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BEGIN:VEVENT
DTSTAMP:20260522T150153Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181113T083000
DTEND;TZID=America/Chicago:20181113T170000
UID:submissions.supercomputing.org_SC18_sess325@linklings.com
SUMMARY:ACM Student Research Competition Posters
DESCRIPTION:SC18 ACM Student Research Competition Posters will be on displ
 ay on Tuesday, Wednesday, Thursday from 8:30am to 5pm in the C2/3/4 Ballro
 om.\n\nThe schedule of the ACM Student Research Competition session will b
 e made available Wednesday evening form the results of the semi-finalists 
 selection that will happen after the poster session.\n\nAccelerating Big D
 ata Processing in the Cloud with Scalable Communication and I/O Schemes\n\
 nWith the advent of cloud computing, the field of Big Data has seen rapid 
 growth. Most cloud providers provide hardware resources such as NVMe SSDs,
  large memory nodes, and SR-IOV. This opens up the possibility of large-sc
 ale high-performance data analytics and provides opportunities to use thes
 e res...\n\n\nShashank Gugnani (Ohio State University)\n------------------
 ---\nModeling Single-Source Shortest Path Algorithm Dynamics to Control Pe
 rformance and Power Tradeoffs\n\nThis work presents a new methodology to i
 mprove the performance of parallel algorithms by tuning the amount of avai
 lable parallelism for execution throughout the runtime. As such, we expose
  key parameters controlling the performance and parallelism of the algorit
 hm 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 Heterogeneous Data Repos
 itories\n\nAs scientific data repositories and filesystems grow in size an
 d complexity, they become increasingly disorganized. The coupling of massi
 ve quantities of data with poor organization makes it challenging for scie
 ntists to locate and utilize relevant data, thus slowing the process of an
 alyzing data of...\n\n\nLuann C. Jung (Massachusetts Institute of Technolo
 gy, University of Chicago) and Brendan T. Whitaker (Ohio State University,
  University of Chicago)\n---------------------\nHardware Transactional Per
 sistent Memory\n\nThis research solves the problem of creating durable tra
 nsactions in byte-addressable Non-Volatile Memory or Persistent Memory (PM
 ) when using Hardware Transactional Memory (HTM)-based concurrency control
 .  It shows how HTM transactions can be ordered correctly and atomically i
 nto PM by the use of a...\n\n\nEllis Giles (Rice University)\n------------
 ---------\nAccelerating DNA Long Read Mapping with Emerging Technologies\n
 \nDNA sequencing technologies output only short fragments of a genome, cal
 led reads. New single-molecule real-time sequencing technologies can produ
 ce long reads, 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----------
 -----------\nOoO Instruction Benchmarking Framework on the Back of Dragons
 \n\nIn order to construct an accurate instruction execution model for mode
 rn out-of-order micro architectures, an accurate description of instructio
 n latency, throughput and concurrency is indispensable. Already existing r
 esources and vendor provided information is neither complete nor detailed 
 enough a...\n\n\nJulian Hammer (University of Erlangen-Nuremberg, RRZE)\n-
 --------------------\nPotC: Many-Body Potential Implementations à La Carte
 \n\nMolecular dynamics is a valuable investigation tool for simulations in
  computational chemistry and materials science. In these simulations, atom
 s move according to so-called potentials, functions that typically describ
 e the distance-dependent interactions between pairs of atoms. For some app
 lication...\n\n\nMarkus Höhnerbach (RWTH Aachen University)\n-------------
 --------\nNumerical Simulation of a Flue Instrument with Finite-Difference
  Lattice Boltzmann Method using GPGPU\n\nIn this work, we discuss the poss
 ibility of using GPGPU techniques for Aeroacoustic Simulation (especially 
 for flue instruments) with the finite-difference lattice Boltzmann method 
 (FDLBM).   Compressible flow simulation has been used in direct aeroacoust
 ic simulation; however, the computational cos...\n\n\nRyoya Tabata (Kyushu
