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DTSTART;TZID=America/Chicago:20181114T150000
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UID:submissions.supercomputing.org_SC18_sess468@linklings.com
SUMMARY:ACM Student Research Competition
DESCRIPTION:Accelerating 2D FFT: Exploit GPU Tensor Cores through Mixed-Pr
 ecision\n\nThe two-dimensional Fourier Transform is a widely-used computat
 ional kernel in many HPC applications. The popular NVIDIA cuFFT library pr
 ovides a simple interface to compute 2D FFT on GPUs, but it's yet to utili
 ze the recent hardware advancement in half-precision floating-point arithm
 etic. In this p...\n\n\nXiaohe Cheng (Hong Kong University of Science and 
 Technology) and Anumeena Sorna (National Institute of Technology, Tiruchir
 appalli)\n---------------------\nSimFS: A Simulation Data Virtualizing Fil
 e System Interface\n\nIn the big (simulation) data era, simulations often 
 produce petabytes of data to be stored in parallel filesystems or large-sc
 ale databases. This data is accessed, often by thousands of analysts and s
 cientists, over the course of decades. However, storing these volumes of d
 ata for long time periods ...\n\n\nSalvatore Di Girolamo (ETH Zurich)\n---
 ------------------\nModeling Single-Source Shortest Path Algorithm Dynamic
 s to Control Performance and Power Tradeoffs\n\nThis work presents a new m
 ethodology to improve the performance of parallel algorithms by tuning the
  amount of available parallelism for execution throughout the runtime. As 
 such, we expose key parameters controlling the performance and parallelism
  of the algorithm and build a software-based control...\n\n\nSara Karamati
 , Jeffrey Young, and Rich Vuduc (Georgia Institute of Technology)\n-------
 --------------\nMeasuring Swampiness: Quantifying Chaos in Large Heterogen
 eous Data Repositories\n\nAs scientific data repositories and filesystems 
 grow in size and complexity, they become increasingly disorganized. The co
 upling of massive quantities of data with poor organization makes it chall
 enging for scientists to locate and utilize relevant data, thus slowing th
 e process of analyzing data of...\n\n\nLuann C. Jung (Massachusetts Instit
 ute of Technology, University of Chicago) and Brendan T. Whitaker (Ohio St
 ate University, University of Chicago)\n---------------------\nStudying th
 e Impact of Power Capping on MapReduce-Based, Data-Intensive Mini-Applicat
 ions on Intel KNL and KNM Architectures\n\nIn this poster, we quantitative
 ly measure the impacts of data movement on performance in MapReduce-based 
 applications when executed on HPC systems. We leverage the PAPI ‘powercap’
  component to identify ideal conditions for execution of our applications 
 in terms of (1) dataset characteristics (i.e., ...\n\n\nJoshua H. Davis (U
 niversity of Delaware)\n---------------------\nUsing Integrated Processor 
 Graphics to Accelerate Concurrent Data and Index Structures\n\nWith the ad
 vent of computing systems with on-die integrated processor graphics (iGPU)
 , new programming challenges have emerged from these heterogeneous systems
 . We proposed different data and index structure algorithms that can benef
 it from the Intel's iGPU architecture and the C for Media (CM) prog...\n\n
 \nJoel Fuentes (University of California, Irvine)\n---------------------\n
 Accelerating Microscope Data Analysis Using Parallel Computing\n\nSingle-M
 olecule Localization Microscopy (SMLM) techniques deal with the diffractio
 n limit of fluorescent microscopy by localizing single molecules with high
  precision by stochastically switching molecules on and off. Thousands of 
 camera frames containing subsets of blinking molecules are recorded to...\
 n\n\nJohn Ravi (North Carolina State University)\n---------------------\nA
 ccelerating DNA Long Read Mapping with Emerging Technologies\n\nDNA sequen
 cing technologies output only short fragments of a genome, called reads. N
 ew single-molecule real-time sequencing technologies can produce long read
 s, up to tens of thousands base pairs, within minutes. However, these long
  reads may contain up to 15% errors.\n\nTo construct a genome from DNA...\
 n\n\nRoman Kaplan (Israel Institute of Technology)\n---------------------\
 nRecursive Algebraic Coloring Engine\n\nMany iterative numerical methods f
 or sparse systems and building blocks of sparse linear algebra are difficu
 lt to parallelize due to data dependencies. These may be loop-carried depe
 ndencies as they occur in solvers like Gauss-Seidel or write conflicts as 
 in symmetric sparse matrix vector.  Most of ...\n\n\nChristie Louis Alappa
 t (University of Erlangen-Nuremberg)\n\nTag: Student Program, ACM Student 
 Research Competition\n\nRegistration Category: Tech Program Reg Pass
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