In conjunction with the IEEE
International Parallel and Distributed Processing Symposium
Announcements:
Confirmed Keynote and Invited Speakers
Valerie Schneider
[Keynote Speaker]
National Library of Medicine, NIH
Title: All the Data! Opportunities and Challenges in Data
Exploration and Analyses from Public Sequence Archives
Abstract: In the last two decades, technological
advances and decreasing costs have driven the use of sequencing as a tool
for biological analysis, resulting in generation of tremendous amounts of
new sequence data from across the tree of life. Organisms from diverse
environments around the world are being sequenced in efforts to understand
an equally diverse range of topics, including fundamental biological processes,
climate change, public health crises, evolution, and human diversity. Advances
in computational methods such as assembly, alignment, and variant detection,
to name a few, have been essential in making use of these sequence data. As hosts
for much of these data, public sequence archives such as the Sequence Read Archive
(SRA) and GenBank at the National Center for Biotechnology Information (NCBI),
are key partners in realizing its value. The scale and scope of the data they
contain present researchers with exciting opportunities to ask new types of
questions and develop novel methods to answer them. This talk will present
recent examples of sequence data management, analysis, and resource development
at NCBI associated with large datasets. It will highlight both new opportunities
for reuse of sequence data in the public archives and challenges in operating on
these data of which researchers should be aware. This work was supported by the
National Center for Biotechnology Information of the National Library of Medicine
(NLM), National Institutes of Health.
Biography: Valerie Schneider, Ph.D., has been at NCBI since 2007 and
is the deputy director of Sequence Offerings and the head of the Sequence Plus
program in the Information Engineering Branch at NCBI. In these roles, she
coordinates efforts associated with the curation, enhancement, and organization
of sequence data, as well as oversees tools and resources that enable the public
to access, analyze, and visualize biomedical data. She also manages NCBI’s involvement
in the Genome Reference Consortium, the international collaboration tasked with
maintaining the value of the human reference genome assembly. She earned a Ph.D. in
Biological and Biomedical Sciences from Harvard University in 2001, followed by a
postdoctoral fellowship at the University of Pennsylvania. In her former life as
a wet lab biologist, she studied various research organisms, including Tetrahymena
thermophila, Drosophila melanogaster, Xenopus laevis, chicken, and zebrafish, to
answer questions relevant to human development.
Dan Jacobson
[Invited Speaker]
Chief Scientist for Computational Systems Biology
Oak Ridge National Laboratory
Title: Crises Abound: Health, Climate, Energy, Food, Pandemics...
How Supercomputing, AI, and Large-Scale Systems Biology Can Help Address the Major
Challenges We Are Facing.
Abstract: The cost of generating biological data is dropping
exponentially, resulting in an explosion in the amount of data available for the
biological sciences. This flood of data has opened a new era of systems biology in
which there are unprecedented opportunities to gain insights into complex biological
systems. Integrated biological models need to capture the higher order complexity of
the interactions among cellular components. Solving such complex combinatorial problems
will give us extraordinary levels of understanding of biological systems. Paradoxically,
understanding higher order sets of relationships among biological objects leads to a
combinatorial explosion in the search space of biological data. These exponentially
increasing volumes of data, combined with the desire to model more and more sophisticated
sets of relationships within a cell, across an organism and up to ecosystems and, in fact,
climatological scales, have led to a need for computational resources and sophisticated
algorithms that can make use of such datasets. The disease, traits or phenotypes of an
organism, including its adaptation to its surrounding environment and the interactions
with its microbiome, are the result of orchestrated, hierarchical, heterogeneous collections
of expressed genomic variants regulated by and related to biotic and abiotic signals.
However, the effects of these variants can be viewed as the result of historic selective
pressure and current environmental as well as epigenetic interactions, and, as such,
their co-occurrence can be seen as omics-wide associations in a number of different
manners. We have developed supercomputing and explainable-AI approaches to find complex
mechanisms responsible for all measurable phenotypes as well as an organism’s ability
to detect and modulate its microbiome. The result is progress towards a comprehensive
systems biology model of an organism and how it has adapted to and responds to its
abiotic and biotic environment which has applications in bioenergy, precision agriculture,
ecosystem studies, precision medicine, and pandemic prevention among other disciplines.