  Institute of Technology)\n---------------------\nDesigning Shared Address
  Space MPI Libraries in Many-Core Era\n\nThe emergence of modern multi-/ma
 ny-cores has put more emphasis on optimizing intra-node communication. Exi
 sting designs in MPI libraries that work on the concept of distributed add
 ress spaces incur the overhead of intermediate memory copies to stage the 
 data between processes. This can lead to seve...\n\n\nJahanzeb Maqbool Has
 hmi (Ohio State University)\n---------------------\nIdentifying Network Da
 ta Transfer Bottlenecks in HPC Systems\n\nImproving network data transfer 
 performance is a major factor for improving high performance computing sys
 tems. Most studies analyze data transfer and file system IO performance se
 parately, but understanding the relationship between the two is essential 
 for optimizing scheduling and resource managem...\n\n\nKaren Tu (Lawrence 
 Berkeley National Laboratory; University of California, Berkeley)\n-------
 --------------\nStudying the Impact of Power Capping on MapReduce-Based, D
 ata-Intensive Mini-Applications on Intel KNL and KNM Architectures\n\nIn t
 his poster, we quantitatively measure the impacts of data movement on perf
 ormance in MapReduce-based applications when executed on HPC systems. We l
 everage the PAPI ‘powercap’ component to identify ideal conditions for exe
 cution of our applications in terms of (1) dataset characteristics (i.e., 
 ...\n\n\nJoshua H. Davis (University of Delaware)\n---------------------\n
 Using Integrated Processor Graphics to Accelerate Concurrent Data and Inde
 x Structures\n\nWith the advent of computing systems with on-die integrate
 d processor graphics (iGPU), new programming challenges have emerged from 
 these heterogeneous systems. We proposed different data and index structur
 e algorithms that can benefit from the Intel's iGPU architecture and the C
  for Media (CM) prog...\n\n\nJoel Fuentes (University of California, Irvin
 e)\n---------------------\nSupercomputing for the Multi-Driver Routing\n\n
 Supercomputing is essential for routing traffic by providing drivers the o
 ptimal routes with minimal traveling distances or time. The unique challen
 ges that require supercomputers to overcome are of multiple folds: numerou
 s drivers, massive simultaneous requests, multiple locations, and needs of
  ins...\n\n\nZeyang Ye (Stony Brook University)\n---------------------\nHo
 listic Root Cause Analysis of Node Failures in Production HPC\n\nProductio
 n HPC clusters endure failures incurring computation and resource wastage.
  Despite the presence of various failure detection and prediction schemes,
  a comprehensive understanding of how nodes fail considering various compo
 nents and layers of the system is required for sustained resilience. ...\n
 \n\nAnwesha Das (North Carolina State University)\n---------------------\n
 Recursive Algebraic Coloring Engine\n\nMany iterative numerical methods fo
 r sparse systems and building blocks of sparse linear algebra are difficul
 t to parallelize due to data dependencies. These may be loop-carried depen
 dencies as they occur in solvers like Gauss-Seidel or write conflicts as i
 n symmetric sparse matrix vector.  Most of ...\n\n\nChristie Louis Alappat
  (University of Erlangen-Nuremberg)\n---------------------\nMitigating Per
 formance and Progress Variability in Iterative Asynchronous Algorithms\n\n
 Large HPC machines are susceptible to irregular performance. Factors like 
 chip manufacturing differences, heat management, and network congestion co
 mbine to result in varying execution time for the same code and input sets
 . Asynchronous algorithms offer a partial solution. In these algorithms, f
 ast ...\n\n\nJusts Zarins (University of Edinburgh)\n---------------------
 \nNautDB: Toward a Hybrid Runtime for Processing Compiled Queries\n\nGener
 al purpose operating and database system suffer under the load of their ge
 nerality which makes achieving optimal performance extremely hard, especia
 lly on modern hardware. The goal of this research is to integrate, for the
  first time, specialization techniques from the OS community (hybrid runt.
