But they don’t need these resources all the time.

Ideally, a scientist studying the properties of new materials for producing solar energy, for example, would be able to grab a “slice” of a high-bandwidth pipeline, set their workflow in motion, grab compute resources in the cloud and then release those resources, so they could be used by other researchers in different configurations.

At the RENCI/North Carolina research exhibit at SC11, three demonstrations by the RENCI networking research group and Duke University will use ORCA, the Open Resource Control Architecture, to bring together cyber resources from multiple providers as needed to accommodate a scientific workflow.

ORCA was developed by Duke computer science professor Jeff Chase and his students with funding from the National Science Foundation. It is one of the experimental control frameworks for the NSF’s Global Environments for Network Innovation (GENI) project. GENI is a virtual laboratory for networking experiments that will help researchers develop the tools and protocols that will define future internets. With funding from the Department of Energy Advanced Scientific Computing Research program and the NSF Software Development for Cyberinfrastructure program, researchers are adapting ORCA as an Infrastructure as a Service (IaaS) platform for serving the diverse needs of computational scientists.

The first demonstration will execute a scientific workflow by using ORCA to allocate a slice of computational resources from multiple cloud providers and bandwidth-provisioned network connections between provider sites. The workflow, managed by the Pegasus workflow management system, will use six serial applications, which will run on Condor clusters dynamically provisioned from clouds owned by RENCI in Chapel Hill, NC, and by Duke University in Durham, NC. The two clouds are connected by the Breakable Experimental Network (BEN), an experimental network that connects RENCI and its partner institutions at Duke, UNC-Chapel Hill and North Carolina State University.

A final large MPI application will run on several thousand processors on Hopper, a Cray Xe6 system at the National Energy Research Scientific Computing Center (NERSC) in Berkeley, CA.

ORCA will provision several network resources to move data across the continent, starting with BEN in North Carolina. From the southeastern U.S., the workflow will make its way to NERSC, first via the National Lambda Rail, then to the StarLight interconnect in Chicago, and finally via ESnet, the Energy Science Network, to NERSC.

“We will set up a collection of disparate resources in multiple clouds that never existed before and won’t exist once the job is completed,” said Ilia Baldine, director of the RENCI networking research group. “We plan to show that ORCA is an Infrastructure as a Service platform suitable for both GENI experimenters and computational scientists and that it is capable of provisioning resources as they are needed and then allowing them to return to their owners to be accessed by other users.”

The science: new materials for solar energy

The scientific job will be a simplified version of a workflow used to apply effective forward design strategies to the discovery of new materials for solar energy. In inverse design, scientists start with a set of desired electronic properties for a material and then search for the best structure. A major step in the process is the calculation of a particular property that occurs as part of the forward chain. The workflow will examine the electronic structure of moieties of Ruthenium (Ru) molecules and attempt to determine their total energy. Ruthenium can absorb light in the visible spectrum, which makes it a good candidate for a material used in cost-effective solar energy cells. The work is supported under U.S-DOE SciDAC-e award DE-FC02-06ER25764, “Enhancing Productivity of Materials Discovery Computations for Solar Fuels and Next Generation Photovoltaics.”

A related demonstration will use the ORCA framework to execute a Hadoop workflow on multiple clouds connected through bandwidth-provisioned network pipelines.  Hadoop is a software framework for data-intensive distributed applications. A third demonstration will take a closer look at a part of the first demonstration: the on-demand provisioning of computational infrastructure to stand up a Condor cluster in a networked cloud environment.

The demonstrations will take place in the RENCI booth (2942).  Demonstration times are:

• Monday, Nov. 14: 7 p.m. – 9 p.m.
• Tuesday, Nov. 15: 10:30 a.m. (demo 1), 11:30 a.m. (demo 2) and 1 p.m. (demo 3)
• Wednesday, Nov. 16: 10:30 a.m. (demo 1), 2 p.m. (demo 2) and 2:30 p.m. (demo 3)
• Thursday, Nov. 17: 10:30 a.m. – 12:30 p.m. (demos 1, 2 and 3)

ORCA was developed at the Duke University New Internet Computing Lab by computer science professor Jeff Chase and his students. RENCI and Duke are partners in a GENI project to evaluate ORCA as a future Internet control plane framework.

For more information:

ORCA/BEN website

Networked Clouds website

GENI Project website

RENCI website

CHAPEL HILL, NC, July 22, 2011–A R21 NIH exploratory/developmental research grant from the Agency for Healthcare Research and Quality (AHRQ) will enable RENCI and Duke University to develop a system that aggregates and visualizes historical medical data so doctors can use it to help them make the best possible treatment decisions for their patients.

