We will provide an overview of DOE’s IRI initiative as it moves into early implementation, what drives the IRI vision, and the role of DOE in the larger national research ecosystem.
The Open Science Data Cloud is a hosted, managed, distributed facility that allows scientists to manage and archive medium and large datasets, provide computational resources to analyze the data, and share the data with colleagues and the public. It currently consists of 6 racks, 212 nodes, 1568 cores and 0.9 PB of storage across 4 locations with 10G networks. Projects using the Open Science Data Cloud include Bionimbus for hosting genomics data and Matsu 2 for providing flood data to disaster response teams. The goal is to build it out over the next 10 years into a small data center for science that can preserve data like libraries and museums preserve collections.
The document provides an overview of research data management for the School of Engineering at the University of Lincoln. It discusses the benefits of research data management, including increased transparency, collaboration, and opportunities for new research. It also outlines some of the support and requirements for research data management from funders and institutions.
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
The document discusses data management plan requirements for proposals submitted to the U.S. Department of Energy Office of Science for research funding. It provides context on the history of data management policies, outlines the four main requirements for inclusion of a data management plan, and suggests elements that should be included in the plan such as data types/sources, content/format, sharing/preservation, and protection. It also discusses tools like the Public Access Gateway for Energy and Science that can help manage access to research publications and data.
EarthCube Community Webinar 12.19.13: NSF EarthCube Funding Solicitation 13-529
The document summarizes an EarthCube community webinar that took place on December 19, 2013. The webinar covered EarthCube updates, the EarthCube test enterprise governance project, and the EarthCube funding solicitation. It provided an agenda for presentations on EarthCube governance, the funding solicitation, and a perspective on EarthCube from the NSF. It also described the goal of EarthCube to create a future state of geosciences cyberinfrastructure and outlined the test enterprise governance project which aims to develop an agile approach to designing an EarthCube system through community engagement.
CCCORE: Cloud Container for Collaborative Research
Cloud-based research collaboration platforms render scalable, secure and inventive environments that enabled academic and scientific researchers to share research data, applications and provide access to high- performance computing resources. Dynamic allocation of resources according to the unpredictable needs of applications used by researchers is a key challenge in collaborative research environments. We propose the design of Cloud Container based Collaborative Research (CCCORE) framework to address dynamic resource provisioning according to the variable workload of compute and data-intensive applications or analysis tools used by researchers. Our proposed approach relies on–demand, customized containerization and comprehensive assessment of resource requirements to achieve optimal resource allocation in a dynamic collaborative research environment. We propose algorithms for dynamic resource allocation problem in a collaborative research environment, which aim to minimize finish time, improve throughput and achieve optimal resource utilization by employing the underutilized residual resources.
Victoria A. White Head, Computing Division Fermilab
Global scientific collaborations are essential for particle physics experiments. Fermilab experiments involve over 200 institutions from around the world, with over half of physicists and a third of students coming from outside the US. Fermilab is working to support these collaborations through networks, grid computing, guest scientists programs, and outreach. Advances in information technology and global e-science are profoundly impacting many fields.
The document discusses the developing needs for e-infrastructures to support research. It summarizes the key recommendations from the OSI report, which include providing researchers with access to resources, facilities to discover resources, confidence in resource quality and integrity, and assurance of future accessibility. The JISC committee is developing a new strategy to address priorities around integrating data from multiple sources and enabling collaboration across boundaries.
The document discusses Internet2, an advanced networking consortium that operates a 15,000 mile fiber optic network for research and education. It provides very high speed connectivity and collaboration technologies to facilitate large data sharing and frictionless research. Examples are given of life sciences projects utilizing Internet2's high-speed network for genomic research and agricultural applications involving terabytes of satellite and sensor data. The network is expanding to include cloud computing resources and supercomputing centers to enable global-scale distributed scientific computing and collaboration.
Cloud Standards in the Real World: Cloud Standards Testing for Developers
Learn about standards studied in the US National Science Foundation Cloud and Autonomic Computing Industry/University Cooperative Research Center Cloud Standards Testing Lab and how you can get involved to extend the successes from these results in your own cloud software settings. Presented at the O'Reilly OSCON 2014 Open Cloud Day.
Video available at https://www.youtube.com/watch?v=eD2h0SqC7tY
Facing data sharing in a heterogeneous research community: lights and shadows...
1) RITMARE is a large, multi-institutional Italian marine research project aiming to build a data management infrastructure to facilitate sharing of data across research communities.
