Three questions with a new staff member! Aloha, Katrina!
Katrina hails from Kāne’ohe, Hawai’i where she was born and raised. She recently graduated from the University of Hawai’i at Mānoa with an M.S. in Computer Science and is now with ESnet’s Software Engineering Management and Analysis Group. Katrina loves her island life and enjoys dancing hula, hiking, and going to the beach. She also loves both playing and making video games in her spare time.
What brought you to ESnet?
During my time as a Research Assistant at UH Mānoa, I had the opportunity to work with some of ESnet’s team members and I really admired both the work they did as well as the work culture they were a part of. When I heard there were openings at ESnet, I jumped at the chance to continue working with such awesome people!
What is the most exciting thing going on in your field right now?
In recent years, Data Visualization has become more popular with the general public, being shared through social media and used by the masses instead of only scientists and analysts. As a result, we are seeing really creative and interesting ways of showing data beyond the standard charts. Also, the integration of machine learning to allow us to easily visualize large amounts of data is really exciting.
What book would you recommend?
If you like Fantasy Fiction, the Sword of Truth series by Terry Goodkind is great, but definitely a time commitment. I also just started reading The Windup Girl.
Across the physical sciences, new instruments and capabilities are continuing a relentless growth in data production and need for high speed networking and analysis resources.
ESnet stays on-top of these trends via the Network Requirements Review process, which for the past 15 years has been a remarkable and useful collaboration between the DOE Office of Advanced Supercomputing Research (ASCR), ESnet and science programs across the DOE Office of Science.
The latest Network Requirements Review for the Office of Science High Energy Physics program office (HEP) is now available — among many other findings, this review confirms that the exponential growth of scientific data generation will continue unabated as we proceed into what may well be a new golden age for high energy physics research. Some samples include:
⇾ The upcoming High Luminosity era for the Large Hadron Collider (beyond 2027, or Run-4) will require multi-Tbps network speeds to support globally dispersed “Tier 1” HPC resources. Scientists will use the LHC to uncover how the Higgs-Boson interacts and gives mass to other particles, and explore emerging evidence for particle behaviors not explained by current physics models. Each data-taking year, the experiments, ATLAS and CMS combined, are expected to accumulate roughly 1 EB of new data and it is estimated that complete data set sizes may routinely exceed 100 PB.
⇾ Scientists at the Deep Underground Neutrino Experiment (DUNE) in South Dakota and at Fermilab in Illinois, will use high speed data transfer to identify supernova events, as part of ongoing measurement of neutrino interactions. Supernovae measured by DUNE will generate over 200TB of compressed data per event, and Research and Educational Networks (REN) must be able to supply highly reliable, predictable data transfer capabilities to provide telescope targeting data to global arrays.
⇾ The Cosmic Microwave Background, Stage 4 (CMB-S4) experiment will require data management and transfer capabilities in some of the most demanding locations on earth. Operating two observational locations, and multiple telescopes with a combined total of 500,000 cryogenically-cooled superconducting detectors at the South Pole and in the Chilean Atacama Desert, CMB-S4 will provide an unprecedented picture back into the start of the Universe. Operating for seven years in these conditions, 22 TB (~8 TB at the South Pole and ~14 TB in Chile) of data will be generated daily, leading to an accrual of 3 PB annually, and as much as 100 TB over the full program lifecycle.
Network Requirements Reviews analyze the current, near, and long-term needs of the HEP community, providing a network and data-centric understanding of the scientific process used by the researchers and scientists. These requirements reviews drive ESnet’s investments in new services and capabilities, and enable ESnet to build strong partnerships with Office of Science (SC) programs, PIs, and user facilities. More information on this ESnet requirements review process can be found here.
We would like to thank the 13 HEP projects, and all of the HEP & DOE Office of Science collaborators who generously gave of their time, expertise, and most importantly, their enthusiasm for the future of high energy physics, as part of creating this report.
We want to especially thank the entire Science Engagement team plus Kate Robinson, and Dale Carder with our Network Engineering group who all provided outstanding support and technical expertise.
High-speed intelligent Research and Educational Networks (RENs), such as the one we’re building as part of the ESnet 6 program, will require a greater ability to understand and manage traffic flows. One research program underway to provide this capability is the High Touch effort, a programmable, scalable, and expressive hardware and software solution that produces and analyzes per-packet telemetry information with nanosecond-accurate timing. Along with Zhang Liu, Bruce Mah, Yatish Kumar, and Chin Guok, I have just released a presentation for the Proceedings of the 2021 Virtual Meeting on Systems and Network Telemetry and Analytics, describing work underway to create a programmable, very high speed, packet monitoring, and telemetry capability as part of bringing High-Touch to life.
