STFC-RAL-CR03 R61: After coming up in our presentation. There are a couple of videos.
STFC-RAL-CR03 R61: which I'm not there in previous slides,
STFC-RAL-CR03 R61: Again, because the parasites are confused. So I, actually, decor utilization, within the computing division, and I'll be talking about how we are
STFC-RAL-CR03 R61: Visualizing the data that comes from visual systems.
STFC-RAL-CR03 R61: But before that, I'd like to introduce my team. So, the visualization group, per se, sits within the ML and Vigilance group, and we are about
STFC-RAL-CR03 R61: 10 to 14 people within the organization, and daily.
STFC-RAL-CR03 R61: But then there are a range of collaborators with whom we work, right? That includes University of Manchester, SCFC, the Hartley Center.
STFC-RAL-CR03 R61: There are a bunch of people who have been working with us from Parale as well.
STFC-RAL-CR03 R61: Everything is our, SCC provider, we use services like CSP3, Associate, and image.
STFC-RAL-CR03 R61: Nvidia has been supporting a lot of visualization work. Essentially.
STFC-RAL-CR03 R61: bringing in the expertise, using their ominous platform. And we recently acquired, using a cluster, that's only meant for, visualization.
STFC-RAL-CR03 R61: We also work with, U.S. national labs, like Princeton, Argonne, and Oak Ridge.
STFC-RAL-CR03 R61: Their expertise lies within, like, large-scale simulation data, visualization, data streaming, and all.
STFC-RAL-CR03 R61: So, before, starting the talk, let me introduce what Fusion is.
STFC-RAL-CR03 R61: So, fusion is the, sun's power on Earth.
STFC-RAL-CR03 R61: It's a complex process, where light atomic nuclei, react, like hydrogen isotopes, to combine and form heavier, nuclei, and in that process, they kind of generate energy. And the idea is that we can capture energy, essentially used to power our homes.
STFC-RAL-CR03 R61: There are several, major global vision, initiatives.
STFC-RAL-CR03 R61: Peter in France is, one of the largest experimental, to come at our project, which got recently becoming, and that published document.
STFC-RAL-CR03 R61: Within UK, there is STEP that is coming up, which is, strength, a compact one. That's what, UK essentially excels in.
STFC-RAL-CR03 R61: There's a new site that's coming up close to West Burton, where we are building the new power plant, and the idea is that that will be a commercial plant connected to the grid.
STFC-RAL-CR03 R61: There is a hybrid facility in China called the CFPTR that is aimed at both research and commercialization.
STFC-RAL-CR03 R61: Oh.
STFC-RAL-CR03 R61: So, fusion, is hard, people say.
STFC-RAL-CR03 R61: But why it is hot? The reason is that it requires temperatures that are hotter than the core of the sun, at Earth, which is a bit difficult. So, the traditional tokamats use things called plasma confinement, using magnetic field or lasers.
STFC-RAL-CR03 R61: Which is an extremely complex process.
STFC-RAL-CR03 R61: And, I mean, the reactors itself are supposed to operate under extreme physical, thermal, and material stresses, which makes it even more hard, to make the machine operate.
STFC-RAL-CR03 R61: And in order to, we could work.
STFC-RAL-CR03 R61: There is the multidisciplinary aspect of region research, and this involves people working from different backgrounds. That varies from plasma physics, material science, superconducting magnets, diagnostics, engineering design control systems.
STFC-RAL-CR03 R61: And, the idea is that they should be working closely, if they are making the idea is to bring everything into place. So integration across these domains is, very critical.
STFC-RAL-CR03 R61: So the motivation of, the work that we do is, again, the PDM itself is a very data-intensive, problem, and that makes it hard to comprehend because of several data sources. So, bringing on to the three challenges, the first challenge is,
STFC-RAL-CR03 R61: a data challenge. Like, how do we integrate data center?
STFC-RAL-CR03 R61: And move from raw data to usable information, because there are so many experimental facilities, so when people are being in simulation areas.
STFC-RAL-CR03 R61: Working together to address this problem.
STFC-RAL-CR03 R61: So we're dealing with, like, multi-domain data. This is, like, a diverse data that, essentially comes into play.
STFC-RAL-CR03 R61: The data mainly ranges in four categories,
STFC-RAL-CR03 R61: One is, engineering care models. These are, like, the, engineering design, the blueprint we have our plans for us to come at.
STFC-RAL-CR03 R61: Please send me massage.
STFC-RAL-CR03 R61: you think of, building the entire facility. An example is, Peter's 20 kilometric model, and this is just a parametric model.
STFC-RAL-CR03 R61: Once you bring it to visualization, you are dealing with, like, trillions of primers, which makes it a very difficult task to visualize.
STFC-RAL-CR03 R61: And this data essentially relies on a system called SPRM, which is used by design industry for managing the design.
STFC-RAL-CR03 R61: Another category is the diagnostic data, which is the data that is produced by the machine. So, experimentalists, working here, dealing with certain data.
STFC-RAL-CR03 R61: should be well aware of how the diagnostic data looks like. These can be time series, time sensor data, 0B probes, 1B probes, 2B, 3D emitting data. These are essentially the sensors that are sitting within the machine, meant for machine operations, and the way,
STFC-RAL-CR03 R61: To operate the machine, and what comes out of the machine in terms of diagnostics.
