Massachusetts Green High Performance Computing Center

Data centers are at the heart of the IT-driven economy. Power consumption of a single data center can range from tens to a hundred megawatts, and operational costs can run into millions of dollars a month. Data center operators incorporate careful design and optimizations to reduce large-scale data centers energy consumption. Because data center design and operations are a source of competitive advantage, insight into modern data centers is scarce. This article describes the design and analysis of a state-of-the-art green university data center, and provides several insights into its operational and efficiency characteristics.

Incorporating equity and inclusion in the effort toward access for everyone.

Data centers are an indispensable part of today's IT infrastructure. To keep pace with modern computing needs, data centers continue to grow in scale and consume increasing amounts of power. While prior work on data centers has led to significant improvements in their energy-efficiency, detailed measurements from these facilities' operations are not widely available, as data center design is often considered part of a company's competitive advantage. However, such detailed measurements are critical to the research community in motivating and evaluating new energy-efficiency optimizations. In this paper, we present a detailed analysis of a state-of-the-art 15MW green multi-tenant data center that incorporates many of the technological advances used in commercial data centers. We analyze the data center's computing load and its impact on power, water, and carbon usage using standard effectiveness metrics, including PUE, WUE, and CUE. Our results reveal the benefits of optimizations, such as free cooling, and provide insights into how the various effectiveness metrics change with the seasons and increasing capacity usage. More broadly, our PUE, WUE, and CUE analysis validate the green design of this LEED Platinum data center.

Computer science education has been making dramatic increases in recent years. Across the US, different states are advancing computer science education through different policies. However, as a state makes choices to advance computer science education, it is critical to consider how these policies will broaden participation in computing (BPC). Many have indicated that only white and Asian males (who make up 30% of our population) currently have the opportunity/privilege to engage in computer science education. Therefore, as we implement state-level computer science education reform, it is critical that BPC remains as our guiding principle. Expanding Computing Education Pathways (ECEP) was created as an NSF national alliance to support state-level educational reform with regards to computer science. Over the past 6 years, this alliance of 22 states and Puerto Rico have worked together to share policies to advance BPC in each state. Through these experiences, ECEP has proposed that state change related to CS educational reform follows five stages: (1) Find your leader(s) and change agents; (2) understand the CS education landscape and identify the key issues/policies; (3) gather and organize your allies to establish goals and develop strategic plans and; (4) get initial funding to support change and; (5) building and utilizing data infrastructure that informs strategic BPC efforts. This study examined the ECEP alliance and the five-stage model through the 25,000+ documents and data sources over the past decade, specifically investigating how these five stages impacted states’ overall BPC efforts. Results indicated that these 5 stages seemed to support states’ BPC efforts.

Facilitating the development of a common framework for monitoring progress in K-12 computer science (CS) education and advocacy with an emphasis on broadening participation is the key to constructing strong CS education policy. Based on a project that brought together leadership teams from six states, a framework for measuring broadening participation in computing (BPC) and setting the foundation for national scaling was developed. Built around a collaboration of leaders representing experience in data gathering, data analysis, data reporting, and data utilization, this project applied the tenets of collective impact to address the challenge of consistently measuring progress toward BPC across state contexts. By establishing a common agenda, including mutually agreed upon definitions of computer science education and broadening participation, these leaders guided the selection of metrics. This led to the development of shared measurement systems and built a deeper understanding of state data systems across the participating states. This phase resulted in common goals and a monitoring system to measure BPC efforts that could inform state policy efforts. Mutually reinforcing activities included the development and sharing of tools, allowing stakeholders to quickly and accurately analyze and disseminate data that drives BPC measurement and policy work. Guided by backbone support to coordinate the work and continuous communication, meaningful participation of all stakeholders was central to the project. Making the case for CS education policy via common metrics and measuring progress across a region stands to impact BPC policy efforts across the United States. The common framework developed in this project serves as a call to action, especially for state and local education agencies committed to increasing diversity in computer science pathways.

Over the past 20 years, there has been a concentrated effort on expanding K–12 pathways, experiences, and access in computer science education (CSEd). Computer science (CS) is a multifaceted discipline within education, and the current emphasis in education policy has focused on how to expand access for K–12 students in CSEd that will lead to increased innovation and bring new participants into the United States labor economy. Industry partners have advocated for policies and incentives to increase pathways to CS opportunities. This chapter interrogates the side effects of CSEd and offers a framework for considering how side effects impact CS teaching and learning. We highlight the barriers that exist within CS and CSEd and how broadening participation in computing efforts could address longstanding equity and disparity issues.