Fatema Bannat Wala with our Cyber Security team was recognized with the 2021 Zeek Community Champion award by Corelight! More information on the award and her work with Zeek can be found here.
Zeek is an open source network security monitoring software extensively used by ESnet. Zeek (formally called Bro) was initially developed by researchers at Berkeley Lab, and more information on ESnet’s use of Zeek can be found in Fatema’s October Light Bytes post.
Please meet our newest Network Operations Center Engineer, John Amerkhanian. John comes to us from Richmond, CA, and grew up locally in Albany, CA. He graduated from UC Berkeley in 2015 with a degree in Political Science.
What brought you to ESnet?
As a kid growing up in the Berkeley area, you always heard about how there is exciting research happening in the LBNL buildings up on the hill. When my friend got a job with ESnet in 2016, I knew I’d like to join them there someday. I’m very excited to support some of the best energy researchers in the world and can’t wait to see how they’re improving the ways we produce, consume, and store energy.
What is the most exciting thing going on in your field right now?
Without a doubt it’s the leaps and bounds made in computer processor development, these days you can get a processor that is a fraction of the size of a Pentium 4 with nearly double the processing power and very low energy usage. The computing applications for these processors in my field are very exciting.
In the previous post we discussed deploying ZoMbis (Zeek on Management based information system) for ESnet6’s management network to monitor the traffic traversing the network and to provide visibility into what’s happening on our management network. This blog post will discuss how we use traffic sinkholes, which are a way of redirecting traffic so that it can be captured and analyzed. As opposed to our usual passive data collection system (e.g., tapping or port mirroring), traffic is being actively redirected to network monitoring systems such as Zeek. Network sensors can then perform various levels of in-depth analysis on the traffic, which can help detect misconfigurations, identify hostile traffic, or even perform automated mitigations for certain attacks.
Sinkholes are an important tool in the arsenal of network operators—they support network cyber defense by providing a way to redirect packets sent to or from unallocated (so-called “bogon” addresses) or other unexpected IP addresses. Additionally, they can help protect against reconnaissance or vulnerability scanning. If an attack does slip through these defenses, the damage could be limited, or the malicious traffic could be analyzed by network defenders to determine the source and methods being used.
As part of the ESnet6 security architecture, a sinkhole service will be deployed on the production management network, to redirect internal management traffic as well as externally sourced internet traffic destined to the management network. Using the Border Gateway Protocol (BGP), the sinkholes will advertise routes to the destination gateway for IP ranges of the management network to redirect the traffic to the target sinkhole. In our network, the management plane address set fits within a “supernet” (a collection of subnets) which can then advertise the sinkhole address as a destination. We will use this advertised supernet to redirect all traffic from external sources on the Internet away from the management network and to the external sinkhole.
An internal sinkhole will also advertise this management supernet for “inside” resources, but in this case, legitimate traffic will have a more specific route for the destination and not go to the sinkhole. This way, only traffic destined to an invalid subnet will be redirected to the internal sinkhole. This design should be extremely useful in identifying possible misconfigurations or other unexpected behaviors in the ESnet6 management network. if everything is behaving as expected, we should never see any traffic to the catch-all destination of the sinkhole.
The following diagram, taken from a ZeekWeek 2020 presentation by ESnet security engineer Scott Campbell, shows the basic design of the two kinds of sinkholes:
In the external sinkhole conceptual diagram above, routers R1 and R2 will be advertising the management address ranges to external sources. If any traffic destined to the management network is received from the Internet, it will instead be redirected to the sinkhole.
The external use case is a bit simpler than the internal sinkhole, which is diagrammed below. In the latter case, there will be some legitimate connections, such as between two ESnet points of presence (POPs), or between a POP and our data center. Any unwanted, misconfigured, or hostile scanning traffic will end up in the internal sinkhole. Hence internal sinkholes can be thought of both as network “garbage cans” and intrusion sensors helping to detect changes in normal management traffic patterns.
The ESnet Security Team will use Zeek, to analyze traffic at the application level, for both types of sinkholes. The logs generated by Zeek will then be collected centrally and will provide useful insights into what kind of unwanted traffic is being directed at our management plane, both from internal or external sources, and help better protect ESnet6 from attackers.