AHRQ, a division of the U.S. Department of Health and Human Services, will provide $300,000 over two years to RENCI and Duke University Health System to develop VisualDecisionLinc, a software prototype that integrates historical patient data and comparative data from similar patients, all derived from electronic medical records (EMRs), into a decision support tool. The VisualDecisionLinc system hypothesizes that doctors will make better treatment decisions if they can quickly access and easily analyze data about similar patients and the effectiveness of various treatments.

The system uses data from the MindLinc EMR system developed at Duke University Medical Center. MindLinc-EMR is a widely used behavioral health EMR system containing data from more than 2.1 million patient encounters, making it the largest data warehouse of anonymous psychiatry data in the U.S. The AHRQ-funded work will build on an ongoing RENCI-Duke project and will focus on three key initiatives:

• Developing the best processes for selecting comparative populations. The researchers will use demographic information, case histories and diagnoses to help clinicians select comparative populations from the EMR that are most relevant to their patients.
• Creating a visual user interface to help in selecting the best treatment choices. Clinicians need to be able to find the important information in their datasets quickly and to view data in a way that is easy to analyze. Visualization and visual analytics techniques will be used to aggregate, view and interact with large volumes of patient data, and to help clinicians understand their data quickly.
• Evaluating the effectiveness of VisualDecisionLinc in preparation for a larger-scale research implementation.

“Our premise is straightforward,” said Ketan Mane, senior research informatics developer at RENCI, who is creating VisualDecisionLinc with Chris Bizon a RENCI senior research scientist, Phil Owen, RENCI IT developer, and Charles Schmitt, RENCI’s director of informatics. “The EMRs include massive amounts of patient data on diagnoses, medication, and treatment outcomes, but doctors don’t have time to analyze pages and pages of data in a spreadsheet format. We want to use information technology to resolve this information overload problem, while at the same time gathering insights about data characteristics for better decision support.”

The focus of the RENCI-Duke research project is to provide EMR data to clinicians in ways that are useful—for example, summaries of patients with similar medical profiles– and in a visual format that is easy to understand, said Mane, “so that the data can be used to support clinical decision-making at the point of care.”

The RENCI team will work with Dr. Kenneth Gersing, a psychiatrist and medical director of clinical informatics in the psychiatry department at Duke University, Dr. Ricardo Pietroban, vice chair of the department of surgery at Duke, and Bruce Burchett, an assistant professor of psychiatry at Duke. Drs. Ranga Krishnan and John Rush, dean and vice dean of clinical sciences at the Duke-NUS Graduate Medical School in Singapore, will serve as advisors to the project.

The Duke team linked with RENCI two years ago to assist in an ongoing effort to use electronic medical records to improve medical decision-making.

“The goal is to use EMRs to make the best treatment decisions possible and to improve patient outcomes,” said Gersing, who led the development of MindLinc-EMR. “If we can treat patients more effectively, it means fewer clinician visits, a better quality of life, and lower healthcare costs.”

For more information:

Feature story: Evidence-based medicine

Mindlinc Website

Visualization of the construction of Francesco a Folloni, Campania, Italy. What began as a class project will expand through the RENCI@Duke Applied Scientific and Information Visualization program.

DURHAM, NC–RENCI experts in visualization, visual analytics, and data mining and management will work with three Duke University research teams—one in the School of Medicine and two in art, art history and visual studies—on projects to improve treatments for prostate cancer and to document the evolution of historic places, artwork and art markets.

The projects are the first to be launched through the RENCI@Duke Faculty Engagement Program in Applied Scientific and Information Visualization, an effort to expand the use of visualization tools and technologies among Duke researchers.  The research teams will receive about $12,000 each from RENCI to support their work and will be expected to develop new research methods, models, applications or prototypes that can lead to larger projects supported by grant money.

The projects are:

• A Visualization Tool for Knowledge-Based Treatment Planning for Prostate Cancer.
  Joseph Lo, radiology

  Shiva Das, radiation oncology

  Vorakarn Chanyavanich, medical physics

Lo, Das and Chanyavanich will work with RENCI to develop a software tool that would allow clinicians to visualize and analyze a large dataset of prostate cancer cases in order to develop better treatment plans for patients. The research team will first develop a user interface for visualizing complex data, including 3D CT scans, 2D images, hand-drawn slice contours, volume rendered structure maps, and radiation fluence maps.
The visualization tool will draw on data from 500 prostate cancer cases at three institutions. CT scan data from new cases will be matched to similar information in the database and best matches will be used to develop treatment parameters. Those parameters will then guide the development of clinical-quality treatment plans.

RENCI will provide visualization resources, including its 13.5-foot-by-5-foot multi-touch visualization wall, and programming expertise to develop the user interface for the tool. RENCI experts also will render large, 3D volumetric datasets and offer advice on visualization, data mining and how to share data among institutions.