Biography: Dan Jacobson, Ph.D. is currently working as Chief Scientist for
Computational Systems Biology at Oak Ridge National Laboratory. Dan’s career as a
computational systems biologist has included leadership roles in academic, corporate,
NGO and national lab settings. His research focuses on understanding the complex sets
of interactions of molecules of all types (across all omics layers) in cells that lead
to phenotypes, traits and disease states in organisms and how all of that is conditional
on the surrounding environment. Dan’s lab was the first group to perform an exascale
calculation and holds the current record for the fastest calculation done in human
history (9.4 Exaops). For his recent work, Dan has been awarded the Gordon Bell Prize,
the HPCwire Top HPC-enabled Science Award, Oak Ridge National Laboratory Director’s Award,
the Oak Ridge National Laboratory Outstanding Achievement Award, and the Secretary of
Energy’s Achievement Award.
Accepted Papers:
Paper 1. "Parallel Inference of Phylogenetic Stands with Gentrius" authored by Togkousidis, Chernomor, Stamatakis.
Paper 2. "Using Hyperdimensional Computing to Extract Features for the Detection of Type 2 Diabetes" authored by Watkinson, Devineni, Joe, Givargis, Nicolau, Veidenbaum.
Paper 3. "An Efficient Parallel Sketch-based Algorithm for Mapping Long Reads to Contigs", authored by Rahman, Bhowmik, Kalyanaraman.
Paper 4. "Designing Efficient SIMD Kernels for High Performance Sequence Alignment", authored by Popovici, Awan, Guidi, Egan, Hofmeyr, Oliker, Yelick.
Welcome to the 2023 HiCOMB webpage!
Fahad Saeed and Serdar Bozdag will serve as the program chairs for
HiCOMB 2023. Please look for updates below for CFP and PC and other
related information about the workshop's technical program.
Paper submissions are now open and deadline is Jan 21, 2023 Feb 20th, 2023 .
Online HiCOMB Proceedings (covering all
past editions)
HiCOMB 2023 Call For
Papers
The size and complexity of genomic and biomedical big data continue to
grow at a exponential pace, and the analysis of these complex, noisy, data
sets demands efficient algorithms and high performance computing
architectures. Hence, high-performance computing (HPC) has become
an integral part of research and development in bioinformatics,
computational biology, and medical and health informatics. The goal of
the HiCOMB workshop is to showcase novel HPC research and technologies
to solve data- and compute-intensive problems arising from all areas of
computational life sciences. The workshop will feature contributed
papers as well as invited talks from reputed researchers in the field.
For peer-reviewed papers, we invite authors to submit original and
previously unpublished work that are at the intersection of
the "pillars" of modern day computational life sciences and HPC.
More specifically, we encourage submissions from all areas of biology
that can benefit from HPC, and from all areas of HPC that need new
development to address the class of computational problems that
originate from biology.