NSF-supported cyberinfrastructure (CI) has been highly successful in advancing science and engineering over the last few decades. During that time, there have been significant changes in the size and composition of the participating community, the architecture and capacity of compute, storage, and networking platforms, and the methods by which researchers and CI professionals communicate. These changes require rethinking the role of research support services and how they are delivered. To address these changes and support an expanding community, MATCH is implementing a model for research support services in ACCESS that comprises

1 st in the Northeast) First multi-university HPC facility of its kind in

This study investigates a university-community partnership focused on broadening participation for girls in science, technology, engineering, and mathematics (STEM). Stakeholders across partner organizations (an informal learning community organization and a public research university) call the success and longevity of the collaboration "magic" because of the commitment required to maintain it despite partnership complexities and few formal incentives. Using qualitative inquiry and sensemaking/ sensegiving frameworks, this article elucidates the "magic" behind the partnership. Findings emphasize individual motivations and behaviors, program collaboration obstacles, and collective partnership identity impacting the program's sustainability (i.e., magic). This study can inform research and practice related to improving access into STEM pathways for underrepresented populations through education partnerships that often experience resource constraints alongside the organizational complexities of cross-sector engagement.

The K-12 broadening participation in computing (BPC) effort requires access to comprehensive state and national K-12 data from which stronger strategies for systems change can be developed. The Expanding Computing Education Pathways (ECEP) Alliance Common Metrics Project (CMP) engages state teams that include state and local education agencies, researchers, and other BPC advocates addressing K-12 computer science (CS) inequities in access and participation at the systems level. The CMP promotes collaboration and knowledge sharing, with teams reporting how CMP enhances BPC policy, pathways, and practices to improve student access and participation in computing. This experience report shares how the CMP advances data as a key tool for driving BPC strategies in state advocacy and policy efforts.

The goal of this study is to describe a design architecture for a self-powered IoT (Internet of Things) sensor network that is currently being deployed at various locations throughout the Dallas-Fort Worth metroplex to measure and report on Particulate Matter (PM) concentrations. This system leverages diverse low-cost PM sensors, enhanced by machine learning for sensor calibration, with LoRaWAN connectivity for long-range data transmission. Sensors are GPS-enabled, allowing precise geospatial mapping of collected data, which can be integrated with urban air quality forecasting models and operational forecasting systems. To achieve energy self-sufficiency, the system uses a small-scale solar-powered solution, allowing it to operate independently from the grid, making it both cost-effective and suitable for remote locations. This novel approach leverages multiple operational modes based on power availability to optimize energy efficiency and prevent downtime. By dynamically adjusting system behavior according to power conditions, it ensures continuous operation while conserving energy during periods of reduced supply. This innovative strategy significantly enhances performance and resource management, improving system reliability and sustainability. This IoT network provides localized real-time air quality data, which has significant public health benefits, especially for vulnerable populations in densely populated urban environments. The project demonstrates the synergy between IoT sensor data, machine learning-enhanced calibration, and forecasting methods, contributing to scientific understanding of microenvironments, human exposure, and public health impacts of urban air quality. In addition, this study emphasizes open source design principles, promoting transparency, data quality, and reproducibility by exploring cost-effective sensor calibration techniques and adhering to open data standards. The next iteration of the sensors will include edge processing for short-term air quality forecasts. This work underscores the transformative role of low-cost sensor networks in urban air quality monitoring, advancing equitable policy development and empowering communities to address pollution challenges.