• Visualizing Historical Materials
  Caroline Bruzelius, art, art history and visual studies (AAHVS)

  Rachael Brady, Pratt School of Engineering and AAHVS

  Sheila Dillon, Mark Olson and Raquel Salvatella de Prada, AAHVS

  John Taormina, AAHVS and director, Visual Media Center

This project grew out of a class offered by the research team in 2009 in which students used digital visualization and mapping technologies to reconstruct works of art and historic places in 3D environments. The researchers will focus on three long-term projects:

• Creating a 3D relational database of ancient and medieval sculptures that links to the environments where the objects were originally displayed. The Nasher Museum at Duke and the Museum of Fine Arts in Boston are collaborators on the project.
• Reconstructing the history and development of Venice, Italy, through the development over time of its markets, bridges, administrative centers, and religions complexes. The project will start with a visual presentation of property acquisitions and development of the Dominican convent of Santi Giovanni e Paolo. The project is a collaboration with the University of Venice and the University of California at Merced.
• Continuation of a project with the Franciscan Order and convents of San Francesco a Folloni to visualize the construction and development of the Franciscan Churches of Campania in Florence, Italy. One of the researchers’ first goals will be to produce a laser scan of the interior of the Bascilia di San Lorenzo in order to precisely measure and analyze the building’s phases of construction.

RENCI’s role will include designing and implementing a database for 3D objects and their contexts, building a shared repository of assets (scanned documents, images, 3D models, maps), developing systems for data management and archival gallery publishing.

• Visualizing Art, Law and Markets
  Victoria Szabo:  art, art history, and visual studies (AAHVS) and program director, Information Science + Information Studies (ISIS)
  Hillary Coe Smith, Sandra van Ginhoven, Katherine De Vos Devine, AAVS

Launched last year, this project, which applies information visualization techniques to the study of emerging art markets, will be integrated into the information visualization program.  The project involves a team from the Duke Visual Studies Initiative (VSI) and seeks to create a collaborative infrastructure for analyzing market flows in early modern Europe using a variety of media incorporated into a database-driven, dynamic visualization tool. The tool will visualize influence networks and geographic market maps in order to understand how art markets emerged and grew. The research team plans to develop the tool so it will be useful to other VSI scholars.

About RENCI@Duke
RENCI@Duke opened in May 2008 and supports the use of visualization technology and advanced computational methods to explore issues in science, engineering, the arts, humanities and social sciences. Centrally located in the TelCom Building on Duke’s West Campus, the facility features a high-resolution multi-touch visualization wall, high-definition videoconferencing and networking capabilities, and staff specialists in visualization and informatics.

Your medical history—and the histories of patients with similar conditions—can help you.

That’s the foundation of a RENCI project to build an easy-to-use data analysis and visual dashboard to help doctors quickly determine the best treatment options for their patients.

The project teams Chris Bizon, RENCI senior research scientist, Ketan Mane, RENCI senior research informatics developer, and Charles Schmitt, RENCI’s director of informatics, with Dr. Kenneth Gersing, a psychiatrist and medical director of clinical informatics in the psychiatry department at Duke University Health Center, and Bruce Bruchett, a statistician in the Duke psychiatry department.

Gersing is the mastermind behind MindLinc, a tool for managing, evaluating and improving behavioral health treatment used at Duke and in medical clinics across the U.S. MindLinc includes anonymous emergency medical record (EMR) data accumulated from psychiatric patients over 20 years. As with any large data set, quickly analyzing data and translating the analysis into better patient care poses many challenges.

“The EMR data is there. It represents patients from multiple sites and across time,” said Mane. “We are developing a way to find important information in the data quickly and to view the results in a way that is easy and quick to understand at the point of care.  Doctors don’t have time to pore over pages of spreadsheets.”

Using the RENCI dashboard, a clinician can compare one patient’s medical history—for example, a 40-year-old male with depression—to the EMRs of other patients with similar conditions and histories and with similar demographic characteristics. From the dashboard on their computer screen, the clinician can examine graphs that show which medications have been most effective in treating similar patients.

The dashboard also presents graphs that map the effectiveness of different treatments over time and show the patient’s medical history over time, including doctor and emergency room visits. By examining the visual data, the clinician can draw conclusions about what triggered an emergency room visit or what medications are most likely to remain effective over time.

Click image for larger version

Above: RENCI’s clinical decision support dashboard analyzes treatment options for a hypothetical patient. The top left quadrant shows patient demographics, the effectiveness of different medications on patients with similar conditions, and the medication selected by the physician (in yellow). The middle section highlights and quantifies other medical conditions for the patient (in red) and the comparative population (in black). The graph at the bottom shows the patient’s response to medications over time. The blue extension of the graph gives doctors an intuitive view of how well the selected medication should work over time. The flow chart on the right is a medical treatment guideline, shown for reference. More parameters that can be manipulated in real time are available in a separate control panel.

