John Cazes

dblp:145/5225 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0001-6607-2152ORCID · corroborated

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
2 papers
Storage systems · 64% High-performance computing · 36%

Topics — the 8 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
multiple sequence alignment
0.212014
PUmPER: phylogenies updated perpetually · Bioinform. 2014
Bioinformatics and computational biology
phylogenetics
0.212014
PUmPER: phylogenies updated perpetually · Bioinform. 2014
Bioinformatics and computational biology › phylogenetics
phylogenetic inference
0.212014
PUmPER: phylogenies updated perpetually · Bioinform. 2014
Bioinformatics and computational biology › multiple sequence alignment
progressive alignment
0.212014
PUmPER: phylogenies updated perpetually · Bioinform. 2014
Storage systems › file systems › distributed file system
parallel file system
0.212014
A User-Friendly Approach for Tuning Parallel File Operations · SC 2014
High-performance computing
parallel i/o
0.212014
A User-Friendly Approach for Tuning Parallel File Operations · SC 2014
Storage systems › i/o optimization
parallel i/o optimization
0.212014
A User-Friendly Approach for Tuning Parallel File Operations · SC 2014
Storage systems › file systems › distributed file system › parallel file system
lustre file system
0.112014
A User-Friendly Approach for Tuning Parallel File Operations · SC 2014

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

starting topology reuse · 0.4maximum likelihood · 0.4performance modeling · 0.2auto-tuning library · 0.2
YearPublicationVenuePosition
2014 A User-Friendly Approach for Tuning Parallel File Operations
abstract
The Lustre file system provides high aggregated I/O bandwidth and is in widespread use throughout the HPC community. Here we report on work (1) developing a model for understanding collective parallel MPI write operations on Lustre, and (2) producing a library that optimizes parallel write performance in a user-friendly way. We note that a system's default stripe count is rarely a good choice for parallel I/O, and that performance depends on a delicate balance between the number of stripes and the actual (not requested) number of collective writers. Unfortunate combinations of these parameters may degrade performance considerably. For the programmer, however, it's all about the stripe count: an informed choice of this single parameter allows MPI to assign writers in a way that achieves near-optimal performance. We offer recommendations for those who wish to tune performance manually and describe the easy-to-use T3PIO library that manages the tuning automatically.
Robert T. McLay, Doug James, Si Liu 0008, John Cazes, William L. Barth
SC4
2014 PUmPER: phylogenies updated perpetually
abstract
SUMMARY: New sequence data useful for phylogenetic and evolutionary analyses continues to be added to public databases. The construction of multiple sequence alignments and inference of huge phylogenies comprising large taxonomic groups are expensive tasks, both in terms of man hours and computational resources. Therefore, maintaining comprehensive phylogenies, based on representative and up-to-date molecular sequences, is challenging. PUmPER is a framework that can perpetually construct multi-gene alignments (with PHLAWD) and phylogenetic trees (with ExaML or RAxML-Light) for a given NCBI taxonomic group. When sufficient numbers of new gene sequences for the selected taxonomic group have accumulated in GenBank, PUmPER automatically extends the alignment and infers extended phylogenetic trees by using previously inferred smaller trees as starting topologies. Using our framework, large phylogenetic trees can be perpetually updated without human intervention. Importantly, resulting phylogenies are not statistically significantly worse than trees inferred from scratch. AVAILABILITY AND IMPLEMENTATION: PUmPER can run in stand-alone mode on a single server, or offload the computationally expensive phylogenetic searches to a parallel computing cluster. Source code, documentation, and tutorials are available at https://github.com/fizquierdo/perpetually-updated-trees. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary Material is available at Bioinformatics online.
Fernando Izquierdo-Carrasco, John Cazes, Stephen A. Smith, Alexandros Stamatakis
Bioinform.2