 ..\n\n\nSamuel Grayson (University of Texas, Dallas)\n--------------------
 -\nAccelerating 2D FFT: Exploit GPU Tensor Cores through Mixed-Precision\n
 \nThe two-dimensional Fourier Transform is a widely-used computational ker
 nel in many HPC applications. The popular NVIDIA cuFFT library provides a 
 simple interface to compute 2D FFT on GPUs, but it's yet to utilize the re
 cent hardware advancement in half-precision floating-point arithmetic. In 
 this p...\n\n\nXiaohe Cheng (Hong Kong University of Science and Technolog
 y) and Anumeena Sorna (National Institute of Technology, Tiruchirappalli)\
 n---------------------\nSimFS: A Simulation Data Virtualizing File System 
 Interface\n\nIn the big (simulation) data era, simulations often produce p
 etabytes of data to be stored in parallel filesystems or large-scale datab
 ases. This data is accessed, often by thousands of analysts and scientists
 , over the course of decades. However, storing these volumes of data for l
 ong time periods ...\n\n\nSalvatore Di Girolamo (ETH Zurich)\n------------
 ---------\nDendro-GR: Massively Parallel Simulations of Binary Black Hole 
 Intermediate-Mass-Ratio Inspirals\n\nWe present a portable and highly-scal
 able algorithm and framework that targets problems in the astrophysics and
  numerical relativity communities. This framework combines together a para
 llel octree-refined adaptive mesh with wavelet adaptive multiresolution an
 d a physics module to solve the Einstein ...\n\n\nMilinda Fernando (Univer
 sity of Utah)\n---------------------\nGeomancy: Automated Data Placement O
 ptimization\n\nExascale cloud storage and High-Performance Computing Syste
 ms (HPC) deliver unprecedented storage capacity and levels of computing po
 wer, though the full potential of these systems remain untapped because of
  inefficient data placement. Changes in data access patterns can cause a s
 ystem's performance...\n\n\nOceane Bel (University of California, Santa Cr
 uz)\n---------------------\nPrecomputing Outputs of Hidden Layers to Speed
  Up Deep Neural Network Training\n\nDeep learning has recently emerged as 
 a powerful technique for many tasks including image classification. A key 
 bottleneck of deep learning is that the training phase takes a lot of time
 , since state-of-the-art deep neural networks have millions of parameters 
 and hundreds of hidden layers. The early...\n\n\nSohil Lal Shrestha (Unive
 rsity of Texas, Arlington)\n---------------------\nEulerian Algorithms for
  the Discretization of Plasma Kinetic Equations\n\nWhile fluid models are 
 common tools in the study of plasmas, many of these systems, whether in as
 trophysics or the lab, are only weakly collisional and far from equilibriu
 m, making them more accurately described by kinetic equations. Kinetic equ
 ations can be computationally demanding due to the need...\n\n\nJames L. J
 uno (University of Maryland)\n---------------------\nAccelerating Microsco
 pe Data Analysis Using Parallel Computing\n\nSingle-Molecule Localization 
 Microscopy (SMLM) techniques deal with the diffraction limit of fluorescen
 t microscopy by localizing single molecules with high precision by stochas
 tically switching molecules on and off. Thousands of camera frames contain
 ing subsets of blinking molecules are recorded to...\n\n\nJohn Ravi (North
  Carolina State University)\n---------------------\nMonitoring Parsl Workf
 lows\n\nAs a Python library that enables workflows, Parsl gives users the 
 ability to define complex workflows in Python and run them in parallel on 
 any computer system. This poster describe the process of adding monitoring
  to Parsl. Simple and comprehensive monitoring of a workflow’s state and r
 esource usag...\n\n\nConnor Pigg (University of Illinois)\n\nRegistration 
 Category: Tech Program Reg Pass, Exhibits Reg Pass
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