The clinician also can change the parameters for comparisons as needed. If, for example, race has little relevance to a particular disease or to the effectiveness of a medication, the clinician can tell the system to disregard race when presenting the data. If the clinician suspects that time since the initial diagnosis might factor into the effectiveness of a treatment, that variable can be included in determining results.

“It’s similar to when you buy a book on Amazon.com,” said Gersing. “You buy a book and you see a note ‘people who liked this also liked …’ They are making predictions based on your past behavior.

“In our case, we’re not trying to get you to buy a book. The bottom line is more effective treatments, lower costs, and healthier people,” he said.

Gersing hooked up with RENCI through Ricardo Pietroban, vice chair of the department of surgery at Duke University Health Center, who knew Mane and his work and thought that RENCI’s informatics expertise could enhance Gersing’s efforts to use EMRs to improve medical decision-making.

“RENCI has been extremely helpful, not only by providing a visual interface but also the analytics,” said Gersing. “To use the data, you first need to pick out the important characteristics from the background noise.”

A prototype of the RENCI visual dashboard is almost complete and will be tested on the full MindLinc database later this year. The tool will then be tested in clinical settings in the psychiatric department at Duke Health Center and refined based on feedback from doctors and other clinicians.

Charles Schmitt, RENCI’s director of informatics, sees the project as an example of how RENCI can help the medical community translate research data into better patient care.

“There are guidelines that doctors follow when determining how to treat a patient, but they get dated pretty quickly,” said Schmitt. “Analytics and information visualization is an intuitive way to put data to use and have immediate results for the healthcare system.”

For more information see the Mindlinc website or the RENCI Evidence-based Medicine project page.

GENI is a multi-year effort to construct infrastructure for a large-scale experimental network that will enable the worldwide research community to test ideas and clean-slate designs in a range of technology areas including network design, distributed systems, and cyber-security. GENI will be built using a “spiral development” approach. Spiral 1 awards were announced Sept. 29 by BBN Technologies, the advanced technology solutions firm that is managing the project for the NSF. The awards, totaling  $12 million, fund research to build, integrate, and begin to operate the first prototypes of the GENI suite of network research infrastructure. The RENCI-Duke-Infinera project will receive $640,000 over three years.

GENI Spiral 1 focuses on ways to discover, schedule and control resources for large-scale research experiments and to measure capabilities. Multiple competing approaches are being funded to provide design insights for the evolving suite of experimental infrastructure.

The RENCI-Duke-Infinera winning proposal leverages the strengths of each organization. RENCI and Duke will use ORCA (Open Resource Control Architecture)—a software framework developed at Duke—to implement a model for the GENI control plane and deploy it on the newly implemented Breakable Experimental Network (BEN) in order to create a ‘GENI island’ – a miniature version of the future GENI testbed. BEN, a RENCI-managed, regional experimental network testbed designed to push the limits of networking research, links RENCI’s home office in Chapel Hill to sites at UNC Chapel Hill, Duke and NC State University.

Infinera will provide engineering support, integrating the Infinera DTN platform deployed on BEN to enable flexible provisioning of bandwidth. Based on large-scale photonic integration, the Infinera DTN delivers 100 Gigabits/second of optical capacity on a pair of photonic integrated circuits, enabling optical networks with unprecedented capacity, flexibility, speed, and intelligence. Infinera’s Bandwidth Virtualization™ feature enables a high level of flexibility and programmability in an optical platform for the wide-ranging research agenda planned for the GENI project and BEN.

“Infinera is delighted to support RENCI in exploring new architectures and experiments towards the development of the next-generation Internet,” said Infinera Chief Technology Officer Drew Perkins. “We are very excited that Infinera’s Bandwidth Virtualization capability is a near-perfect match with RENCI’s vision of a highly programmable optical layer.”

“BEN will serve as a miniature GENI prototype allowing us to experiment with different arrangements of network resources with special attention being paid to the provisioning of the optical substrate.” said Ilia Baldine, a senior network researcher at RENCI and principal investigator for the project. “Using BEN and with ORCA as a foundation, our plan is to deploy, demonstrate and evaluate the fundamental concepts and capabilities of GENI, such as end-to-end slicing in an optical network that connects heterogeneous computing and storage resources.”

Successive spirals of GENI funding will refine and extend the GENI suite in response to the research community’s evolving needs and interests.

