| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | August 30, 2021 |
| Latest Amendment Date: | April 7, 2023 |
| Award Number: | 2126253 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Kevin Thompson
kthompso@nsf.gov (703)292-4220 OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2021 |
| End Date: | September 30, 2024 (Estimated) |
| Total Intended Award Amount: | $400,000.00 |
| Total Awarded Amount to Date: | $416,000.00 |
| Funds Obligated to Date: |
FY 2022 = $16,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
11200 SW 8TH ST MIAMI FL US 33199-2516 (305)348-2494 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
11200 SW 8TH ST Miami FL US 33199-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Campus Cyberinfrastructure |
| Primary Program Source: |
01002122DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Building resilient, sustainable, livable, and environmentally safe dynamic systems (natural or human built) requires on-demand computing resources, facilitating machine learning, data processing, and data analytics. These systems rely on computation to support simulation, modeling, and analyses to enable discovery, facilitate understanding, and make decisions. This project implements RAPTOR (Reconfigurable Advanced Platform for Transdisciplinary Open Research), a reconfigurable compute environment to address dynamic and diverse computing needs of science drivers??coastal resilience, sustainable environmental research, and systems biology.
The goal of RAPTOR is to increase research production by enhancing computing capabilities at Florida International University (FIU), both at the campus level and through participation in a resource-sharing federated distributed computing community. For that, RAPTOR integrates with the Chameleon Cloud Infrastructure for on-demand resource allocation and the Open Science Grid (OSG) for opportunistic preemptible resource sharing allocation. The result is a platform capable of connecting with a rapidly deployable sampling system that can assimilate and transmit data in real-time to facilitate actionable intelligence and drive adaptive environmental monitoring decisions, and respond as conditions change. The integration of knowledge, tools, and modes of computation proposed by RAPTOR builds upon the expertise of domain researchers, computer scientists, and IT practitioners towards a ?smart cyberinfrastructure? to foster and develop transdisciplinary approaches. RAPTOR not only introduces new computing modalities at FIU to support its researchers, but also benefits a broader federated community of researchers and scholars sharing resources through OSG and Chameleon Cloud.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Introduction
Florida International University (FIU) engages in trans-disciplinary research in environmental science and engineering (coastal environmental monitoring, freshwater quality analyses and ecotoxicological studies, water management and everglades restoration); extreme events research (disaster risk and resiliency analysis, hurricane loss and storm surge modeling, prediction, and mitigation); and computational and systems biology (including proteomics, genomics and connectomics). These important science applications are highly complex and dynamic systems (natural or human-built). The all rely on computation to support simulation, modeling, and analyses to enable discovery, facilitate understanding, and make predictions and decisions.
Intellectual Merit and Broder Impacts
In response to its diverse computational requirements of scientific computing applications, FIU implemented RAPTOR: a Reconfigurable Advanced Platform for Transdisciplinary Open Research, purpose-built to support high-performance computing (HPC), high-throughput computing (HTC), data-intensive, machine learning, and real-time on-demand computing applications. RAPTOR is a reconfigurable compute environment, supporting the dynamic provisioning of compute nodes between HPC/HTC and bare-metal environments. The Chameleon software provisions bare-metal nodes and provides researchers full control of the software stack. RAPTOR federates with the OSG and the Chameleon Cloud to share its compute resources in response to the CC* program requirements.
RAPTOR is supporting science drivers at FIU: (1) Scalable HPC Machine Learning Models for Mass Spectrometry based Omics: Results showed that the MPI and CUDA codebases were successfully compiled and executed on RAPTOR with minimal modification.
(2) AI/ML to Predict Sea Level Variability: RAPTOR’s HPC platform offers a significant advantage when testing models like PatchTST on large datasets. The reduction in compute time allowed for quicker iterations, making it an ideal choice for resource-intensive tasks. Future work, including hyperparameter tuning, will also be performed on RAPTOR to further optimize model performance. RAPTOR provides an ideal platform for testing new ML methods.
(3) Weather Research Model: Preliminary tests of the WRF Model execution on RAPTOR suggest promising results regarding the model's computing performance for high-resolution nests at a spatial resolution of 1km in an inner domain of 500 x 500 km centered in South Florida.
(4) Stochastic storm simulation for Florida Public Hurricane Loss Model: The FPHLM estimates loss cost from hurricane events for residential property. The model requires more than 140,000 synthetic storms to be completed in order to estimate the loss. RAPTOR used the OSG to execute the FPHLM model, resulting in a reduction in compute time from 3 months to 2 weeks.
RAPTOR, with its OSG federation OSG, is providing core hours to the following fields of science: Physics (275, 704), Astrophysics (171,320), Chemistry (68,057), Evolutionary Biology (35,249), Computer and Information Sciences (5,528), Mathematics (1,668), Research Computing (1,603), Gravitational Physics (783), Chemical Engineering (126), and Nuclear Physics (2).
With support from REU funding, RAPTOR supported two undergraduate students. They were were actively involved in gaining practical experience under the mentorship of the IT practitioners, and research experience from the PI and Co-PIs. RAPTOR also supported the research of three graduate students under the supervision of the PI and Co-PIs.
Summary-Conclusion
RAPTOR has been successfully implemented. The stakeholders of RAPTOR plan to build upon the project’s success to continue increasing FIU’s research production. For example, EnviStor: A Repository for Supporting Collaborative Interdisciplinary Research on South Florida's Built and Natural Environments, is a CC* Storage award (#2322308) that will create a centrally managed PB-scale storage system that will provide much-needed storage capabilities to RAPTOR, FIU, and the scientific community of collaborating institutions.
RAPTOR has fostered collaboration between the Knight Foundation School of Computing and Information Sciences (KFSCIS), the Institute of Environment (IoE), the Division of IT, and the Office of Research and Economic Development (ORED). Opportunities are being explored to evolve RAPTOR and integrate it into FIU’s strategic plans for research.
Last Modified: 01/29/2025
Modified by: Jason X Liu
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