Areas of interest within computational life sciences include (but not
limited to):
- Biological sequence analysis (genome assembly, long/short read
data structures, read mapping, clustering, variant analysis, error
correction, genome annotation)
- Computational structural biology (protein structure, RNA
structure)
- Functional genomics (transcriptomics, RNAseq/microarrays, single
cell analysis, proteomics, phospho-proteomics)
- Systems biology and networks (biological network analysis, gene
regulatory networks, metabolomics, molecular pathways)
- Tools for integrated multi-omics and biological databases (network
construction, modeling, link inference)
- Computational modeling and simulation of biological systems
(molecular dynamics, protein structure/docking, dynamic models)
- Phylogeny (phylogenetic tree reconstruction, molecular evolution)
- Microbes and microbiomes (taxonomical binning, metagenomics,
classification, clustering, annotation)
- Biomedical health analytics and biomedical imaging (electronic
health records, precision medicine, image analysis)
- Biomedical literature mining (text mining, ontology, natural
language processing)
- Computational epidemiology (infectious diseases, diffusion
mechanisms)
- Phenomics and precision agriculture (IoT technologies, feature
extraction)
- Visualization of large-scale biomedical data and patient
trajectories
Areas of interest within HPC include (but are not limited to):
- Parallel and distributed algorithms (scalable machine learning,
parallel graph/sequence analytics, combinatorial pattern matching,
optimization, parallel data structures, compression)
- Biological data management, metadata standards such as compliance
to FAIR principles, AI-ready data processing
- Data-intensive computing techniques
(communication-avoiding/synchronization-reducing techniques,
locality-preserving techniques, big data streaming techniques)
- Parallel architectures (multicore, manycore, CPU/GPU, FPGA,
system-on-chip, hardware accelerators, energy-aware architectures,
hardware/software co-design)
- Memory and storage technologies (processing-in-memory, NVRAM,
burst buffers, 3D RAM, parallel/distributed I/O)
- Parallel programming models (libraries, domain specific languages,
compiler/runtime systems)
- Scalable AI/ML frameworks for biological systems, modeling, and
analysis
- Scientific workflows (data management, data wrangling, automated
workflows, productivity)
- Scientific computing (numerical analysis, optimization)
- Empirical evaluations (performance modeling, case-studies)
Submission guidelines
To submit a paper, please upload a PDF file through the Linklings
HiCOMB 2023 submission link:
https://ssl.linklings.net/conferences/ipdps/?page=Submit&id=HiCOMBWorkshopFullSubmission&site=ipdps2023
IPDPS
workshops can have submission in three categories: regular papers (up
to 10 pages), short papers (up to 4 pages), and extended abstracts (1
page). Submitted manuscripts may not exceed ten (10) single-spaced
double-column pages using a 10-point size font on 8.5x11 inch pages
(IEEE conference style), including figures, tables, and references
(see IPDPS
Call for Papers for more details). All papers will be reviewed
by three or more referees. This year, the authors of the accepted
papers will be given a choice on whether to have the paper appear in
the IPDPSW Proceedings (which will be digitally indexed and archived
as part of the IEEE Xplore Digital Library). If the authors choose not
to make it part of the proceedings, then the paper will not
be considered archival. In either case, all accepted papers
will be posted online on the workshop website, and all accepted papers
(archived or not) will need to have an oral presentation at the
workshop by one of the authors of the paper.
Important Dates
Workshop
submission deadline
(for all categories):
|
Jan 21, 2023 Feb 20th, 2023
|
| Author notification: |
March 1st, 2023 |
| Final camera-ready papers deadline: |
March 7, 2023 |
| Workshop: |
May 15, 2023 |
Program Chairs
Zeeshan Ahmed (Rutgers Institute for Health)
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Shoaib Akram (Australian National University
Mohammed Alser (ETH Zurich)
Muaaz Gul Awan (Lawrence Berkeley National Laboratory)
Brittany Baur (University of Michigan)
Sanjukta Bhowmick (University of North Texas)
Banabithi Bose (Northwestern University)
Ercument Cicek (Bilkent University)
Xuan Guo (University of North Texas)
Ajay Gupta (Western Michigan University)
Yuede Ji (University of North Texas)
Ziynet Nesibe Kesimoglu (University of North Texas)
Ashfaq Khokhar (Iowa State University)
Sumesh Kumar (Florida International University)
Yongchao Liu (Ant Group)
Sita Sirisha Madugula (University of north Texas Health Sciences)
Serghei Mangul (USC)
Umair Mohammad (Florida International University)
Ananda Mondal (Florida International University)
Chad Myers (University of Minnesota)
Giri Narasimhan (Florida International University)
Ibrahim Numanagi (University of Victoria)
Jubair Ibn Malik Rifat (University of North Texas)
Ashok Srinivasan (University of West Florida)
Sandino Vargas-Parez (Kalamazoo College)
Yashu Vashishath (University of North Texas)
General Chairs
Steering Committee Members
HiCOMB Archive