“The GENI engagement is a key part of a regional initiative to investigate new structures for ‘virtualized’ server networks involving other RENCI partners,” said Jeff Chase, a professor of computer science at Duke and co-principal investigator on the project. “The next generation of researchers and educators will be able to tap into a programmable ‘cloud’ of servers, networks, and storage for research in networking, distributed computing, and other areas.”

For more on GENI, visit www.geni.net
For more on BEN, visit http://ben.renci.org

About RENCI
The Renaissance Computing Institute brings together computer and discipline scientists, artists, humanists, industry leaders, entrepreneurs, state leaders and educators for collaborations designed to reshape science, the economy, the state of North Carolina and the world. RENCI leverages its expertise and resources in leading edge computing, networking, visualization and data technologies to find solutions to previously intractable problems. Founded in 2004 as a major collaborative venture of Duke University, North Carolina State University, the University of North Carolina at Chapel Hill and the state of North Carolina, RENCI is a statewide virtual organization.  For more, see www.renci.org.

The open house runs from 3 p.m. – 5 p.m. in the new Duke-RENCI engagement center in the Office of Information Technology Telecommunications Building, 390 Science Drive, Suite 106 on Duke’s West Campus. Remarks by Duke University Provost Peter Lange will begin at 3:15 p.m.

The Duke engagement center features a 13-foot by 5-foot multi-touch visualization wall equipped with six high-definition projectors. Designed by engineers and visualization specialists at RENCI, the wall allows users to manipulate high-resolution data using both hands and multiple fingers for a more natural and intuitive data exploration experience. A demonstration of the wall’s capabilities will employ gesture and touch to navigate through a 3D virtual world using a new open source Croquet application called Cobalt being developed at Duke.

“The multi-touch visualization wall is intended to inspire researchers to try new methods of collaborating and interacting with data,” said Marilyn Lombardi, director of RENCI at Duke. “The wall is one way in which we plan to partner with faculty and students at Duke. The center will make it easier for the Duke community to work with RENCI on a wide range of projects of national and state focus.”

RENCI’s other engagement centers include two locations at UNC Chapel Hill (ITS Manning Building and the Health Sciences Library), RENCI at NC State on the Centennial Campus, and engagement centers at UNC Asheville, UNC Charlotte and East Carolina University in Greenville. RENCI’s anchor site is at the Europa Center office building in Chapel Hill.

RENCI…Catalyst for Innovation
The Renaissance Computing Institute brings together computer and discipline scientists, artists, humanists, industry leaders, entrepreneurs, state leaders and educators for collaborations designed to reshape science, the economy, the state of North Carolina and the world. RENCI leverages its expertise and resources in leading edge computing, networking and data technologies to ignite innovation and find solutions to previously intractable problems. Founded in 2004 as a major collaborative venture of Duke University, North Carolina State University, the University of North Carolina at Chapel Hill and the state of North Carolina, RENCI is a statewide virtual organization.  For more, see www.renci.org.

Kathy Kleiman, historian, computer programmer, telecommunications lawyer and head of the ENIAC Programmers Project, will speak about these women—whom ABC News referred to “Rosie the Riveter meets Bill Gates”—and about her efforts to produce a film documenting their unique and unsung accomplishments at the Fall 2008 Renaissance Computing Institute (RENCI) Distinguished Lecture.

Kleiman will speak on Thursday, Sept. 25, at the Bryan University Center on the campus of Duke University. The lecture, titled Shaking Up Computer History: Finding the Women of ENIAC, is co-sponsored by Duke University’s Office of the Provost and Office of Information and Technology, and by Women in Science and Engineering (WISE). The lecture hall will open at 11:30 a.m. and lunch will be available free of charge on a first-come, first-served basis. Kleiman’s talk will begin at noon.

Twenty years ago, Kleiman discovered the ENIAC programmers—Kathleen Mauchly Antonelli, Frances Bilas Spence, Frances “Betty” Snyder Holberton, Jean Jennings Bartik, Marlyn Wescoff Meltzer and Ruth Lichterman Teitelbaum—who programmed the first all-electronic programmable computer, the ENIAC. Kleiman devoted her undergraduate thesis to writing the ENIAC programmers’ missing chapter of computer history. A decade later she returned to the ENIAC women to capture their stories in their own voices. These powerful interviews form the basis of a full-length feature documentary Invisible Computers: The Story of the ENIAC Programmers. Some excerpts from the documentary will be shared at the lecture.

“Despite the outstanding success of ENIAC, these pioneering women were relegated to obscurity for over 50 years,” said Kleiman. “They performed their work under difficult conditions and taught themselves to program without programming manuals, classes or languages. The programmers performed a differential calculus equation critical to a secret WWII effort.”