STFC-RAL-CR03 R61: So, for the ETA project, it's expected that it will be producing raw data of up to a petabyte per year.
STFC-RAL-CR03 R61: So there are challenges in terms of processing that data, storing that data, and again, it's, machine isn't producing that much of data. The question comes, like, how the data is going to be stored? Because this much of storage is, like, very, very hard to achieve, can be expensive.
STFC-RAL-CR03 R61: The third aspect is the simulation data, which involves multi-physics models, models like MSG, aeropinetics. They also range in terms of petabytes, when it comes to spatial temporal data.
STFC-RAL-CR03 R61: to generate simulations, devices like, HPC value, that kind of are spread all across the UK. At UK, yeah, essentially, within the UK, we need specific leads operated by Dirac.
STFC-RAL-CR03 R61: So, Cables has one execution facility called FCXP3. Durant has one, called Cosmo. There is some other AI which is coming in this room, and these are, like, different locations within UK that have these data sets.
STFC-RAL-CR03 R61: And beyond UK,
STFC-RAL-CR03 R61: we work very closely with US partners that have access to even larger compute. So, supercomputers like Cynthia, Summit, we kind of utilize those systems to scale our simulations.
STFC-RAL-CR03 R61: And there, we deal with data science operations, high evolution.
STFC-RAL-CR03 R61: So it's expected that, once ETAL is operational, the simulation data, per se, would be roughly 2 petabytes per day.
STFC-RAL-CR03 R61: Which, again, is a challenge to process the data, store it.
STFC-RAL-CR03 R61: The third aspect is, the final one, the fourth one is, AIM data, and this includes data that comes from survey models, predictive analytics, analytics, anomaly detections, and these are, like, the models that are kind of trained on simulation diagnostic, and DNA models.
STFC-RAL-CR03 R61: But they still be a great block of data. So, to deal with these kind of models, the challenge is,
STFC-RAL-CR03 R61: Not the storage, but the compute.
STFC-RAL-CR03 R61: And… That brings me to the second challenge, that we are dealing with, this range of data errors.
STFC-RAL-CR03 R61: So we are processing what is the best way to represent him, how to generate meaningful experiences,
STFC-RAL-CR03 R61: Because, these data can be represented, in different fashion, and that can be for different, industries, which ranging from science, the scientists who are kind of looking at the data in terms of new discoveries.
STFC-RAL-CR03 R61: co-creation, so teams like science and engineering, or engineering and diagnostics, science and diagnostics, they like to kind of explore data together, so, again, telling them how to represent it.
STFC-RAL-CR03 R61: Dashboards is another way, like, how to design the dashboards to, essentially visualize the number of sensors and the kind of data streams that we are dealing with, ranges from, about 1,000 to 2,000 sensors at the moment.
STFC-RAL-CR03 R61: But in terms of user, the amount of sensor is going to extend up to 10,000
STFC-RAL-CR03 R61: There is also a faculty utilization, yeah, we are,
STFC-RAL-CR03 R61: It's meant for, general data consumption, and also for outreach.
STFC-RAL-CR03 R61: So.
STFC-RAL-CR03 R61: The question here is, like, we want data to flow in the public school databases that not just support, exploration, but also meaningful insight, which is used by science communicable actions, like population and engagement, that is required for communication and training.
STFC-RAL-CR03 R61: Which leads me to the third challenge, the discovery challenge is deciding what to visualize and how to visualize.
STFC-RAL-CR03 R61: And the reason is that there are several different stakeholders with different needs that are looking at these data sets. And these stakeholders may range from scientists, engineers, operators, to the public or ministers, who are ready to fund the research, but they are
STFC-RAL-CR03 R61: interested in different aspects of data. So the challenge here is, like, how to take a set of data and make it different tasteful for different communities.
STFC-RAL-CR03 R61: So, in my part, you will see some examples of how we are taking complex data and bringing it for… mainly for public, and for operational teammaking.
STFC-RAL-CR03 R61: But the, major challenge is to address all these big challenges together.
STFC-RAL-CR03 R61: To bring in some sort of meaning.
STFC-RAL-CR03 R61: And which brings me to a new framework that, we are currently working on, so it's a work in progress.
STFC-RAL-CR03 R61: We call it PIXT Framework, which,
STFC-RAL-CR03 R61: and for future information utilization for experienced design. So we are kind of, coming from the design area and trying to address this problem of utilizing the data meant for stakeholders.
STFC-RAL-CR03 R61: Nope.
STFC-RAL-CR03 R61: So the 5XE framework is, designed to be a flexible and modular framework.
STFC-RAL-CR03 R61: Mainly aimed at building visualization workflows that might involvemently.
STFC-RAL-CR03 R61: The architecture itself is not related. It's adaptable to local tools and goals and users, because different organizations have different demands, different policies against or in favor of tool use, so we are keeping that flexible.
STFC-RAL-CR03 R61: It provides a shared visual design language, and bridges technical architectures with the stakeholder requirements. It also supports responsive and interoperative stakeholder visualization.
STFC-RAL-CR03 R61: So our primary, goal here is to, come from the end-user perspective and be sure to the visualization.
STFC-RAL-CR03 R61: This is how the framework loosely looks like.
STFC-RAL-CR03 R61: It's, again, designed for UKEA, but I don't see why it can't be extended to a facility like CERN, or any other facility that generates heterogeneous data.
STFC-RAL-CR03 R61: So it starts with,
STFC-RAL-CR03 R61: the UK facilities, so we've got several facilities, Mastio is the, research department, but we also have Chimera, we have Snow Liberty, which is, a newcom source for planting.
STFC-RAL-CR03 R61: We have HIVE, which is, again, an experimental facility where, we kind of test part of geochematics, not the entire fusion.
STFC-RAL-CR03 R61: These facilities, are kind of supported by, our science team, that handles, design, simulations, and essentially generate range of data that range from CAD design, something coming from engineering design team.
STFC-RAL-CR03 R61: Simulation data that is coming from simulation teams, or those who work in physics.
STFC-RAL-CR03 R61: Experimental or diagnostic data, which, essentially comes from the machine, or, AIML data.
STFC-RAL-CR03 R61: So what we do is we kind of ingest these, different sources of data by working closely with the stakeholders, who are responsible for data generation, and then, depending upon the specific type of data, we kind of post-process the data.
STFC-RAL-CR03 R61: So, canned apps require certain, application, processing? Like, for example, Aras Innovator, which is a PLM, by7, requires a different kind of processing, which takes the data within ELM and bring it to, us, which is,
STFC-RAL-CR03 R61: to a comment which he could recognize.
STFC-RAL-CR03 R61: simulation apps powered by VTK, because a lot of simulations are agro-VTK, or they generate the data that can be easily, represented using VTK.
STFC-RAL-CR03 R61: diagnostic applications, then we generate streams of data, sometimes live, sometimes offline, but it requires, like, post-processing. And the idea is to process the data from these sources and, integrate them to produce a unified format, called as OpenUSE.
STFC-RAL-CR03 R61: which is a format that is easy to visualize, and it's something that is, coming from the VFX industry, or, animation industry. So, OpenUSD format has been,
STFC-RAL-CR03 R61: here since about 15 to 20 years. The format itself was invented by Pixar. That was first using Prod Story 3, Prod Story 1, and it went back to Prod Story 3, and then we open sourced it. it's…
STFC-RAL-CR03 R61: An open format of representing complex data, that can be consumed by different visualization tools.
STFC-RAL-CR03 R61: So what we do is we use a range of processing apps to kind of convert the data to a single unified, format called Zofern UFC, which also acts as a single source of truth.
STFC-RAL-CR03 R61: And then, again, we work closely with stakeholders to come up with different experiences, and these experiences range from
STFC-RAL-CR03 R61: Reading photorealistic visualization, that is meant for general public or for scientific information. Immersive visualization, like we have, we have. I'll show you some use cases around it.
STFC-RAL-CR03 R61: Scientific visualizations, these are the object utilization that kind of essentially required or reach by scientific community for communication.
STFC-RAL-CR03 R61: And digital engineering workflows, that involve, like, the vertex or manufacturing power, consuming that data and essential decision-making.
STFC-RAL-CR03 R61: Sorry, it's gonna be an election.
STFC-RAL-CR03 R61: So, to support, the, ecosystem that I explained, we got
STFC-RAL-CR03 R61: virtualization team, as well as OBX Platform, which is a new cluster that has, I mean, that's undergoing its welcome at the moment.
STFC-RAL-CR03 R61: And that is aimed as, something, doing all this together. This particular platform is,
STFC-RAL-CR03 R61: a medium-sized cluster, having about 64 GPUs and 16 loans, and that's only in that visualization. So, the idea is to utilize the cluster for filming these experiences, representing complex data.
STFC-RAL-CR03 R61: And, helping us in delivering these experiences to, devices like laptops or mobile phones that don't have any good compute originalization power.
STFC-RAL-CR03 R61: So, this is another representation of, same, framework, but here the example shows, how different teams kind of collaborate, in bringing a unified, visualization. So, for example.
STFC-RAL-CR03 R61: Freedom research team, works in simulation and ML modeling, and they generate AI and simulation data.
STFC-RAL-CR03 R61: this engineering design team that utilize PLL for delivering CAD models, and they generate engineering design data, and then there's fusion operation teams.
STFC-RAL-CR03 R61: That do these experimental campaigns, and they generate operational data.
STFC-RAL-CR03 R61: And my team sits after that, which kind of closely works with these teams to understand their data, and we generate these visualization workflows, and our workflows arranged from different kinds of visualization and experience, and from advanced visualization to where we are to collaborate with transport.
STFC-RAL-CR03 R61: to interact with user experiences. And here, whatever,
STFC-RAL-CR03 R61: Data that's coming up gets converted to a information, which can be kind of utilized by the key stakeholders.
STFC-RAL-CR03 R61: And now that, information, which is super important, can be used for decision-making, and one set use cases that, that time decision-making leads to policies and decisions.
STFC-RAL-CR03 R61: But again, that's just one example. There could be a number of decisions involved. For example, someone sitting in an operational control room would like to consume this information, and do a decision making to offer it commercially.
STFC-RAL-CR03 R61: So, in this talk, I will show you a couple of, use cases, coming from our facilities, like Kaiga and Bastio.
STFC-RAL-CR03 R61: But before that, this is, again, another, Workflow,
STFC-RAL-CR03 R61: of the experience generation. So, again, these are a couple of slides which have these blog diagrams, and I'll quickly jump onto
STFC-RAL-CR03 R61: more visualizations. But our current workflow, looks like we work very closely with stakeholders, and we follow the design process, in which, the first part is gathering the requirement.
STFC-RAL-CR03 R61: It's like, what is it that they…
STFC-RAL-CR03 R61: stakeholders are interested in looking at in terms of complex data. And then comes the iterative design process, where we work closely with the stakeholders and the other
STFC-RAL-CR03 R61: operators and owners of the data to come up with a design and visualization, that grows in a creative fashion. So, I mean, it's something… it's working hard, something about working guide, it's something we should fix, or something which needs to be implemented in a different way.
STFC-RAL-CR03 R61: So that process goes on in loop until the final design is kind of
STFC-RAL-CR03 R61: approved by the stakeholder, and once it's approved, we kind of deliver the final experience. So that's, like, one of the service models we've got, in terms of
STFC-RAL-CR03 R61: delivering these experiences, and you can quickly catch that there's a lot of communication that is involved, and communication itself can act as a new kind of data, or knowledge. So.
STFC-RAL-CR03 R61: We are currently working on introducing co-pilot agents for, requirement gathering, knowledge capture, knowledge transformation, and workflow automation, such that the communication that's going on at the moment also gets captured by co-pilots, and we could reuse our workflows.
STFC-RAL-CR03 R61: So there is a project going on at the moment, that involves, co-pilots, having acting as a central communicator, and operating, part of it, of most of the workflows, where possible.
STFC-RAL-CR03 R61: And also, the agents, can lead for analytics, feedback, and engagement.
STFC-RAL-CR03 R61: But this is all about, utilization service, okay?
STFC-RAL-CR03 R61: so far, the framework has been, applied in different facilities within UKEA.
STFC-RAL-CR03 R61: I've got examples from Ashley and Chimera, but Liberty is a new facility that is coming up, and I was told that, you know, people are working in electronics. So Liberty is a new facility that has an electronic source, and the idea is that
STFC-RAL-CR03 R61: The mucos will be combated to, new materials, for discovery. Essentially to make what comes out of fusion.
STFC-RAL-CR03 R61: We've got different tool stacks at the moment, for data processing. We are using applications like PowerView, Blender, WearMask, which is our internal tool, Airflow and Galaxy for workflow integration and automation.
STFC-RAL-CR03 R61: For integration, Open University is, kind of considered as, the essential connector.
STFC-RAL-CR03 R61: We are utilizing platforms like NVIDIA Omniverse,
STFC-RAL-CR03 R61: and websites and dashboards for, visualization, per se. For AI co-pilots, currently, we are exploring different co-pilots that are
STFC-RAL-CR03 R61: They're out in the market.
STFC-RAL-CR03 R61: But because we are very closely tied to Microsoft, my team particularly is using Microsoft Copilots, although we are also trying to use, ChatGPT or OpenAI Copilot.
STFC-RAL-CR03 R61: For compute, there's a large-scale NVIDIA virtualization cluster that is, currently undergoing installation at the site, but then we have access to, more visualization facilities within UKEA and at Cambridge, at Durham, and at, the U.S. National Labs.
STFC-RAL-CR03 R61: So, what's Omniverse? Omniverse is,
STFC-RAL-CR03 R61: massively, extensible, software, which is a platform called 3D design, collaboration, and Simulation.
STFC-RAL-CR03 R61: The platform itself is very loadedly defined, where there is a central nuclear server, which acts as a central repository for collaboration, and that's where all the files and data get stored. So, think of it as OneDrive equivalent.
STFC-RAL-CR03 R61: And this,
STFC-RAL-CR03 R61: UPS kind of links to the Omniverse-specific applications that, can, be something which comes with Omniverse, like create for, I mean, visualize very complex things.
STFC-RAL-CR03 R61: Or it's also possible to build custom applications using extension tools, data laboring technology.
STFC-RAL-CR03 R61: So the platform itself is very, very, loosely designed, and there is a lot of scope of building the ecosystem, which we are currently working.
STFC-RAL-CR03 R61: So, using Nubius as a central server, it is possible to, push in more sources of data that can be intravenous in nature.
STFC-RAL-CR03 R61: But it's also possible to pull in data from Nucleus, which is, like, a single source, or OpenUSC, and…
STFC-RAL-CR03 R61: It's possible to generate brain-depth visualization that varies from photorealistic visualizations, rendering, complex engineering VFX workflows, or ARVR, things such as, using, Apple Vision or any sort of 3D glasses.
STFC-RAL-CR03 R61: For data exploration.
STFC-RAL-CR03 R61: so this is one such example of, Chimera digital building experience.
STFC-RAL-CR03 R61: Chimera is a… Chimera is a facility for, material testing, under freezing condition, and the idea is to test material under extreme thermal, mechanical, and electromagnetic stresses.
STFC-RAL-CR03 R61: The facility itself is kind of supported by simulation, and it generates, like, very large multiplic simulation data sets that range from petabyte to petabyte.
STFC-RAL-CR03 R61: And the workflow that you can see on the right
STFC-RAL-CR03 R61: uses, USD as a central source, where the simulation data goes through a range of, data processing steps.
STFC-RAL-CR03 R61: And the data gets pushed to USD. In the same way, the engineering CAD data goes through, manual data processing, and that gets pushed to
STFC-RAL-CR03 R61: USC. And here, the USC itself is, like, a free kind of format where, you can kind of merge different sources of data.
STFC-RAL-CR03 R61: And in non-destructive fashion. And once there is a central data source present, it's possible to kind of ingest that data, do data integration, intellectual exploration, collaboration.
STFC-RAL-CR03 R61: So one set output looks like this, where…
STFC-RAL-CR03 R61: the CAP data is kind of, superimposed with the simulation data, and then that leads to, like, these four different kinds of visualization, showing different quantities. So the one that is closest to you, in the front, is a photo-based visualization of the chimera block,
STFC-RAL-CR03 R61: which takes the, properties of the real materials, like copper alloys, or beryllium alloys, or tungsten alloys. So that's the visualization of how the actual property looks like.
STFC-RAL-CR03 R61: But the remaining three are, the representation of
STFC-RAL-CR03 R61: how stress or changes the property of the material, what happens when it comes to, like, providing peace or conditions? And, the last one is material displacement, which kind of deforms the material.
STFC-RAL-CR03 R61: And using the same source of data, it's possible to generate more
STFC-RAL-CR03 R61: Engaging visualization that can be, kind of, to the general public.
STFC-RAL-CR03 R61: So, what I showed in my previous slide, the same data set is, like, now consumed by a blender to generate
STFC-RAL-CR03 R61: This video.
STFC-RAL-CR03 R61: which looks like this. You are again looking at temperature and stress and, the time period, on how the data looks like.
STFC-RAL-CR03 R61: And this is, again, the similar visualization, where,
STFC-RAL-CR03 R61: We only visualize the data write of a single timestamp, which what you're seeing is,
STFC-RAL-CR03 R61: A great deal of fluid velocity within the chambera block.
STFC-RAL-CR03 R61: And this is, like, one of the largest known thermohydraulics simulations that has been conducted on this particular facility.
STFC-RAL-CR03 R61: Using the, frontier HDC.
STFC-RAL-CR03 R61: Oh, and I get… Took us quite a lot of effort to not just do the simulation.
STFC-RAL-CR03 R61: but to bring the data from, U.S, national facilities like Frontier to the UK, and then when we process it at Durham, then moved it to come to Cambridge, which is where, the visualization cluster is sitting.
STFC-RAL-CR03 R61: And then we are able to access data.
STFC-RAL-CR03 R61: This is another one,
STFC-RAL-CR03 R61: Which is the master view, document experience, and, what you're seeing is, a combination of, engineering cat data and the simulation data. So, the, structure of the document, which is, like,
STFC-RAL-CR03 R61: cut-down version of the actual acidity, which resides within UKEA. The plasma is coming from, joint, which is, MSG code for, generative plasma simulations, and essentially else.
STFC-RAL-CR03 R61: And it uses a similar process of integrating CAD materials and simulation data.
STFC-RAL-CR03 R61: To create a combined digital twin.
STFC-RAL-CR03 R61: once you have the vision to it, it's possible to do VR walkthroughs.
STFC-RAL-CR03 R61: Collaborative design, decision making, and it's also possible that
STFC-RAL-CR03 R61: any sort of changes can be quickly seen. So, for example, the simulation that you are seeing, it's using
STFC-RAL-CR03 R61: One of the meshes. But if the engineering team decides to change the mesh, it's possible to see if there will be any changes, or whether those changes can be communicated back to the other teams that rely on engineering data.
STFC-RAL-CR03 R61: So, this one is, one example, which I will explain, that uses, circulation data, essentially to integrate about 1,000 meticapis.
STFC-RAL-CR03 R61: processes it and combines it with, the FPX or the CAD models, of the facility.
STFC-RAL-CR03 R61: Within, and within the omniverse.
STFC-RAL-CR03 R61: And that's where we kind of assign the real materials, realistic materials to the resources to generate a visualization that looks like this, which is
STFC-RAL-CR03 R61: Do you have to speak to Nature?
STFC-RAL-CR03 R61: It's also possible to generate device alerts, which can be used for public in outreach.
STFC-RAL-CR03 R61: We also took a step to generate, time series animation of…
STFC-RAL-CR03 R61: How a data could help an experimentalist who is, kind of.
STFC-RAL-CR03 R61: trained at looking at camera data. So, what we did was we took the parameters of the actual camera, which is sitting at MassView. We modeled the virtual version of the camera and rendered the simulations in a way, that they appear very similar to the rear camera.
STFC-RAL-CR03 R61: So, experimentalists who are… are the first-line workers who are very used to, seeing the, real data that comes from the real camera can make informed decisions, to look at the transmission data in a similar way.
STFC-RAL-CR03 R61: And this is all the possible,
STFC-RAL-CR03 R61: just a single source, so again, we are not entering, or we are not generating large number of files, we are just ingesting the data from the central OpenUSC and generating…
STFC-RAL-CR03 R61: This is another example of…
STFC-RAL-CR03 R61: Master diameter material, what you are seeing on your left is a scientific visualization of,
STFC-RAL-CR03 R61: due to EDM and freaking retention, within the director block of Z programmat.
STFC-RAL-CR03 R61: Which, essentially, is a block of tension. But on your right, what you see is, when the same block gets irradiated, you see these tensets that build over time.
STFC-RAL-CR03 R61: And this is, again, a visualization, which is aimed for general public.
STFC-RAL-CR03 R61: That shows, how the stress is built up over the time, and how it kind of looks like in terms of equivalent time, which is what experimental style used to say.
STFC-RAL-CR03 R61: This one, is again an interesting example of immersive experience, where, we took the CAM model of mass view, and combined the, simulation data, which comes from, joint simulation, to create a 3D model that looks like this.
STFC-RAL-CR03 R61: And, we kind of, created a path for visualizing this data in AR and VR. So, if, anyone who has,
STFC-RAL-CR03 R61: smartphone, and if they, kind of scan this QR code, it will take you to our 3D viewer, where they can kind of explore this
STFC-RAL-CR03 R61: We model, the mobile phone.
STFC-RAL-CR03 R61: Oh.
STFC-RAL-CR03 R61: But if they press the button, which says view in here, they can also visualize the same module in real world, so the model kind of appears right in front of them.
STFC-RAL-CR03 R61: It's just, like, it can be quite engaging for,
STFC-RAL-CR03 R61: Public, decision makers, and it kind of…
STFC-RAL-CR03 R61: brings in, historian type, as we tonight.
STFC-RAL-CR03 R61: We are also working on, using this technology for building adaptive dashboards, such that, we can kind of,
STFC-RAL-CR03 R61: combine resources of the data and bring them to the control room operators. There was a talk that I delivered, early in the morning, in a conference,
STFC-RAL-CR03 R61: that talks about, kind of, using different sources of data, and helps me, controlling operations and building, the update dashboards using AI.
STFC-RAL-CR03 R61: This one is, a volumetric 3D representation of the data, so we've got a…
STFC-RAL-CR03 R61: 3D monitor itself, that,
STFC-RAL-CR03 R61: essentially, shows you the data in 3D without wearing any special glasses or any equipment.
STFC-RAL-CR03 R61: So this is one example.
STFC-RAL-CR03 R61: That, shows how a volumetric 3D looks like. The data can pop out from the same.
STFC-RAL-CR03 R61: So, nursing, the framework itself is aimed at providing these different experiences.
STFC-RAL-CR03 R61: That range from, again, digital twins, that range from photorealistic visualization, emotional experiences, scientific visualization, and digital engineering workflow.
STFC-RAL-CR03 R61: So, currently, we are… -Oh.
STFC-RAL-CR03 R61: working on, Omniverse applications for customization.
STFC-RAL-CR03 R61: We are trying to build a unified application, that incorporates most of our work through the automation tools. We are also working with our collaborators, at the University of Manchester.
STFC-RAL-CR03 R61: And the other departments in bringing in real-time robotics and manufacturing, integrating them.
STFC-RAL-CR03 R61: With the integrated, engineering team,
STFC-RAL-CR03 R61: There are some words going around interoperability with PLL payment external systems.
STFC-RAL-CR03 R61: Essentially bringing in the data from different vendors to a unified representation.
STFC-RAL-CR03 R61: The AI and simulation model embedding is also, underway. We have a new collaboration coming up, with ideas to bring in some sort of target models, to close the loop, between the, the experiments, the simulations, and the utilizations.
STFC-RAL-CR03 R61: Nope.
STFC-RAL-CR03 R61: There's also project going on, right in this library, on diagnostics for other integration.
STFC-RAL-CR03 R61: So, with that, I'd like my talk, and I'm open to, any questions that you have on my slides, or in general, we are… I think we're already open for collaboration. We are already collaborating with, SCFC partners, learning, from different,
STFC-RAL-CR03 R61: Departments or organizations are quite robust, quite keen to know your thoughts.
STFC-RAL-CR03 R61: Yes.
STFC-RAL-CR03 R61: Questions in the room? Yes, please, Chris.
STFC-RAL-CR03 R61: So, I have a question. I mean, I have a friend who worked on JetJet, okay, and of course, what he was saying, he was an experimentalist, and he was saying that we're constantly discovering new
STFC-RAL-CR03 R61: instabilities that had not been predicted, and then the theorists would work to try to actually model those and so on, because it was coming very much from the experimental. What you showed on Marsden, so regular and so on, and you didn't put the word discovery there, but can you discover
STFC-RAL-CR03 R61: new phenomena, such as instabilities from these simulations, or do they come more in from the experimental data? Yeah.
STFC-RAL-CR03 R61: Yeah, so that query are,
STFC-RAL-CR03 R61: So the… the fixed waves models,
STFC-RAL-CR03 R61: Because they rely on a set of equations, they will…
STFC-RAL-CR03 R61: I think will have limitations. So that's where our AI-enabled workflows are coming into picture. So we use, techniques such as FMO spins to kind of model these institability.
STFC-RAL-CR03 R61: that, not just rely on the raw experimental data, but also the physics-based model, because, I mean, a lot of these instabilities cannot be modeled using physics equations, but the combination of physics equations and ML can kind of bring in modeling, such instability.
STFC-RAL-CR03 R61: Yeah, there is, some work going on, which I haven't cover, but my capabilities are okay.
STFC-RAL-CR03 R61: What questions?
STFC-RAL-CR03 R61: Yes, sir.
STFC-RAL-CR03 R61: Is there any guidance on the accessibility?
STFC-RAL-CR03 R61: When, you know, we have the data chain.
STFC-RAL-CR03 R61: And we have the solid model.
STFC-RAL-CR03 R61: To avoid any potential data leak, or, you know, apart from login passwords.
STFC-RAL-CR03 R61: with any kind.
STFC-RAL-CR03 R61: I will build on the government, or that, or the very wrong guidance, like, how to access that information.
STFC-RAL-CR03 R61: Yeah, so, I mean, that kind of goes… Hello.
STFC-RAL-CR03 R61: Sort of beyond the work that my team does, but within computing.
STFC-RAL-CR03 R61: We have the team that is looking at the security vulnerabilities, and we keep on testing.
STFC-RAL-CR03 R61: the facilities inside. So there's a lot of guidance that is internal to UKEA. I'm not very sure about, the sources, maybe something from government or something from third party, but then we rely from different information from several sources.
STFC-RAL-CR03 R61: But we also test our internal systems.
STFC-RAL-CR03 R61: But that's, I think that's the difference between it that kind of, looks into it. Although I work quite closely
STFC-RAL-CR03 R61: But, security, and vulnerability, in terms of data is one area in which, like, we are kind of working on at the moment. The reason is that we kind of deal with, range of data, and the data is deciding at different locations. So,
STFC-RAL-CR03 R61: There is a new project called Science BMZ.
STFC-RAL-CR03 R61: Which is coming up, that is aimed at sharing the data in a secure fashion.
STFC-RAL-CR03 R61: So it's not… People are not restricted in terms of data sharing, but they are also secure.
STFC-RAL-CR03 R61: But that's a new product for some, with digital assets.
STFC-RAL-CR03 R61: Other question? Yes, please, Norman. Thank you for your book. Interesting to see how other fields tackle massive data problems as well. Two questions in mind. What… what is… what language is used for the
STFC-RAL-CR03 R61: simulations.
STFC-RAL-CR03 R61: The fundamental simulations, if you're simulating a plasma behavior, is that… like, which is that domain you have to know?
STFC-RAL-CR03 R61: Yeah, so that depends on the tools and the software that is used by the…
STFC-RAL-CR03 R61: simulation team. So, for example, as far as I know, I bought, people using Quotron, 2 C++, 2 Python.
STFC-RAL-CR03 R61: And that all varies. Funnily enough, I thought Ford cracked my finger in there. It was ancient, but still the fastest. Yeah, yeah. And there are,
STFC-RAL-CR03 R61: Some of the new implementations that have
STFC-RAL-CR03 R61: kind of implemented these simulations to utilize GPUs, that makes it even more faster. The other question was, you talked about 5XD as a framework.
STFC-RAL-CR03 R61: and NVIDIA's Omniverse platform.
STFC-RAL-CR03 R61: of these, does… do you access the NVIDIA platform through the 5XD framework, or are these two bits?
STFC-RAL-CR03 R61: work together, or have I misunderstood what you're doing? Yeah, so the 5-HT framework is a conceptual framework, it's a design framework.
STFC-RAL-CR03 R61: that aims at capturing the tools, like Omniverse, as well as people, the team that we work with, and the processes that we follow to build these experiences. So is it software, ultimately? The framework is… no, it's a design framework.
STFC-RAL-CR03 R61: So it kind of painted between the processes, but the Omniverse is an output that we use. Okay, so Omniverse is the software, and 5XD is the thing that
STFC-RAL-CR03 R61: creates the flow diagram. So that's the building block. So, for example, if any newcomer wants to start building these experiences, like, these are the blanks and spots they will have to fill in.
STFC-RAL-CR03 R61: in order to generate these experiences, where Omniverse acts as an enabler.
STFC-RAL-CR03 R61: So, for example, we are utilizing Omniverse, but another organization can, for example, there could be other tools, that might be more relevant to a different organization. What does ITER use at the moment?
STFC-RAL-CR03 R61: I'm not too sure, because ITER is still going through the design and customization. They must have simulations and visualizations.
STFC-RAL-CR03 R61: They have at least part of this problem.
STFC-RAL-CR03 R61: Yeah, so I… what I didn't show was, which is a simulation that was, done by, one of the groups, within the computing, that takes the, what I showed, the time there are kind of simulations between moves and necklace.
STFC-RAL-CR03 R61: But they have taken the block from ETA. So, again…
STFC-RAL-CR03 R61: We are working closely, but, we are essentially not,
STFC-RAL-CR03 R61: the ones that are building these tools for ITER,
STFC-RAL-CR03 R61: Either, again, it's a large organization, and again, there are a range of challenges, which, is like…
STFC-RAL-CR03 R61: Beyond what we can address.
STFC-RAL-CR03 R61: And so, Anthony said, I'm not too sure what they're doing.
STFC-RAL-CR03 R61: But again, we are working closely in different places.
STFC-RAL-CR03 R61: Okay, thank you.
STFC-RAL-CR03 R61: More questions, Tim?
STFC-RAL-CR03 R61: I'm just following on from the questions about, omnibus, the worry with using
STFC-RAL-CR03 R61: software from NVIDIA is that you get locked into their, their platform, their system,
STFC-RAL-CR03 R61: What… how dependent are you on that particular software? If they suddenly say, we're going to charge you lots of money for you to start using it? I mean, the… what they're doing is they are building the hybrid models where,
STFC-RAL-CR03 R61: Some of the tools and technologies around Omnibus are being open source, but Omnibus per se is a licensed model, and we have kind of applied the license to build tools and technology.
