Internet2 and National Science Foundation Announce Selection of First-Phase Research Proposals for Exploring Clouds for Acceleration of Science (E-CAS) Project

WASHINGTON–()–Internet2 and the National Science Foundation (NSF) confirmed
the selection of six proposals by an external academic review panel for
the first phase of the Exploring Clouds for Acceleration of Science
(E-CAS) project
that was first announced
in November 2018
. The E-CAS project comprises two phases of
NSF-funded, campus-based research that will be supported in part through
contributions from Amazon Web Services and Google Cloud to produce a
deeper understanding of the use of cloud computing in accelerating
scientific discoveries.

The successful proposals for the year-long first phase of the E-CAS
project are:

Development of BioCompute Objects for Integration into Galaxy in a
Cloud Computing Environment

Raja Mazumder, George Washington

BioCompute objects allow researchers to describe bioinformatic analyses
comprised of any number of algorithmic steps and variables to make
computational experimental results clearly understandable and easier to
repeat. This project will create a library of BioCompute objects that
describe bioinformatic workflows on AWS, which can be accessed and
contributed to by users of the widely used bioinformatics platform,

Investigating Heterogeneous Computing at the Large Hadron Collider
Harris, Massachusetts Institute of Technology

Only a small fraction of the 40 million collisions per second at the
Large Hadron Collider are stored and analyzed due to the huge volumes of
data and the compute power required to process it. This project proposes
a redesign of the algorithms using modern machine learning techniques
that can be incorporated into heterogeneous computing systems, allowing
more data to be processed and thus larger physics output and potentially
foundational discoveries in the field.

Building Clouds: Worldwide building typology modelling from images
Aliaga and Dev Niyogi, Purdue University

This project will utilize computational power and network connectivity
to provide a world-scalable solution for generating building-level
information for urban canopy parameters as well as for improving the
information for estimating local climate zones, both of which are
critical to high resolution urban meteorological/environmental models.

Accelerating Science by Integrating Commercial Cloud Resources in the
CIPRES Science Gateway

Mark Miller, San Diego Supercomputing

CIPRES is a web portal that allows scientists around the world to
analyze DNA and protein sequence data by providing access to parallel
phylogenetics codes run on large high-performance computing (HPC)
clusters provided by the NSF-funded eXtreme
Science and Engineering Discovery Environment (XSEDE) program
currently runs analyses for about 12,000 scientists per year. This
project will develop the infrastructure needed to cloudburst CIPRES jobs
to newer, faster V100 GPUs at AWS. As a result, individual jobs will run
up to 1.8 fold faster, and users will have access to twice as many GPU
nodes as they did in the previous year.

Deciphering the Brain’s Neural Code Through Large-Scale Detailed
Simulation of Motor Cortex Circuits

William Lytton, State
University of New York

This project aims to help decipher the brain’s neural coding mechanisms
with far-reaching applications, including developing treatments for
brain disorders, advancing brain-machine interfaces for people with
paralysis, and developing novel artificial intelligence algorithms.
Using a software tool for brain modeling, researchers will run thousands
of parallelized simulations exploring different conditions and inputs to
the system.

IceCube computing in the cloud
Benedikt Riedel,
University of Wisconsin

The IceCube Neutrino Observatory located at the South Pole supports
science from a number of disciplines including astrophysics, particle
physics, and geographical sciences operating continuously being
simultaneously sensitive to the whole sky. This project aims to burst
into cloud to support follow-up computations of observed events, as well
as alerts to and from the research community, such as other telescopes
and LIGO.

“NSF is thrilled to see the scientific diversity and potential among the
selected projects. We look forward to the progress over the next year
for these six projects as they investigate the viability and
effectiveness of commercial clouds as an option for leading-edge
research computing and computational science in a range of areas,” said
Manish Parashar, Director of NSF’s Office of Advanced
Cyberinfrastructure (OAC).

“More recent advancements in cloud offerings allow researchers to
explore unique ways of processing huge amounts of data with highly
complex inter-relationships using high-throughput computational methods
and machine learning systems,” added Howard Pfeffer, president and CEO
of Internet2, and principal investigator on the E-CAS project. “We’re
excited to support these important and timely scientific research
projects as we collectively explore how advancement in commercial clouds
can better support the work of researchers and the higher education

Following the completion of the first phase of these six research
projects, two final projects will be selected in July 2020 for another
year of support, with a focus on delivering scientific results. Each
phase of the project will be followed by a community-led workshop to
assess lessons learned and to define leading practices.

For more information about the E-CAS project, please visit

The National Science Foundation (NSF) is an independent federal
agency that supports fundamental research and education across all
fields of science and engineering. In fiscal year (FY) 2018, its budget
was $7.8 billion. NSF funds reach all 50 states through grants to nearly
2,000 colleges, universities and other institutions. Each year, NSF
receives more than 50,000 competitive proposals for funding and makes
about 12,000 new funding awards.

This material is based upon work supported by the National Science
Foundation under Grant No. 1904444. Any opinions, findings, and
conclusions or recommendations expressed in this material are those of
the author(s) and do not necessarily reflect the views of the National
Science Foundation.

About Internet2

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community whose core infrastructure components include the nation’s
largest and fastest research and education network that was built to
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