The lecture will also reference the contributions made by several of the ENIAC programmers for decades after WWII, including seminal contributions to computer languages and standards.

Kleiman’s interests also extend to Internet governance issues. She is a founding member of the Internet Corporation for Assigned Names and Numbers (ICANN) and co-founder of its Noncommercial Users Constituency. Concerned about protecting noncommercial uses of the Internet, including political and personal speech, Kleiman speaks on issues of free speech, fair use and privacy issues in Internet forums around the world. She is a graduate from Harvard College and Boston University School of Law.

The one-hour lecture will be followed by a question and answer session. It is free and open to the general public, but attendees must register on the RENCI website. For more information and to register, please see Distinguished Lecture Series.

RENCI…Catalyst for Innovation
The Renaissance Computing Institute, a multi-institutional organization, brings together multidisciplinary experts and advanced technological capabilities to address pressing research issues and to find solutions to complex problems that affect the quality of life in North Carolina, our nation and the world. RENCI leverages its expertise and resources in leading edge computing, visualization, networking and data technologies to catalyze new collaborations and find solutions to previously intractable problems. Founded in 2004 as a major collaborative venture of Duke University, North Carolina State University, the University of North Carolina at Chapel Hill and the state of North Carolina, RENCI is a statewide virtual organization. For more, see www.renci.org.

The Infinera equipment will support RENCI’s research agenda for BEN, which serves as a testbed for experimentation with disruptive technologies such as enabling researcher access to the dark fiber, experiments with new transmission, modulation, and coding formats, interaction between the optical plane and the packet forwarding plane in the network, network virtualization and remote visualization of high-definition images on visualization walls using multiple optical wavelengths. BEN connects sites at Duke University, North Carolina State University, University of North Carolina at Chapel Hill and RENCI’s main office in Chapel Hill and enables university researchers to test their software and hardware by placing equipment at these sites. North Carolina’s MCNC, which manages the North Carolina Research and Education Network (NCREN), is also collaborating with RENCI on BEN and its offices in Research Triangle Park will connect to the network.

For its experiments using BEN, RENCI chose an Infinera Digital Optical Network because Infinera’s scalability, flexibility, and ease of operations make it an ideal platform for an advanced research network where researchers are experimenting with cutting-edge technologies and applications using large volumes of bandwidth and requiring frequent reconfiguration. Infinera’s Bandwidth Virtualization™ capabilities also enabled the joint GENI proposal.

GENI’s Vision for a “Sliceable, Programmable” Network
Last year, the NSF launched an ambitious multimillion dollar project, the Global Environment for Network Innovations (GENI), to design and construct a large-scale network that will enable the worldwide research community to test ideas and clean-slate designs in a range of technology areas including network design, distributed systems, and cyber-security. GENI’s aim is to forge new solutions to problems facing today’s Internet including inadequate security, reliability, manageability and scalability. RENCI, Duke University, and Infinera have collaborated on a proposal that envisages a sliceable and highly programmable optical network that connects diverse storage and computing resources to enable dynamic, reliable network provisioning. End-to-end slicing, which combines provisioning of edge computer and storage resources as well as core network resources, is considered one of the top technical risks by GENI.

The Infinera optical platform can deliver these advanced experimental features because of its innovative design. Based on large-scale photonic integrated circuits (PICs) which integrate more than 60 optical devices on a pair of chips, the Infinera system delivers bandwidth in increments of 100 Gigabits/second (Gb/s) and is scalable to 800 Gb/s today and more with Infinera’s next-generation ILS2 line system. The Infinera paradigm of Bandwidth Virtualization™ creates a “pool” of available bandwidth that can be deployed and reconfigured to deliver a wide range of optical services, from 1 Gb/s to 40 Gb/s services today, and 100 Gb/s services in the future. The Infinera PIC-based optical engine enables a highly flexible pool of bandwidth, which can be configured through service adapters to support a wide variety of services, with the entire architecture controllable with advanced GMPLS-powered network software.

The RENCI-Duke-Infinera proposal for GENI leverages the strengths of each organization. RENCI and Duke will use ORCA—a software framework developed at Duke—to implement a model for the GENI management plane and deploy it on BEN in order to create a ‘GENI island’ – a miniature version of the future GENI testbed. Infinera has used its innovative photonic integrated circuits and Bandwidth Virtualization™ feature to enable an unsurpassed level of flexibility and programmability in an optical platform for this project.

“We partnered with Infinera because we needed a scalable and flexible solution to accommodate our wide-ranging research agenda for BEN, and because we needed a product that would meet the demands for cutting-edge research necessary to participate in the GENI initiative,” said Ilia Baldine, manager of network research and infrastructure at RENCI. “Infinera’s solutions provided us with the best pathway to create a high-speed reconfigurable experimental network and to become a leader in developing the next generation of advanced research networks.”

