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L. J. Dursi

dblp:05/5660 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 50% Performance modeling and evaluation · 50%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis
base calling
0.312017
Nanocall: an open source basecaller for Oxford Nanopore sequencing data · Bioinform. 2017
Bioinformatics and computational biology › sequence analysis › base calling
nanopore base calling
0.312017
Nanocall: an open source basecaller for Oxford Nanopore sequencing data · Bioinform. 2017
Bioinformatics and computational biology
sequence analysis
0.312017
Nanocall: an open source basecaller for Oxford Nanopore sequencing data · Bioinform. 2017
High-performance computing › scientific computing systems
adaptive mesh refinement
0.012000
High Performance Reactive Fluid Flow Simulations Using Adaptive Mesh Refinement on Thousands of Processors · SC 2000
Performance modeling and evaluation › simulation › parallel and distributed simulation
parallel simulation
0.012000
High Performance Reactive Fluid Flow Simulations Using Adaptive Mesh Refinement on Thousands of Processors · SC 2000

Methods — techniques the papers use, named apart from their topics

parallel computation · 0.3hidden markov model · 0.3
YearPublicationVenuePosition
2017 Nanocall: an open source basecaller for Oxford Nanopore sequencing data
abstract
MOTIVATION: The highly portable Oxford Nanopore MinION sequencer has enabled new applications of genome sequencing directly in the field. However, the MinION currently relies on a cloud computing platform, Metrichor (metrichor.com), for translating locally generated sequencing data into basecalls. RESULTS: To allow offline and private analysis of MinION data, we created Nanocall. Nanocall is the first freely available, open-source basecaller for Oxford Nanopore sequencing data and does not require an internet connection. Using R7.3 chemistry, on two E.coli and two human samples, with natural as well as PCR-amplified DNA, Nanocall reads have ∼68% identity, directly comparable to Metrichor '1D' data. Further, Nanocall is efficient, processing ∼2500 Kbp of sequence per core hour using the fastest settings, and fully parallelized. Using a 4 core desktop computer, Nanocall could basecall a MinION sequencing run in real time. Metrichor provides the ability to integrate the '1D' sequencing of template and complement strands of a single DNA molecule, and create a '2D' read. Nanocall does not currently integrate this technology, and addition of this capability will be an important future development. In summary, Nanocall is the first open-source, freely available, off-line basecaller for Oxford Nanopore sequencing data. AVAILABILITY AND IMPLEMENTATION: Nanocall is available at github.com/mateidavid/nanocall, released under the MIT license. CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.
Matei David, L. J. Dursi, Delia Yao, Paul C. Boutros, Jared T. Simpson
Bioinform.2
2000 High Performance Reactive Fluid Flow Simulations Using Adaptive Mesh Refinement on Thousands of Processors
abstract
We present simulations and performance results of nuclear burning fronts in super- novae on the largest domain and at the finest spatial resolution studied to date. These simulations were performed on the Intel ASCI-Red machine at Sandia National Laboratories using FLASH, a code developed at the Center for Astrophysical Thermonuclear Flashes at the University of Chicago. FLASH is a modular, adaptive mesh, parallel simulation code capable of handling compressible, reactive fluid flows in astrophysical environments. FLASH is written primarily in Fortran 90, uses the Message-Passing Interface library for inter-processor communication and portability, and employs the PARAMESH package to manage a block-structured adaptive mesh that places blocks only where resolution is required and tracks rapidly changing flow features, such as detonation fronts, with ease. We describe the key algorithms and their implementation as well as the optimizations required to achieve sustained performance of 238 GFLOPS on 6420 processors of ASCI-Red in 64 bit arithmetic.
Alan C. Calder, Bruce C. Curtis, L. J. Dursi, Bruce Fryxell, Greg Henry, Peter MacNeice, Kevin Olson, Paul M. Ricker, Robert Rosner, Francis X. Timmes, Henry M. Tufo, J. W. Turan, Michael Zingale
SC3