The Northeast Cyberteam Program is a collaborative effort across Maine, New Hampshire, Vermont, and Massachusetts that seeks to assist researchers at small and medium-sized institutions in the region with making use of cyberinfrastructure, while simultaneously building the next generation of research computing facilitators. Recognizing that research computing facilitators are frequently in short supply, the program also places intentional emphasis on capturing and disseminating best practices in an effort to enable opportunities to leverage and build on existing solutions whenever practical. The program combines direct assistance to computationally intensive research projects; experiential learning opportunities that pair experienced mentors with students interested in research computing facilitation; sharing of resources and knowledge across large and small institutions; and tools that enable efficient oversight and possible replication of these ideas in other regions. Each project involves a researcher seeking to better utilize cyberinfrastructure in research, a student facilitator, and a mentor with relevant domain expertise. These individuals may be at the same institution or at separate institutions. The student works with the researcher and the mentor to become a bridge between the infrastructure and the research domain. Through this model, students receive training and opportunities that otherwise would not be available, research projects get taken to a higher level, and the effectiveness of the mentor is multiplied. Providing tools to enable self-service learning is a key concept in our strategy to develop facilitators through experiential learning, recognizing that one of the most fundamental skills of successful facilitators is their ability to quickly learn enough about new domains and applications to be able draw parallels with their existing knowledge and help to solve the problem at hand. The Cyberteam Portal is used to access the self-service learning resources developed to provide just-in-time information delivery to participants as they embark on projects in unfamiliar domains, and also serves as a receptacle for best practices, tools, and techniques developed during a project. Tools include Ask.CI, an interactive site for questions and answers; a learning resources repository used to collect online training modules vetted by Cyberteam projects that provide starting points for subsequent projects or independent activities; and a Github repository. The Northeast Cyberteam was created with funding from the National Science Foundation, but has developed strategies for sustainable operations. Each project involves a researcher seeking to better utilize cyberinfrastructure in research, a student facilitator, and a mentor with relevant domain expertise. These individuals may be at the same institution or at separate institutions. The student works with the researcher and the mentor to become a bridge between the infrastructure and the research domain. Through this model, students receive training and opportunities that otherwise would not be available, research projects get taken to a higher level, and the effectiveness of the mentor is multiplied. Providing tools to enable self-service learning is a key concept in our strategy to develop facilitators through experiential learning, recognizing that one of the most fundamental skills of successful facilitators is their ability to quickly learn enough about new domains and applications to be able draw parallels with their existing knowledge and help to solve the problem at hand. The Cyberteam Portal is used to access the self-service learning resources developed to provide just-in-time information delivery to participants as they embark on projects in unfamiliar domains, and also serves as a receptacle for best practices, tools, and techniques developed during a project. Tools include Ask.CI, an interactive site for questions and answers; a learning resources repository used to collect online training modules vetted by Cyberteam projects that provide starting points for subsequent projects or independent activities; and a Github repository. The Northeast Cyberteam was created with funding from the National Science Foundation, but has developed strategies for sustainable operations. Providing tools to enable self-service learning is a key concept in our strategy to develop facilitators through experiential learning, recognizing that one of the most fundamental skills of successful facilitators is their ability to quickly learn enough about new domains and applications to be able draw parallels with their existing knowledge and help to solve the problem at hand. The Cyberteam Portal is used to access the self-service learning resources developed to provide just-in-time information delivery to participants as they embark on projects in unfamiliar domains, and also serves as a receptacle for best practices, tools, and techniques developed during a project. Tools include Ask.CI, an interactive site for questions and answers; a learning resources repository used to collect online training modules vetted by Cyberteam projects that provide starting points for subsequent projects or independent activities; and a Github repository. The Northeast Cyberteam was created with funding from the National Science Foundation, but has developed strategies for sustainable operations.

Distributed cyberinfrastructures (CI) pose opportunities and challenges for the execution of scientific workflows, especially in the context of Earth science applications. They provide heterogeneous resources that can meet the needs of the applications that are part of the scientific workflows and provide the necessary performance and scalability to achieve scientific goals. However, the challenge with distributed CI is that it is difficult to find the right resources for the applications and to orchestrate the workflow execution from resource provisioning to job execution to delivering the final results. In some cases, poor choice of resources may result in slow execution or outright failure. In this paper, we present Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) Pegasus, a CI solution built as part of the U.S. National Science Foundation ACCESS program that provides automated execution of scientific applications. We demonstrate Pegasus's capabilities with SOil MOisture SPatial Inference Engine (SOMOSPIE), an earth science multi-component application for fine-grained soil moisture predictions. We identify a roadmap to migrate applications such as SOMOSPIE on ACCESS resources with the support of ACCESS Pegasus, outlining both strengths and weaknesses of this approach.

Feedback and survey data collected from hundreds of participants of the Ecosystem for Research Networking (formerly Eastern Regional Network) series of NSF (OAC-2018927) funded community outreach meetings and workshops revealed that Structural Biology Instrument driven science is being forced to transition from self-contained islands to federated wide-area internet accessible instruments. This paper discusses phase 1 of the active ERN CryoEM Federated Instrument Pilot project whose goal is to facilitate inter-institutional collaboration at the interface of computing and electron microscopy through the implementation of the ERN Federated OpenCI Lab’s Instrument CI Cloudlet design. The conclusion will be a web-based portal leveraging federated access to the instrument, workflows utilizing edge computing in conjunction with cloud computing, along with real-time monitoring for experimental parameter adjustments and decisions. The intention is to foster team science and scientific innovation, with emphasis on under-represented and under-resourced institutions, through the democratization of these scientific instruments.