“We are excited to partner with RENCI on its Breakable Experimental Network and on the GENI proposal,” said Infinera Chief Technology Officer Drew Perkins. “Leading-edge research like that envisaged by GENI will play a vital role in developing new technologies for a more powerful, flexible, scalable Internet that can support the applications of the future.”

The Infinera DTN is a Digital ROADM for long-haul and metro core networks, combining high-capacity DWDM transport, integrated digital bandwidth management, and GMPLS-powered service intelligence in a single platform.

For further information
Media:
Jeff Ferry
Infinera
Tel. +1-408-572-5213
jferry@infinera.com

Investors:
Bob Blair
Infinera
Tel. +1-408-716-4879
bblair@infinera.com

About RENCI
The Renaissance Computing Institute, a multi-institutional organization, brings together multidisciplinary experts and advanced technological capabilities to address pressing research issues and to find solutions to complex problems that affect the quality of life in North Carolina, our nation and the world. RENCI leverages its expertise and resources in leading edge computing, visualization, networking and data technologies to catalyze new collaborations and find solutions to previously intractable problems. Founded in 2004 as a major collaborative venture of Duke University, North Carolina State University, the University of North Carolina at Chapel Hill and the state of North Carolina, RENCI is a statewide virtual organization. For more, see www.renci.org.

About Infinera
Infinera provides Digital Optical Networking systems to telecommunications carriers worldwide. Infinera’s systems are unique in their use of a breakthrough semiconductor technology: the Photonic Integrated Circuit (PIC). Infinera’s systems and PIC technology are designed to provide optical networks with simpler and more flexible engineering and operations, faster time-to-service, and the ability to rapidly deliver differentiated services without reengineering their optical infrastructure. For more information, please visit www.infinera.com.

This press release contains certain forward-looking statements based on current expectations, forecasts and assumptions that involve risks and uncertainties. These statements are based on information available to Infinera as of the date hereof; and actual results could differ materially from those stated or implied, due to risks and uncertainties. Forward-looking statements include statements regarding Infinera’s expectations, beliefs, intentions or strategies regarding the future, such as the benefits and capabilities of our products and the Digital Optical Network’s architecture, that RENCI chose an Infinera Digital Optical Network because Infinera’s scalability, flexibility, and ease of operations make it an ideal platform for an advanced research network where researchers are experimenting with cutting-edge technologies and applications using large volumes of bandwidth and requiring frequent reconfiguration, that Infinera’s Bandwidth Virtualization™ capabilities enabled the joint GENI proposal; that the Infinera optical platform can deliver advanced experimental features because of its innovative design that based on large-scale photonic integrated circuits (PICs) which integrate more than 60 optical devices on a pair of chips, the Infinera system delivers bandwidth in increments of 100 Gigabits/second (Gb/s) and is scalable to 800 Gb/s; that the Infinera paradigm of Bandwidth Virtualization™ creates a “pool” of available bandwidth which can be deployed and reconfigured to deliver a wide range of optical services, from 1 Gb/s to 10 Gb/s services today, and 40 Gb/s and 100 Gb/s services in the future, that Infinera’s “programmable optical network” is based on the powerful PIC-based optical engine enabling a highly flexible pool of bandwidth that can be configured through service adapters to support a wide variety of services, and that Infinera has used its innovative integrated components and Bandwidth Virtualization™ feature to enable an unsurpassed level of flexibility and programmability in an optical platform for this project. Such forward-looking statements can be identified by forward-looking words such as “anticipated,” “believed,” “could,” “estimate,” “expect,” “intend,” “may,” “should,” “will,” and “would” or similar words. The risks and uncertainties that could cause our results to differ materially from those expressed or implied by such forward-looking statements include aggressive business tactics by our competitors, our dependence on a single product, our ability to protect our intellectual property, claims by others that we infringe their intellectual property, our manufacturing process is very complex, product performance problems we may encounter, our dependence on sole or limited source suppliers, our ability to respond to rapid technological changes, our ability to maintain effective internal controls, the ability of our contract manufacturers to perform as we expect, a new technology being developed that replaces the PIC as the dominant technology in optical networks, general political, economic and market conditions and events, including war, conflict or acts of terrorism; and other risks and uncertainties described more fully in our annual report on Form 10-K filed with the Securities and Exchange Commission on February 19, 2008, our public announcements and other documents filed with or furnished to the Securities and Exchange Commission. These statements are based on information available to us as of the date hereof and we disclaim any obligation to update the forward-looking statements included in this press release, whether as a result of new information, future events or otherwise.

