performance simulations to discuss computational techniques and technologies.
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