Yi Zhang

  1. Optimizing I/O for Big Array Analytics.

    Authors: Yi Zhang, Jun Yang
    Subjects: Databases
    Abstract

    Big array analytics is becoming indispensable in answering important
    scientific and business questions. Most analysis tasks consist of multiple
    steps, each making one or multiple passes over the arrays to be analyzed and
    generating intermediate results. In the big data setting, I/O optimization is a
    key to efficient analytics. In this paper, we develop a framework and
    techniques for capturing a broad range of analysis tasks expressible in
    nested-loop forms, representing them in a declarative way, and optimizing their
    I/O by identifying sharing opportunities.

  2. Bounds on the Hilbert-Kunz Multiplicity.

    Authors: Yi Zhang, Hailong Dao, Craig Huneke, Olgur Celikbas
    Subjects: Commutative Algebra
    Abstract

    In this paper we give new lower bounds on the Hilbert-Kunz multiplicity of
    unmixed non-regular local rings, bounding them uniformly away from one. Our
    results improve previous work of Aberbach and Enescu.

  3. A Property Of Local Cohomology Modules Of Polynomial Rings.

    Authors: Yi Zhang
    Subjects: Commutative Algebra
    Abstract

    Let $R=k[x_1,..., x_n]$ be a polynomial ring over a field $k$ of
    characteristic $p>0,$ and let $I=(f_1,...,f_s)$ be an ideal of $R.$ We prove
    that every associated prime $P$ of $H^i_I(R)$ satisfies $\text{dim}R/P\geqslant
    n-\sum\text{deg}f_i.$ In characteristic 0 the question is open.

  4. A Property of the Frobenius Map of a Polynomial Ring.

    Authors: Yi Zhang, Gennady Lyubeznik, Wenliang Zhang
    Subjects: Commutative Algebra
    Abstract

    Let R be a ring of polynomials in a finite number of variables over a perfect
    field k of characteristic p>0 and let F:R\to R be the Frobenius map of R, i.e.
    F(r)=r^p. We explicitly describe an R-module isomorphism Hom_R(F_*(M),N)\cong
    Hom_R(M,F^*(N)) for all R-modules M and N. Some recent and potential
    applications are discussed.

  5. RIOT: I/O-Efficient Numerical Computing without SQL.

    Authors: Yi Zhang, Herodotos Herodotou, Jun Yang
    Subjects: Databases
    Abstract

    R is a numerical computing environment that is widely popular for statistical
    data analysis. Like many such environments, R performs poorly for large
    datasets whose sizes exceed that of physical memory. We present our vision of
    RIOT (R with I/O Transparency), a system that makes R programs I/O-efficient in
    a way transparent to the users. We describe our experience with RIOT-DB, an
    initial prototype that uses a relational database system as a backend.

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