The ESnet6 2021 Annual Status Review was a great success, and the Review Committee, led by DOE, concluded that the ESnet6 Project is being managed and executed well!
Given that the project’s budget, scope, and schedule were approved in February 2020, this was the first official Annual Status Review – and what a year it has been! The 2021 Review was a major milestone, allowing the Project to formally present the project performance over the past year and, consequently, during the COVID-19 pandemic. I continue to be amazed by the entire project team, and I felt very honored to be the one to introduce the astounding progress we made during an extremely challenging year. Not only that, it was all done while operating the current ESnet5 production network at the same time.
The project execution continued at full speed while some of us started carving out time over the past several months to prepare for the Review. Pulling together all of the information required, synthesizing it into a clear and concise set of briefings and documents, and presenting it to leaders in our field is a monumental task under any circumstances, but the pandemic made this especially difficult. However, the project team, backed by strong support across LBNL (Procurement, Project Management Office, Project Management Advisory Board members, and many others) made everything appear seamless. The impressive level of teamwork did not go unnoticed and was specifically mentioned repeatedly during the Closeout session. I am grateful for and proud of, all of the members of the team who contributed to this terrific success.
The Review Committee consisted of three Subcommittees (Technical, Cost & Schedule, Project Management & Environment, Safety & Health), all charged with answering a set of questions to determine if we were on schedule, achieving scope, within budget, and performing all tasks safely. The answer to every charge question: Yes! It was an all-encompassing couple of days, but we really couldn’t have asked for a better result. In short, there were no formal recommendations, so we’ll be considering how best to implement several of the Review Committee’s extremely helpful comments as we proceed onward. Our hard work, not only on the Review itself, paid off!
With the formal Review complete for the year, we’re all back to our daily project plan of execution, while keeping the network “lights on” in the process, of course.
Please welcome James Kafader to ESnet! James comes to us from Internet Archive (IA), where he worked on the Archive-It team, which develops and maintains a turnkey archiving platform. Archive-It partners with external institutions and national libraries to capture data on their behalf. It is essentially the project incubator at IA and focused on high-quality and large-scale archiving. The data collected by Archive-It represents about 30% of the available captures in the global wayback machine.
Question 1: What brought you to ESnet?
In 2020, I spent a lot of time thinking about the interconnectedness of natural systems, and how they relate to the earth’s climate. It strikes me that it’s imperative, as a planet and nation, to focus on reducing the impact of climate change in short order. This line of thinking led me to dedicate my time to science, which could have a positive impact on the global climate.
Question 2: What is the most exciting thing going on in your field right now?
This is a good question. I consider myself very much a generalist in terms of how I approach software development, as well as in my overall view of reality. My view of computational systems is very conservative as well — I like to understand the algorithms involved with any new technology as intimately as possible before selecting it for use. I’d say in many ways that the most exciting thing going on in my field is renewed interest in how large-scale systems affect equitability for their participants; that is, how the networks, systems, and structures that we build affect outcomes for each of us.
Question 3: What book would you recommend?
I recently read Breath by James Nestor. It was an engaging read and helped a lot with my mood and stability, if not the most scientifically accurate thing I’ve ever read. Another favorite is Difficult Conversations by Sheila Heen, Douglas Stone, and Bruce Patton.
5.5 Questions with Eli Dart (ESnet), C.S. Chang, and Michael Churchill (PPPL)
In 2025, when the International Thermonuclear Experimental Reactor (ITER) generates “first plasma”, it will be the culmination of almost 40 years of effort. First started in 1985, the project has grown to include the scientific talents of seven members (China, EU, India, Japan, Korea, Russia, and the US, with EU membership bringing the total to 35 countries) and if successful, will mark the first time that a large scale fusion reactor generates more thermal power than is used to heat isotopes of hydrogen gas to a plasma state.
ESnet is supporting this international scientific community as this dream of limitless, clean energy is pursued. When operational at full capacity, ITER will generate approximately a petabyte-per-day of data, much of which will need to be analyzed and fed back in near real-time to optimize the fusion reaction and manage distribution of data to a federated framework of geographically distributed “remote control rooms” or RCR. To prepare for this demanding ability to distribute both data and analytics, recently ESnet’s Eli Dart and the Princeton Plasma Physics Laboratory’s (PPPL) Michael Churchill and C.S. Chang were co-authors on a test exercise performed with collaborators at Pacific Northwest National Laboratory (PNNL), PPPL, Oak Ridge National Laboratory (ORNL), and with the Korean KREONET, KSTAR, National Fusion Research Institute, and the Ulsan National Institute of Science and Technology. This study (https://doi.org/10.1080/15361055.2020.1851073) successfully demonstrated the use of ESnet and the ScienceDMZ architecture as part of trans-Pacific large data transfer, and near real-time movie creation and analysis of the KSTAR electron cyclotron emission images, via links between multiple paths at high sustained speeds.