Scientists from the three institutions will begin field operations on July 20 at Purchase Knob in the Great Smoky Mountains National Park in North Carolina. For 10 days, they will measure rainfall levels and how rainfall varies in size, velocity and intensity depending on elevation. The study, called the “NASA Precipitation Measurement Missions (PMM) Hydrometeorological Observations in the Southern Appalachians, NC,” should help researchers, government agencies, mountain communities and emergency workers understand how rainfall amounts—and water related problems such as floods—vary greatly due to the size, height and surface characteristics of the mountains.

“The highest rainfall accumulations in the eastern US after hurricane landfalls have been registered in the Appalachian Mountains in western North Carolina,” said Ana Barros, a professor in the civil and environmental engineering department at Duke University’s Pratt School of Engineering and lead researcher on the project. “How the terrain modifies the microphysical and dynamical processes that govern precipitation processes as tropical storms approach and pass over the mountains is not yet understood. This is also the case for convective storms generally, and it hampers our ability to forecast severe weather and anticipate and prepare for natural hazards.”

According to Barros, the field experiment in the Smokey Mountains is just one element of a comprehensive project that includes the development of high-resolution models for simulating summertime interaction between orography, or the average height of the land, and severe storms in western North Carolina.

“We plan to use the observations collected during the intense field observing period to evaluate the fidelity of existing models of mountain rain events and to test new ways to represent what happens with precipitation in the atmosphere and near the ground during major rainstorms in mountainous regions,” she said.

Central to the project will be RENCI’s Micro Rain Radar, a compact, vertically pointed radar that calculates and provides the rain rate, liquid water content, reflectivity and vertical fall velocity of precipitation in real time. The radar also predicts rain rates during severe storms. RENCI’s MRR, which has been used to determine at what level precipitation freezes during winter storms in order to help predict icing events, will be transported to the western mountains to measure how rain changes as it falls through the atmosphere. A high-speed camera will be attached to the MRR to provide visual observations of warm-weather precipitation.

The MRR system is particularly important to the experiment because it can provide detailed information on the size of raindrops at various heights above the ground surface, explained Barros. Other sensors, such as disdrometers and the high-speed camera can only provide observations at the point of measurement.  The additional information from the MRR will be critical to understanding how rainfall changes from the point where it is produced in clouds to where it hits the land surface, she said.

To study atmospheric conditions, the field study will use a data collection system called a tethersonde system, consisting of meteorological sensor packages, which will be launched from the ground up to a maximum altitude of around 500 meters (1,640 feet). The system will record the vertical profile of air pressure, temperature, relative humidity, wind speed and wind direction. The launches will be scheduled hourly throughout the two weeks, except under rainy or high wind conditions. The researchers will also take 50 radiosonde soundings using a balloon-borne instrument platform with radio transmitting capabilities to obtain a profile of the atmospheric boundary layer. Microphysical investigation of warm season precipitation will rely on a high-speed camera capable of recording 1,000 frames per second.

“This project was underway between Duke and UNC Asheville and RENCI was able to join the collaboration and bring the added observing tool of the MRR,” said Ken Galluppi, head of disaster research projects at RENCI. “This is a perfect example of how RENCI likes to work—collaborate with research teams to add value to their work.”

RENCI…Catalyst for Innovation
The Renaissance Computing Institute brings together computer and discipline scientists, artists, humanists, industry leaders, entrepreneurs, state leaders and educators for collaborations designed to reshape science, the economy, the state of North Carolina and the world. RENCI leverages its expertise and resources in leading edge computing, networking and data technologies to ignite innovation and find solutions to previously intractable problems. Founded in 2004 as a major collaborative venture of Duke University, North Carolina State University, the University of North Carolina at Chapel Hill and the state of North Carolina, RENCI is a statewide virtual organization.  For more, see www.renci.org.

“Thinking Through New Media: 2006 Graduate Student Conference” is sponsored by the Renaissance Computing Institute (RENCI), the Humanities, Arts, Sciences, and Technology Advanced Collaboratory (HASTAC), and Duke University Information Science and Information Studies (ISIS). Events will be held at the John Hope Franklin Center for Interdisciplinary and International Studies, 2204 Erwin Road, Durham, NC. The conference seeks to build a graduate student community around new media scholarship and to introduce participants to HASTAC (pronounced “haystack”), ISIS, and RENCI, a joint institute of the University of North Carolina at Chapel Hill, Duke and North Carolina State University.

Students traveling from outside the Triangle area may apply for scholarships to subsidize their travel and lodging expenses. All scholarship applications must be received by Sunday, May 7. To submit papers, students must email the paper title, one-page abstract and two-page CV to isis-info2duke.edu by Monday, May 1.

Conference details, including online registration, are available at http://isis.duke.edu/events/TTNM.