Cornell Leads New NSF Federated Cloud Project

November 3, 2015

ITHACA, N.Y., Nov. 3 — Cornell University will lead a five-year, $5 million project sponsored by the National Science Foundation (NSF) to build a federated cloud comprised of data infrastructure building blocks (DIBBs) designed to support scientists and engineers requiring flexible workflows and analysis tools for large-scale data sets, known as the Aristotle Cloud Federation.

The federated cloud will be deployed at Cornell University (CU), the University at Buffalo (UB), and the University of California, Santa Barbara (UCSB) and shared by seven science teams with over forty global collaborators.

David Lifka, Director of the Cornell University Center for Advanced Computing (CAC) will lead the project with colleagues Tom Furlani, Director of the UB Center for Computational Research, and Rich Wolski, Professor of Computer Science at UCSB.

Initial users of the cloud federation—earth and atmospheric sciences, finance, chemistry, astronomy, civil engineering, genomics, and food science—were selected based on the diversity of their data analysis requirements and cloud usage modalities. Their use cases will demonstrate the value of sharing resources and data across institutional boundaries. The overarching goal is optimizing “time to science”—the actual time it takes a researcher to obtain their scientific results. The elasticity provided by sharing resources means researchers don’t have to wait for local resources to become available to get their science started.

Metrics provided by UB’s XDMoD (XD Metrics on Demand) and UCSB’s QBETS (Queue Bounds Estimation Time Series) will enable researchers and administrators to make informed decisions about when to use federated resources outside their institutions.

“Cloud-based systems are rapidly becoming a key component in the support of research programs in academe and industry. By adding cloud metrics to XDMoD, researchers and senior leaders will be able to obtain detailed operational metrics of cloud systems in order to improve the efficiency of jobs run on the cloud, as well as measure overall cloud performance,” said Furlani. “Efficient use of federated clouds requires the ability to make predictions about where a workload will run best,” added Wolski. “Using XDMoD data and cloud-embedded performance monitors, QBETS will make it possible to predict the effects of federated work-sharing policies on user experience, both in the DIBBs cloud and in the Amazon Web Services (AWS) Cloud.”

“The goal of the Aristotle Cloud Federation is to develop a federated cloud model that encourages and rewards institutions for sharing large-scale data analysis resources that can be expanded internally with common, incremental building blocks and externally through meaningful collaborations with other institutions, commercial clouds, and NSF cloud resources,” said project PI Lifka. The project name—Aristotle—was chosen because Aristotle’s concept “the whole is greater than the sum of its parts” reflects the multi-institutional synergy and collaborations that the federation aspires to create.

The project will implement a new allocations and accounting model that will allow institutional administrators to track utilization across federated sites and use this data as an exchange mechanism between partner sites. This data will demonstrate the potential benefits of sharing institutional resources such as deploying local infrastructure that is right-sized for steady state usage rather than irregular peak loads.

Federation components, documentation, and best practices developed in this grant will be provided to the national community with the information necessary to create customized Virtual Machine instances, leverage resources at federated sites, burst to AWS, access, move, and share large-scale data, and deploy new cloud federations.

Cloud provider AWS will collaborate with the federation developers and scientists. “We are excited to work with the Aristotle team to provide cost-effective and scalable infrastructure that helps accelerate the time to science,” said Jamie Kinney, Senior Manager Scientific Computing, Amazon Web Services, Inc.

Scientists will use the federation to solve data challenges. “We plan to use Aristotle to exploit cloud-based parallelism and perform asynchronous, interactive analysis of complex environmental models that generate thousands of data files” said Patrick Reed, a Cornell University Civil and Environmental Engineering researcher who collaborates with University of North Carolina, Chapel Hill and Penn State engineers. “We will use Aristotle to enhance our decision management tools so that we can solve problems of increasing complexity such as helping cities to better manage their drought risks.”

According to Varun Chandola, a Computer Science and Engineering researcher at the UB, massive troves of geospatial data such as earth observation and climate simulations are scattered around the world within the data archives of researchers, government, and the private sector. Chandola is working with colleagues at NASA Ames, Oak Ridge National Laboratory, and several universities on streamlining the integrated visualization and analysis of geo-data. “We plan to use Aristotle to develop a cloud-based solution that allows researchers to seamlessly integrate heterogeneous geo-data from a variety of sources into a cloud-based analysis engine,” Chandola said.