Q 1: This was a complex test, involving several sites and analytic workflows. Can you walk our readers through the end-to-end workflow?
Eli Dart: The data were streamed from a system at KSTAR, encoded into ADIOS format, streamed to PPPL, rendered into movie frames, and visualized at PPPL. One of the key attributes of this workflow is that it is a streaming workflow. Specifically, this means that the data passes through the workflow steps (encoding in ADIOS format, transfer, rendering movie frames, showing the movie) without being written to non-volatile storage. This allows for performance improvements, because no time is spent on storage I/O. It also removes the restriction of storage allocations from the operation of the workflow – only the final data products need to be stored (if desired).
Q 2: A big portion of this research supports the idea of federated, near real-time analysis of data. In order to make these data transfers performant, flexible, and adaptable enough to meet the requirements for a future ITER RCR, you had to carefully engineer and coordinate with many parties. What was the hardest part of this experiment, and what lessons does it offer ITER?
Eli Dart: It is really important to ensure that the network path is clean. By “clean” I mean that the network needs to provide loss-free IP service for the experiment traffic. Because the fusion research community is globally distributed, the data transfers cover long distances, which greatly magnifies the negative impact of packet loss on transfer performance. Test and measurement (using perfSONAR) is very important to ensure that the network is clean, as is operational excellence to ensure that problems are fixed quickly if they arise. KREONET is an example of a well-run production network – their operational excellence contributed significantly to the success of this effort.
Q 3: One of the issues you had to work around was a firewall at one institution. What was involved in working with their site security, and how should those working with Science DMZ work through these issues?
Eli Dart: Building and operating a Science DMZ involves a combination of technical and organizational work. Different institutions have different policies, and the need for different levels of assurance depending on the nature of the work being done on the Science DMZ. The key is to understand that security policy is there for a reason, and to work with the parties involved in the context that makes sense from their perspective. Then, it’s just a matter of working together to find a workable solution that preserves safety from a cybersecurity perspective and also allows the science mission to succeed.
Q 4: How did you build this collaboration and how did you keep everyone on the same page, any advice you can offer other experiments facing the same need to coordinate multi-national efforts?
Eli Dart: From my perspective, this result demonstrates the value of multi-institution, multi-disciplinary collaborations for achieving important scientific outcomes. Modern science is complex, and we are increasingly in a place where only teams can bring all the necessary expertise to bear on a complex problem. The members of this team have worked together in smaller groups on a variety of projects over the years – those relationships were very valuable in achieving this result.
Q 5: In the paper you present a model for a federated remote framework workflow. Looking beyond ITER, are there other applications you can see for the lessons learned from this experiment?
C.S. Chang: Lessons learned from this experiment can be applied to many other distributed scientific, industrial, and commercial applications which require collaborative data analysis and decision making. We do not need to look too far. Expensive scientific studies on exascale computers will most likely be collaborative efforts among geographically distributed scientists who want to analyze the simulation data and share/combine the findings in near-real-time for speedy scientific discovery and for steering of ongoing or next simulations. The lessons learned here can influence the remote collaboration workflow used in high energy physics, climate science, space physics, and others.
Q 5.5: What’s next? You mention quite a number of possible follow on activities in the paper? Which of these most interest you, and what might follow?
Michael Churchill: Continued work by this group has led to the recently developed open-source Python framework, DELTA, for streaming data from experiments to remote compute centers, using ADIOS for streaming over wide-area networks, and on the receiver side using asynchronous Message Passing Interface to do parallel processing of the data streams. We’ve used this for streaming data from KSTAR to the NERSC Cori supercomputer and completing a spectral analysis in parallel in less than 10 minutes, which normally in serial would take 12 hours. Frameworks such as this, enabling connecting experiments to remote high-performance computers, will open up the quality and quantity of analysis workflows that experimental scientists can run. It’s exciting to see how this can help accelerate the progress of science around the world.
Congratulations on your success! This is a significant step forward in building the data management capability that ITER will need.