skip to main content

Search for: All records

Creators/Authors contains: "Zhou, Jin"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Free, publicly-accessible full text available October 10, 2023
  2. The cache plays a key role in determining the performance of applications, no matter for sequential or concurrent programs on homogeneous and heterogeneous architecture. Fixing cache misses requires to understand the origin and the type of cache misses. However, this remains to be an unresolved issue even after decades of research. This paper proposes a unified profiling tool--CachePerf--that could correctly identify different types of cache misses, differentiate allocator-induced issues from those of applications, and exclude minor issues without much performance impact. The core idea behind CachePerf is a hybrid sampling scheme: it employs the PMU-based coarse-grained sampling to select very few susceptible instructions (with frequent cache misses) and then employs the breakpoint-based fine-grained sampling to collect the memory access pattern of these instructions. Based on our evaluation, CachePerf only imposes 14% performance overhead and 19% memory overhead (for applications with large footprints), while identifying the types of cache misses correctly. CachePerf detected 9 previous-unknown bugs. Fixing the reported bugs achieves from 3% to 3788% performance speedup. CachePerf will be an indispensable complementary to existing profilers due to its effectiveness and low overhead.
    Free, publicly-accessible full text available June 20, 2023
  3. Free, publicly-accessible full text available June 1, 2023
  4. Free, publicly-accessible full text available May 1, 2023
  5. Abstract

    Charge transport in organic molecular crystals (OMCs) is conventionally categorized into two limiting regimes − band transport, characterized by weak electron-phonon (e-ph) interactions, and charge hopping due to localized polarons formed by strong e-ph interactions. However, between these two limiting cases there is a less well understood intermediate regime where polarons are present but transport does not occur via hopping. Here we show a many-body first-principles approach that can accurately predict the carrier mobility in this intermediate regime and shed light on its microscopic origin. Our approach combines a finite-temperature cumulant method to describe strong e-ph interactions with Green-Kubo transport calculations. We apply this parameter-free framework to naphthalene crystal, demonstrating electron mobility predictions within a factor of 1.5−2 of experiment between 100 and 300 K. Our analysis reveals the formation of a broad polaron satellite peak in the electron spectral function and the failure of the Boltzmann equation in the intermediate regime.

  6. Free, publicly-accessible full text available February 20, 2023
  7. Maex, Reinoud (Ed.)
    Semiparametric joint models of longitudinal and competing risk data are computationally costly, and their current implementations do not scale well to massive biobank data. This paper identifies and addresses some key computational barriers in a semiparametric joint model for longitudinal and competing risk survival data. By developing and implementing customized linear scan algorithms, we reduce the computational complexities from O n 2 or O n 3 to O n in various steps including numerical integration, risk set calculation, and standard error estimation, where n is the number of subjects. Using both simulated and real-world biobank data, we demonstrate that these linear scan algorithms can speed up the existing methods by a factor of up to hundreds of thousands when n > 1 0 4 , often reducing the runtime from days to minutes. We have developed an R package, FastJM, based on the proposed algorithms for joint modeling of longitudinal and competing risk time-to-event data and made it publicly available on the Comprehensive R Archive Network (CRAN).
    Free, publicly-accessible full text available February 8, 2023
  8. Free, publicly-accessible full text available April 1, 2023
  9. Abstract Background Low-depth sequencing allows researchers to increase sample size at the expense of lower accuracy. To incorporate uncertainties while maintaining statistical power, we introduce to analyze population structure of low-depth sequencing data. Results The method optimizes the choice of nonlinear transformations of dosages to maximize the Ky Fan norm of the covariance matrix. The transformation incorporates the uncertainty in calling between heterozygotes and the common homozygotes for loci having a rare allele and is more linear when both variants are common. Conclusions We apply to samples from two indigenous Siberian populations and reveal hidden population structure accurately using only a single chromosome. The package is available on https://github.com/yiwenstat/MCPCA_PopGen .