title: Compression in Molecular Simulation Datasets.
abstract: In this paper, we present a compression framework, for molecular dynamics (MD) simulation data, which yields significant performance by combining the strength of principal component analysis (PCA) and discrete cosine transform (DCT). Though it is a lossy compression technique, the effect on analytics performed on decompressed data is very minimal. Compression ratio up to 13 is achieved with acceptable errors in results of analytical functions.
authors.affiliation: Department of Computer Science and Engineering, University of South Florida, Tampa, FL - 33620, U.S.A.
authors.forename: Anand
authors.initials: A
authors.lastname: Kumar
authors.affiliation: Department of Computer Science and Engineering, Florida Atlantic University, Boca Raton, FL - 33431, U.S.A.
authors.forename: Xingquan
authors.initials: X
authors.lastname: Zhu
authors.affiliation: Department of Computer Science and Engineering, University of South Florida, Tampa, FL - 33620, U.S.A.
authors.forename: Yi-Cheng
authors.initials: YC
authors.lastname: Tu
authors.affiliation: Department of Physics, University of South Florida, Tampa, FL - 33620, U.S.A.
authors.forename: Sagar
authors.initials: S
authors.lastname: Pandit
keywords: compression ratio; data compression; discrete cosine transform; encoding; molecular simulations; principal component analysis