“Research scientists and their collaborators are gathering sensor data and scientific images to optimize food productivity and security,” said Kate McCurdy, Director of the Sedgwick Reserve, a 5,896 acre nature reserve in California. “The scientists wish to combine this data with images taken by the general public and stored in commercial clouds,” she explained. “By combining campus clouds and commercial cloud services, the federated cloud approach implemented by Aristotle will provide the data structure we need.”

“This award continues NSF’s multi-year strategy to stimulate exploration of scalable and sustainable data infrastructure models that facilitate collaborative research across disciplines and institutions,” said Amy Walton, Program Director, Advanced Cyberinfrastructure Division, NSF. “By experimenting with cloud usage metrics, collaborating with a commercial cloud vendor, and exploring pricing/trading allocation mechanisms, the project will provide valuable information about how the innovations work in a range of situations, and how this ‘market approach’ integrates within the larger research ecosystem.”

“Sharing cloud computing and storage assets between institutions and bursting to commercial clouds when appropriate is definitely a model worth a serious trial,” said Robert A. Buhrman, Senior Vice Provost for Research at Cornell. “Creating federated clouds has the potential to increase multi-institutional and multi-disciplinary research collaborations, enhance data-driven insights, and reduce capital expenditures.”

Source: Cornell University Center for Advanced Computing

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

ISC 2024 Takeaways: Love for Top500, Extending HPC Systems, and Media Bashing

May 23, 2024

The ISC High Performance show is typically about time-to-science, but breakout sessions also focused on Europe's tech sovereignty, server infrastructure, storage, throughput, and new computing technologies. This round Read more…

HPC Pioneer Gordon Bell Passed Away

May 22, 2024

Legendary computer scientist Gordon Bell passed away last Friday at his home in Coronado, CA. He was 89. The New York Times has a nice tribute piece. A long-time pioneer with Digital Equipment Corp, he pushed hard for de Read more…

ISC 2024 — A Few Quantum Gems and Slides from a Packed QC Agenda

May 22, 2024

If you were looking for quantum computing content, ISC 2024 was a good place to be last week — there were around 20 quantum computing related sessions. QC even earned a slide in Kathy Yelick’s opening keynote — Bey Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Core42 Is Building Its 172 Million-core AI Supercomputer in Texas

May 20, 2024

UAE-based Core42 is building an AI supercomputer with 172 million cores which will become operational later this year. The system, Condor Galaxy 3, was announced earlier this year and will have 192 nodes with Cerebras Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's latest weapon in the AI battle with GPU maker Nvidia and clou Read more…

ISC 2024 Takeaways: Love for Top500, Extending HPC Systems, and Media Bashing

May 23, 2024

The ISC High Performance show is typically about time-to-science, but breakout sessions also focused on Europe's tech sovereignty, server infrastructure, storag Read more…

ISC 2024 — A Few Quantum Gems and Slides from a Packed QC Agenda

May 22, 2024

If you were looking for quantum computing content, ISC 2024 was a good place to be last week — there were around 20 quantum computing related sessions. QC eve Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Europe’s Race towards Quantum-HPC Integration and Quantum Advantage

May 16, 2024

What an interesting panel, Quantum Advantage — Where are We and What is Needed? While the panelists looked slightly weary — their’s was, after all, one of Read more…

The Future of AI in Science

May 15, 2024

AI is one of the most transformative and valuable scientific tools ever developed. By harnessing vast amounts of data and computational power, AI systems can un Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

ISC 2024 Keynote: High-precision Computing Will Be a Foundation for AI Models

May 15, 2024

Some scientific computing applications cannot sacrifice accuracy and will always require high-precision computing. Therefore, conventional high-performance c Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

Leading Solution Providers

Contributors

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

The NASA Black Hole Plunge

May 7, 2024

We have all thought about it. No one has done it, but now, thanks to HPC, we see what it looks like. Hold on to your feet because NASA has released videos of wh Read more…

Intel Plans Falcon Shores 2 GPU Supercomputing Chip for 2026  

August 8, 2023

Intel is planning to onboard a new version of the Falcon Shores chip in 2026, which is code-named Falcon Shores 2. The new product was announced by CEO Pat Gel Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

How the Chip Industry is Helping a Battery Company

May 8, 2024

Chip companies, once seen as engineering pure plays, are now at the center of geopolitical intrigue. Chip manufacturing firms, especially TSMC and Intel, have b Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire