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At least 91 records · Page 5

Reinventing Image Detective: An Evidence-Based Approach to Citizen Science Online

Usability studies demonstrate that web users are notoriously impatient, spending as little as 15 seconds on a home page. How do you get users to stay long enough to understand a citizen science project? How do you get users to complete complex citizen science tasks online? Image Detective, a citizen science project originally developed by scientists and science engagement specialists at the NASA Johnson Space center to engage the public in the analysis of images taken from space by astronauts to help enhance NASA's online database of astronaut imagery, partnered with the CosmoQuest citizen science platform to modernize, offering new and improved options for participation in Image Detective. The challenge: to create a web interface that builds users' skills and knowledge, creating engagement while learning complex concepts essential to the accurate completion of tasks. The project team turned to usability testing for an objective understanding of how users perceived Image Detective and the steps required to complete required tasks. A group of six users was recruited online for unmoderated and initial testing. The users followed a think-aloud protocol while attempting tasks, and were recorded on video and audio. The usability test examined users' perception of four broad areas: the purpose of and context for Image Detective; the steps required to successfully complete the analysis (differentiating images of Earth's surface from those showing outer space and identifying common surface features); locating the image center point on a map of Earth; and finally, naming geographic locations or natural events seen in the image. Usability test findings demonstrated that the following best practices can increase participation in Image Detective and can be applied to the successful implementation of any citizen science project: (1) Concise explanation of the project, its context, and its purpose; (2) Including a mention of the funding agency (in this case, NASA); (3) A preview of the specific tasks required of participants; (4) A dedicated user interface for the actual citizen science interaction. In addition, testing revealed that users may require additional context when a task is complex, difficult, or unusual (locating a specific image and its center point on a map of Earth). Video evidence will be made available with this presentation.

Romano, Cia↗

Evaluation of Data Catalog Software for Hanford Site Environmental Datasets

Environmental information and data underpin achievement of the U.S. Department of Energy (DOE) Office of Environmental Management (EM) mission at the Hanford Site. The Hanford Environmental Data Management (HEDM) Program is the DOE Richland Operations Office (RL) approach to develop and implement a formal program for managing environmental data and the associated records, materials, and systems at the Hanford Site. The current project, contract, organization, and contractor-specific efforts at managing environmental data sets are insufficient to provide orderly, long-term, site-wide access. A vital element to be created within the HEDM program plan is a catalog of data sources, called the Hanford Environmental Information and Data Index (HEIDI), that will enable long-term access and retrievability for the multiple independent sources of data that might otherwise be difficult to discover. This report compares leading open source and commercial data catalog platforms using criteria to assess the functionality needed to develop the HEIDI catalog of Hanford data sources that connects and exchanges data with established Hanford Local Area Network (HLAN) enterprise information technology systems. Proprietary platforms evaluated included ArcGIS Enterprise Sites, Junar, OpenDataSoft, and Socrata, and non-proprietary platforms included Energy Data eXchange (EDX), Comprehensive Knowledge Archive Network (CKAN), and DKAN (a Drupal-based open data portal based on CKAN). Capabilities supporting data discoverability, retrieval, and archival, as well as metadata standard requirements and integration into the HLAN were rated as either failing to meet requirements (F), meeting requirements (M), or exceeding requirements by delivering additional desired features (E). The lowest rating for any capability area was assigned as the overall rating for the platform. These findings enable DOE-RL and the contractors implementing the HEDM plan to focus on candidate tools likely to meet the requirements for implementing HEIDI. All of the platforms receiving an overall rating of ‘F’ were unable to be deployed on Hanford infrastructure or within dedicated cloud resources. A propriety software-as-a-service (SaaS) model of delivering a data catalog (e.g., found in software such as Junar and OpenDataSoft) favors consistency across customers at the expense of customization and configurable roles that are needed for Hanford work. Hosting data on a shared commercial platform places limits on dataset size (maximum of 240 Mb for OpenDataSoft), a significant limitation for HEIDI implementation. EDX, a government data catalog based on CKAN, received the ‘F’ rating due to an inability to incorporate authentication from HLAN into the system. Among platforms rated ‘M’ or ‘E’, only the Socrata platform had a SaaS delivery model. In contrast to other SaaS platforms, Socrata provided custom roles and gateways that allow local datasets to be incorporated into an online catalog. Socrata also complies with the Federal Risk and Authorization Management Program, a significant benefit for cloud-based management of Hanford data. The other platforms rated ‘M’ or ‘E’, ArcGIS Enterprise Sites, CKAN, and DKAN, provide fully self-hosted options, allowing for greater control and flexibility with the HEIDI catalog. These widely used tools have supportive communities of practice, extensive customization options, and demonstrated deployments that provide evidence that they can meet requirements, often deliver additional desired features, and work well with federal government systems. Completely customized alternatives built on a collection of applications were not evaluated because achieving similar performance to CKAN or DKAN requires substantial resources, especially in the absence of the active communities that have grown to support these tools. ArcGIS Enterprise Sites, Socrata, CKAN, and DKAN were evaluated as strong candidates for successful implementation with HEIDI.

54 ENVIRONMENTAL SCIENCES↗

Autonomous closed-loop mechanistic investigation of molecular electrochemistry via automation

Abstract Electrochemical research often requires stringent combinations of experimental parameters that are demanding to manually locate. Recent advances in automated instrumentation and machine-learning algorithms unlock the possibility for accelerated studies of electrochemical fundamentals via high-throughput, online decision-making. Here we report an autonomous electrochemical platform that implements an adaptive, closed-loop workflow for mechanistic investigation of molecular electrochemistry. As a proof-of-concept, this platform autonomously identifies and investigates an EC mechanism, an interfacial electron transfer ( E step) followed by a solution reaction ( C step), for cobalt tetraphenylporphyrin exposed to a library of organohalide electrophiles. The generally applicable workflow accurately discerns the EC mechanism’s presence amid negative controls and outliers, adaptively designs desired experimental conditions, and quantitatively extracts kinetic information of the C step spanning over 7 orders of magnitude, from which mechanistic insights into oxidative addition pathways are gained. This work opens opportunities for autonomous mechanistic discoveries in self-driving electrochemistry laboratories without manual intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TripleGraph

RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title “TripleGraph” is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).

Sangkeun, MattLee↗

Simulations of Aerosol Microphysics in the NASA GEOS-5 Model

Aerosol-cloud-chemistry interactions have potentially large but uncertain impacts on Earth's climate. One path to addressing these uncertainties is to construct models that incorporate various components of the Earth system and to test these models against data. To that end, we have previously incorporated the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) module online in the NASA Goddard Earth Observing System model (GEOS-5). GEOS-5 provides a platform for Earth system modeling, incorporating atmospheric and ocean general circulation models, a land surface model, a data assimilation system, and treatments of atmospheric chemistry and hydrologic cycle. Including GOCART online in this framework has provided a path for interactive aerosol-climate studies; however, GOCART only tracks the mass of aerosols as external mixtures and does not include the detailed treatments of aerosol size distribution and composition (internal mixtures) needed for aerosol-cloud-chemistry-climate studies. To address that need we have incorporated the Community Aerosol and Radiation Model for Atmospheres (CARMA) online in GEOS-5. CARMA is a sectional aerosol-cloud microphysical model, capable of treating both aerosol size and composition explicitly be resolving the aerosol distribution into a variable number of size and composition groupings. Here we present first simulations of dust, sea salt, and smoke aerosols in GEOS-5 as treated by CARMA. These simulations are compared to available aerosol satellite, ground, and aircraft data and as well compared to the simulated distributions in our current GOCART based system.

Colarco, Peter↗

Development and Implementation of a Hardware In-the-Loop Test Bed for Unmanned Aerial Vehicle Control Algorithms

Successful prediction and management of battery life using prognostic algorithms through ground and flight tests is important for performance evaluation of electrical systems. This paper details the design of test beds suitable for replicating loading profiles that would be encountered in deployed electrical systems. The test bed data will be used to develop and validate prognostic algorithms for predicting battery discharge time and battery failure time. Online battery prognostic algorithms will enable health management strategies. The platform used for algorithm demonstration is the EDGE 540T electric unmanned aerial vehicle (UAV). The fully designed test beds developed and detailed in this paper can be used to conduct battery life tests by controlling current and recording voltage and temperature to develop a model that makes a prediction of end-of-charge and end-of-life of the system based on rapid state of health (SOH) assessment.

Battery Testbed↗

Smart Mobility in the Cloud: Enabling Real-Time Situational Awareness and Cyber-Physical Control Through a Digital Twin for Traffic

This article presents the design, implementation, and use cases of the Chattanooga Digital Twin (CTwin) towards the vision for next-generation smart city applications for urban mobility management. CTwin is an end-to-end web-based platform that incorporates various aspects of the decision-making process for optimizing urban transportation systems in Chattanooga, Tennessee, to reduce traffic congestion, incidents, and vehicle fuel consumption. The platform serves as a cyberinfrastructure to collect and integrate multi-domain urban mobility data from various online repositories and Internet of Things (IoT) sensors, covering multiple urban aspects (e.g., traffic, natural hazards, weather, and safety) that are relevant to urban mobility management. The platform enables advanced capabilities for: (a) real-time situational awareness on traffic and infrastructure conditions on highways and urban roads, (b) cyber-physical control for optimizing traffic signal timing, and (c) interactive visual analytics on big urban mobility data and various metrics for traffic prediction and transportation performance evaluation. The platform is designed using a multi-level componentization paradigm and is implemented using modular and adaptive architecture, rendering it as a generalizable and extendable prototype for other urban management applications. We present several use cases to demonstrate CTwin's core capabilities for supporting decision-making in smart urban mobility management.

33 ADVANCED PROPULSION SYSTEMS↗

Wormhole: A Powerful Data Mashup

The mobile platform is quickly becoming the standard way that users interact with online resources. The iOS operating system allows iPhone and iPad users to seamlessly access highly interactive web applications that until recently were only available via a desktop or laptop. Wormhole is an AJAX application implemented as a smart web widget that allows users to easily supplement web pages with data directly from the Instrument Operations Subsystems division (IOS) at JPL. It creates an interactive mashup using a website's core content enhanced by dynamically retrieved image and metadata supplied by IOS using the webification API. Currently, this technology is limited in scope to NASA data; however, it can easily be augmented to serve many other needs. This web widget can be delivered in various ways, including as a bookmarklet. The underlying technology that powers Wormhole also has applications to other divisions while they are running current missions.

maship↗

Image-Guided Intraoperative Assessment of Surgical Margins in Oral Cavity Squamous Cell Cancer: A Diagnostic Test Accuracy Review

The assessment of resection margins during surgery of oral cavity squamous cell cancer (OCSCC) dramatically impacts the prognosis of the patient as well as the need for adjuvant treatment in the future. Currently there is an unmet need to improve OCSCC surgical margins which appear to be involved in around 45% cases. Intraoperative imaging techniques, magnetic resonance imaging (MRI) and intraoral ultrasound (ioUS), have emerged as promising tools in guiding surgical resection, although the number of studies available on this subject is still low. The aim of this diagnostic test accuracy (DTA) review is to investigate the accuracy of intraoperative imaging in the assessment of OCSCC margins. By using the Cochrane-supported platform Review Manager version 5.4, a systematic search was performed on the online databases MEDLINE-EMBASE-CENTRAL using the keywords “oral cavity cancer, squamous cell carcinoma, tongue cancer, surgical margins, magnetic resonance imaging, intraoperative, intra-oral ultrasound”. Ten papers were identified for full-text analysis. The negative predictive value (cutoff < 5 mm) for ioUS ranged from 0.55 to 0.91, that of MRI ranged from 0.5 to 0.91; accuracy analysis performed on four selected studies showed a sensitivity ranging from 0.07 to 0.75 and specificity ranging from 0.81 to 1. Image guidance allowed for a mean improvement in free margin resection of 35%. IoUS shows comparable accuracy to that of ex vivo MRI for the assessment of close and involved surgical margins, and should be preferred as the more affordable and reproducible technique. Both techniques showed higher diagnostic yield if applied to early OCSCC (T1–T2 stages), and when histology is favorable.

60 APPLIED LIFE SCIENCES↗

Online Simulations of Global Aerosol Distributions in the NASA GEOS-4 Model and Comparisons to Satellite and Ground-Based Aerosol Optical Depth

We have implemented a module for tropospheric aerosols (GO CART) online in the NASA Goddard Earth Observing System version 4 model and simulated global aerosol distributions for the period 2000-2006. The new online system offers several advantages over the previous offline version, providing a platform for aerosol data assimilation, aerosol-chemistry-climate interaction studies, and short-range chemical weather forecasting and climate prediction. We introduce as well a methodology for sampling model output consistently with satellite aerosol optical thickness (AOT) retrievals to facilitate model-satellite comparison. Our results are similar to the offline GOCART model and to the models participating in the AeroCom intercomparison. The simulated AOT has similar seasonal and regional variability and magnitude to Aerosol Robotic Network (AERONET), Moderate Resolution Imaging Spectroradiometer, and Multiangle Imaging Spectroradiometer observations. The model AOT and Angstrom parameter are consistently low relative to AERONET in biomass-burning-dominated regions, where emissions appear to be underestimated, consistent with the results of the offline GOCART model. In contrast, the model AOT is biased high in sulfate-dominated regions of North America and Europe. Our model-satellite comparison methodology shows that diurnal variability in aerosol loading is unimportant compared to sampling the model where the satellite has cloud-free observations, particularly in sulfate-dominated regions. Simulated sea salt burden and optical thickness are high by a factor of 2-3 relative to other models, and agreement between model and satellite over-ocean AOT is improved by reducing the model sea salt burden by a factor of 2. The best agreement in both AOT magnitude and variability occurs immediately downwind of the Saharan dust plume.

Colarco, Peter↗

Engineering of Data Acquiring Mobile Software and Sustainable End-User Applications

The criteria for which data acquiring software and its supporting infrastructure should be designed should take the following two points into account: the reusability and organization of stored online and remote data and content, and an assessment on whether abandoning a platform optimized design in favor for a multi-platform solution significantly reduces the performance of an end-user application. Furthermore, in-house applications that control or process instrument acquired data for end-users should be designed with a communication and control interface such that the application's modules can be reused as plug-in modular components in greater software systems. The application of the above mentioned is applied using two loosely related projects: a mobile application, and a website containing live and simulated data. For the intelligent devices mobile application AIDM, the end-user interface have a platform and data type optimized design, while the database and back-end applications store this information in an organized manner and manage access to that data to only to authorized user end application(s). Finally, the content for the website was derived from a database such that the content can be included and uniform to all applications accessing the content. With these projects being ongoing, I have concluded from my research that the applicable methods presented are feasible for both projects, and that a multi-platform design for the mobile application only marginally drop the performance of the mobile application.

Smith, Benton T.↗

Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit

Software vulnerabilities are flaws in computer systems that leave users open to attack. In many cases, these vulnerabilities go unnoticed and remain unresolved in codebases. Thus, awareness of software vulnerabilities among the public is crucial to ensure effective cybersecurity practices, the development of high quality software, and ultimately national security. This awareness can be better understood by studying the spread and evolution of software vulnerability discussions in online communities. This work is the first to evaluate and contrast how discussions about software vulnerabilities spread on three social platforms -- Twitter, GitHub, and Reddit. To lay the groundwork, we showcase a novel fundamental framework for measuring information spread that identifies the spread mechanisms and observables across platforms, the units of information, and the groups of measurements that can be applied to focus on a specific phenomena e.g., information cascades. We then analyze and contrast social network topologies for three example social networks and measure the scale and speed of the spread of discussion of specific vulnerabilities to understand how far and how widely they spread, how many users participate in discussions, and the duration of their spread. To demonstrate the awareness of more impactful software vulnerabilities, a subset of our analysis focuses on vulnerabilities targeted during recent major cyber attacks as well as vulnerabilities exploited by advanced persistent threat groups. We discover that usually, vulnerability discussions start on GitHub, before occurring on Twitter and Reddit. While studying how some user-level and content-level characteristics influence vulnerability spread, we observe that Twitter discussions started by users predicted to be humans have larger size, breadth, depth, adoption rate, lifetime, and structural virality compared to those started by users predicted to be bots. On Reddit, we contrast the differences in thread structure that originate from posts with positive, negative and neutral polarity. We find that posts that are positive have larger, deeper and wider discussions compared to negative and neutral posts. We anticipate the results of our analysis to not only increase the understanding of software vulnerability awareness but also inform models for simulating information spread across multiple social environments online.

97 MATHEMATICS AND COMPUTING↗

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

The execution of agent-based simulations (ABSs) on hardware accelerator devices such as graphics processing units (GPUs) has been shown to offer great performance potentials. However, in heterogeneous hardware environments, it can become increasingly difficult to find viable partitions of the simulation and provide implementations for different hardware devices. To automate this process, we present OpenABLext, an extension to OpenABL, a model specification language for ABSs. By providing a device-aware OpenCL backend, OpenABLext enables the co-execution of ABS on heterogeneous hardware platforms consisting of central processing units, GPUs, and field programmable gate arrays (FPGAs).We present a novel online dispatching method that efficiently profiles partitions of the simulation during run-time to optimize the hardware assignment while using the profiling results to advance the simulation itself. In addition, OpenABLext features automated conflict resolution based on user-specified rules, supports graph-based simulation spaces, and utilizes an efficient neighbor search algorithm. We show the improved performance of OpenABLext and demonstrate the potential of FPGAs in the context of ABS. We illustrate how co-execution can be used to further lower execution times. OpenABLext can be seen as an enabler to tap the computing power of heterogeneous hardware platforms for ABS.

97 MATHEMATICS AND COMPUTING↗

A common platform for DSN receiver development

NASA's Deep Space Network is currently updating a number of sub systems within the Signal Processing Centers at its Deep Space Communication Complexes in order to modernize aging equipment in the downlink receivers for telemetry, tracking, radio science, and radio astronomy. To reduce development costs and increase commonality among these traditionally custom-built receivers, the implementation team has developed a flexible architecture built primarily around commercial off-the-shelf hardware compliant with the Micro Telecommunications Computing Architecture (uTCA) specification and commercial high speed 10Gbit Ethernet switches. Custom firmware and software are being developed to perform the required signal processing functions needed to replace the legacy systems in a phased implementation approach which establishes a new digital Intermediate Frequency (IF) signal distribution system first, followed by implementations of various receiver functions as dictated by need. The first of these new receivers, the Open Loop Receiver, will come online in the Fall of 2018. A description of the new architecture, referred to as the “Common Platform”, will be provided followed by an overview of the phased implementation approach and initial OLR performance results.

Navarro, Robert↗

NASA Human Research Wiki - An Online Collaboration Tool

In preparation for exploration-class missions, the Exploration Medical Capability (ExMC) element of NASA's Human Research Program (HRP) has compiled a large evidence base, which previously was available only to persons within the NASA community. The evidence base is comprised of several types of data, for example: information on more than 80 medical conditions which could occur during space flight, derived from several sources (including data on incidence and potential outcomes of these medical conditions, as captured in the Integrated Medical Model's Clinical Finding Forms). In addition, approximately 35 gap reports are included in the evidence base, identifying current understanding of the medical challenges for exploration, as well as any gaps in knowledge and/or technology that would need to be addressed in order to provide adequate medical support for these novel missions. In an effort to make the ExMC information available to the general public and increase collaboration with subject matter experts within and outside of NASA, ExMC has developed an online collaboration tool, very similar to a wiki, titled the NASA Human Research Wiki. The platform chosen for this data sharing, and the potential collaboration it could generate, is a MediaWiki-based application that would house the evidence, allow "read only" access to all visitors to the website, and editorial access to credentialed subject matter experts who have been approved by the Wiki's editorial board. Although traditional wikis allow users to edit information in real time, the NASA Human Research Wiki includes a peer review process to ensure quality and validity of information. The wiki is also intended to be a pathfinder project for other HRP elements that may want to use this type of web-based tool. The wiki website will be released with a subset of the data described and will continue to be populated throughout the year.

Barr, Y. R.↗

An exploration of online-simulation-driven portfolio scheduling in Workflow Management Systems

Workflow Management Systems used to automate the execution of scientific workflow applications on parallel and distributed computing platforms must make scheduling decisions at runtime. A large number of workflow scheduling algorithms have been proposed in the literature, but often these algorithms are evaluated based on simplifying assumptions that may not hold in practice. Furthermore, published algorithm evaluation and/or comparison results are necessarily only for a subset of all possible scenarios, and thus may not include scenarios relevant to particular use-cases. Consequently, it is difficult for Workflow Management Systems (WMSs) developers to decide which scheduling algorithm should be implemented. To obviate this difficulty, one possible approach is to implement a portfolio of scheduling algorithms and select the most effective algorithm at runtime. One method for performing this selection is to run an online simulation for each algorithm in the portfolio. The algorithm that leads to the best performance, in simulation, is selected for future use. The above simulation-driven portfolio scheduling (SDPS) approach has been proposed in a few parallel and distributed computing contexts. The main objective of this work is to evaluate the feasibility and potential merit of SDPS if implemented in WMSs. Here we perform this evaluation using simulated WMS executions, where the simulations are instantiated from real-world platform and workflow configurations. Our main finding is that SDPS is on par with or outperforms an approach in which a single algorithm is used, where this algorithm is the one that performs best on average across all our experimental scenarios. Furthermore, we find that SDPS remains an attractive proposition even in the presence of high levels of simulation error and for simulators with relatively low levels of sophistication. In many of our experimental scenarios we find that mitigating simulation error at runtime can further improve performance. Finally, we show that simulation overhead can be made sufficiently low for SDPS to be feasible in practice.

97 MATHEMATICS AND COMPUTING↗

Gulf of Mexico Turbulence Intensity Model Data in Observational Space

The dataset archives model-simulated turbulence intensity and meteorological profiles and timeseries at the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars. The simulated data are interpolated in time and/or space according to observed quantities. The simulations were carried out for the Gulf of Mexico region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles near the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing.

17 WIND ENERGY↗

A Co-design Framework for Online Data Analysis and Reduction

Science applications preparing for the exascale era are increasingly exploring in situ computations comprising of simulation-analysis-reduction pipelines coupled in-memory. Efficient composition and execution of such complex pipelines for a target platform is a codesign process that evaluates the impact and tradeoffs of various application- and system-specific parameters. In this article, we describe a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for composing parametric studies on coupled applications, and Savanna, a runtime engine for orchestrating and executing campaigns of codesign experiments. Furthermore, this toolset facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage versus compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design of Cheetah and Savanna, and present application examples that use this framework to conduct codesign studies on small clusters as well as leadership class supercomputers.

97 MATHEMATICS AND COMPUTING↗