The Ecosystem for Research Networking (ERN) CryoEM Remote Instrument Pilot Project was launched in response to feedback and survey data collected from hundreds of participants of the ERN series of NSF (OAC-2018927) funded community outreach events revealing that Structural Biology instrument driven science is being forced to transition from self-contained islands to federated wide-area internet accessible instruments. Its goal is to facilitate multi-institutional collaboration at the interface of computing and electron microscopy through the implementation of the ERN Federated OpenCI Lab’s Instrument CI Cloudlet design. The conclusion will be a web-based portal leveraging federated access to the instrument, workflows utilizing edge computing in conjunction with cloud computing and real-time monitoring for experimental parameter adjustments and decisions. The intention is to foster team science and scientific innovation, with emphasis on under-represented and under-resourced institutions, through the democratization of these scientific instruments. This paper discusses the latest Phase 1 deployment efforts

poster Share on ACCESS Pegasus: Bringing Workflows to the ACCESS Masses Authors: Mats Rynge USC Information Sciences Institute, USA USC Information Sciences Institute, USA 0000-0002-1779-7189View Profile , Karan Vahi USC Information Sciences Institute, USA USC Information Sciences Institute, USA 0000-0001-8622-2082View Profile , Mohammad Zaiyan Alam USC Information Sciences Institute, USA USC Information Sciences Institute, USA 0009-0006-5705-2639View Profile , Ewa Deelman USC Information Sciences Institute, USA USC Information Sciences Institute, USA 0000-0001-5106-503XView Profile , Todd Miller University of Wisconsin-Madison, USA University of Wisconsin-Madison, USA 0009-0003-0683-3062View Profile , Miron Livny University of Wisconsin-Madison, USA University of Wisconsin-Madison, USA 0000-0001-5444-7439View Profile , Shelley Knuth Research Computing, University of Colorado, USA Research Computing, University of Colorado, USA 0000-0001-7249-4773View Profile , James Griffioen University of Kentucky, USA University of Kentucky, USA 0000-0002-5105-096XView Profile , John Goodhue Massachusetts Green High Performance Computing Center, USA Massachusetts Green High Performance Computing Center, USA 0009-0003-8344-9945View Profile , David Hudak Ohio Supercomputer Center, USA Ohio Supercomputer Center, USA 0000-0002-9043-0850View Profile , Julie Ma Massachusetts Green High Performance Computing Center, USA Massachusetts Green High Performance Computing Center, USA 0000-0001-6220-4314View Profile , Andrew Pasquale Massachusetts Green High Performance Computing Center, USA Massachusetts Green High Performance Computing Center, USA 0000-0002-7501-367XView Profile , Lissie Fein Massachusetts Green High Performance Computing Center, USA Massachusetts Green High Performance Computing Center, USA 0009-0000-9419-9150View Profile Authors Info & Claims PEARC '23: Practice and Experience in Advanced Research ComputingJuly 2023Pages 478–480https://doi.org/10.1145/3569951.3597590Published:10 September 2023Publication History 0citation22DownloadsMetricsTotal Citations0Total Downloads22Last 12 Months22Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

In recent years, state members of the Expanding Computing Education Pathways (ECEP) Alliance have made efforts to increase access to and broaden participation in computing at the K-12 levels. Each ECEP state's K-12 computer science (CS) education journey has been documented during their ECEP membership resulting in over 25,000 digital documents. Over the course of the project it was necessary to track key events, identify trends across states, and maintain consumable records of state progress. A systematic way to collect and track the data is critical to conduct historical and cross-state analyses. In an effort to quantify and categorize, the researchers engaged in a review process of all ECEP reports, artifacts, and other relevant data to develop a system. Relevant and important components were identified in each type of document and assigned codes using ECEP's Five Stage Model ("a five-step process toward state-level CS education reform"), the Capacity, Access, Participation, and Experience (CAPE) framework (to measure equity in CS education implementation), and specific policies initiatives (alignment with various policy initiatives - Code.org's "Nine Policy Ideas to Make CS Fundamental to K?12 Education"). Indiana was identified as a state to conduct an initial, in-depth case study using this process. Indiana's case will be used as a model to further develop the stories of other ECEP Alliance member states. Through the development of a data dashboard, we hope to organize all of this information to make it more easily accessible for review and further analysis. The ECEP data dashboard development is currently in progress.