STFC-RAL-CR03 R61: But the central challenge that gets addressed by Omniverse, which is hard to, I mean, find out internally, is representing a massive amount of information, or visualizing a massive amount of information that can be utilized, or can be visualized using a set of GPUs.
STFC-RAL-CR03 R61: So NVIDIA, per se, is, like, the leader in terms of GPUs when it comes to visualization, and this is the software that, utilizes or harnesses the power of these GPUs for, representing massive data types.
STFC-RAL-CR03 R61: So it seems to be working well for us, and they are kind of operating in a hybrid model, where bits and pieces are open source, bits and pieces can be developed, and some part of it is kind of licensed.
STFC-RAL-CR03 R61: But, again, the… of…
STFC-RAL-CR03 R61: challenge, or the PR is already get logged in to their tools, but so does the PL software. If you are stuck to a vendor, you will be doing stuff to a vendor. KT is one tool which is used by the entire engineering design facility.
STFC-RAL-CR03 R61: There is, like, hard to find replacement. So in same fashion,
STFC-RAL-CR03 R61: And we certainly think that somehow it is kind of working for us. We are also exploring more ways to kind of build these experiences.
STFC-RAL-CR03 R61: That not just utilize Omniverse, per se, but they kind of take data from OpenUSD, which is an open format, that is not owned by ND. And then again, there can be a technology step originally designed that, and we do it on top of OpenUSD. That's what other vendors are doing.
STFC-RAL-CR03 R61: per se, when it comes to data visualization. But again, we are a small team, so we are focused on using Omniverse.
STFC-RAL-CR03 R61: Are there more questions from the room? I have a question regarding the simulation. I noticed that the simulation data seemed to be on several orders, and a few orders of magnitude larger.
STFC-RAL-CR03 R61: And the other sources of data.
STFC-RAL-CR03 R61: So, I was curious what… what is the reason for that, whether it is statistics, or the description of the systems, or which is the main contributor to this large…
STFC-RAL-CR03 R61: data, so, simulation data. I mean, it's the fidelity which, is important, so until we, kind of, go to high fidelity.
STFC-RAL-CR03 R61: That's the main horizontal requirement of doing these simulations.
STFC-RAL-CR03 R61: So the data transfer can be, huge in terms of, what you see.
STFC-RAL-CR03 R61: Comparing it to start models, other sources of data.
STFC-RAL-CR03 R61: And that's because the data, per se, is, first of all, 3D in nature. It's not just surfaces or not just 3D plots. The data is articating the entire volume. And in order to see these minor perturbations, like turbulence or L, it has to be, kind of, simulated at very high resolution.
STFC-RAL-CR03 R61: So the visualization that I showed were actually,
STFC-RAL-CR03 R61: In order of terabytes, but the resolution was 1H in terms of what it should be.
STFC-RAL-CR03 R61: At full resolution, the order of any tool being created 200 times, which kind of makes it even more challenging to visualize, because then you'll be happy machines, you need a lot of memory.
STFC-RAL-CR03 R61: Which can be challenging for visualization, but it gives you insights and discoveries, which is essentially limited by the scientists to, deliver the programs.
STFC-RAL-CR03 R61: Yes, and then in this table, we're showing data, the products of your framework, which is the end products, or the results that people see or use.
STFC-RAL-CR03 R61: What overhead, or how much…
STFC-RAL-CR03 R61: What's… what's… how much data you create from the framework?
STFC-RAL-CR03 R61: Yeah, so that… that varies from, the requirement. For example, I had one figure
STFC-RAL-CR03 R61: Okay.
STFC-RAL-CR03 R61: So this is… We really… But…
STFC-RAL-CR03 R61: To give you an example, because there is a block diagram listed here, here we are dealing with, for this example, we are dealing with terabytes of data.
STFC-RAL-CR03 R61: -Oh.
STFC-RAL-CR03 R61: But the end result is just an image.
STFC-RAL-CR03 R61: Now, if the requirement is a low resolution PLT, the data size will be small.
STFC-RAL-CR03 R61: And our pipeline will use, kind of,
STFC-RAL-CR03 R61: less complex, processing of data. But if the requirement is to generate a very high-resolution visualization, then we switch gears and we kind of post-process the data in a very high resolution fashion, which leads to generation of, like, more data.
STFC-RAL-CR03 R61: So, in our case, it, varies, what the requirements are. So, the requirements are to kind of create images or videos, at what resolution is required, or, like, what is it that they are looking for.
STFC-RAL-CR03 R61: The events I do that.
STFC-RAL-CR03 R61: I mean, the videos can change.
STFC-RAL-CR03 R61: But what we are trying to do is to build, a system where,
STFC-RAL-CR03 R61: These experiences can be streamed onto a browser or onto a machine.
STFC-RAL-CR03 R61: Such that, that bottleneck or challenge for better.
STFC-RAL-CR03 R61: Processing the data on the local machine can be uploaded to something which is sitting, at the cluster level, and then you get to see the results. So you just experience the end result, and all the happy processing goes on and happens on the cluster side.
STFC-RAL-CR03 R61: So that's something we have actually relate upon.
STFC-RAL-CR03 R61: Thank you.
STFC-RAL-CR03 R61: Any further questions on the room, or on Zoom? Are there any questions on Zoom? No. No? And let's thank the speaker again.
STFC-RAL-CR03 R61: So, we'll be heading for lunch, let's say, in 8 to 10 minutes, and you can meet us in the corridor.