2) Subproject 7 of RITMARE seeks to design an IT system that enables interoperability and data exchange without forcing a single model or centralization. Efforts have included developing a data policy, collecting researcher requirements, and creating tools and services.
3) While progress has been made in establishing nodes providing access to data and metadata, uptake by researchers has been less than expected due to insufficient technical support, lack of data-related incentives, and developing a data policy after the project began rather than at the outset.
OSFair2017 Workshop | The European Open Science Cloud Pilot
Brian Matthews presents the European Open Science Cloud (EOSC) and the EOSCpilot | OSFair2017 Workshop
Workshop title: How FAIR friendly is your data catalogue?
Workshop overview:
This workshop will build upon the work planned by the EOSCpilot data interoperability task and the BlueBridge workshop held on April 3 at the RDA meeting. We will investigate common mechanisms for interoperation of data catalogues that preserve established community standards, norms and resources, while simplifying the process of being/becoming FAIR. Can we have a simple interoperability architecture based on a common set of metadata types? What are the minimum metadata requirements to expose FAIR data to EOSC services and EOSC users?
DAY 3 - PARALLEL SESSION 6 & 7
Globus Compute wth IRI Workflows - GlobusWorld 2024
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Globus Connect Server Deep Dive - GlobusWorld 2024
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Providing Globus Services to Users of JASMIN for Environmental Data Analysis
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
First Steps with Globus Compute Multi-User Endpoints
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Enhancing Research Orchestration Capabilities at ORNL.pdf
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
How to Position Your Globus Data Portal for Success Ten Good Practices
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
The Software Sustainability Institute (SSI) provides services to help research groups sustain their software over the long term. It collaborates with groups in various fields to improve key software through advice, training, and partnerships. Case studies describe projects in fields like fusion energy, climate modeling, geospatial data, and computational chemistry. The SSI aims to promote best practices and change perceptions so software is recognized as a valuable long-term asset, not just for initial research. Sustaining software requires support for both technical aspects and community engagement over decades.
Opening Keynote Lecture
15th Annual ON*VECTOR International Photonics Workshop
Calit2’s Qualcomm Institute
University of California, San Diego
February 29, 2016
The Open Science Data Cloud is a hosted, managed, distributed facility that allows scientists to manage and archive medium and large datasets, provide computational resources to analyze the data, and share the data with colleagues and the public. It currently consists of 6 racks, 212 nodes, 1568 cores and 0.9 PB of storage across 4 locations with 10G networks. Projects using the Open Science Data Cloud include Bionimbus for hosting genomics data and Matsu 2 for providing flood data to disaster response teams. The goal is to build it out over the next 10 years into a small data center for science that can preserve data like libraries and museums preserve collections.
The document provides an overview of research data management for the School of Engineering at the University of Lincoln. It discusses the benefits of research data management, including increased transparency, collaboration, and opportunities for new research. It also outlines some of the support and requirements for research data management from funders and institutions.
The document discusses data management plan requirements for proposals submitted to the U.S. Department of Energy Office of Science for research funding. It provides context on the history of data management policies, outlines the four main requirements for inclusion of a data management plan, and suggests elements that should be included in the plan such as data types/sources, content/format, sharing/preservation, and protection. It also discusses tools like the Public Access Gateway for Energy and Science that can help manage access to research publications and data.
EarthCube Community Webinar 12.19.13: NSF EarthCube Funding Solicitation 13-529EarthCube
The document summarizes an EarthCube community webinar that took place on December 19, 2013. The webinar covered EarthCube updates, the EarthCube test enterprise governance project, and the EarthCube funding solicitation. It provided an agenda for presentations on EarthCube governance, the funding solicitation, and a perspective on EarthCube from the NSF. It also described the goal of EarthCube to create a future state of geosciences cyberinfrastructure and outlined the test enterprise governance project which aims to develop an agile approach to designing an EarthCube system through community engagement.
CCCORE: Cloud Container for Collaborative Research IJECEIAES
Cloud-based research collaboration platforms render scalable, secure and inventive environments that enabled academic and scientific researchers to share research data, applications and provide access to high- performance computing resources. Dynamic allocation of resources according to the unpredictable needs of applications used by researchers is a key challenge in collaborative research environments. We propose the design of Cloud Container based Collaborative Research (CCCORE) framework to address dynamic resource provisioning according to the variable workload of compute and data-intensive applications or analysis tools used by researchers. Our proposed approach relies on–demand, customized containerization and comprehensive assessment of resource requirements to achieve optimal resource allocation in a dynamic collaborative research environment. We propose algorithms for dynamic resource allocation problem in a collaborative research environment, which aim to minimize finish time, improve throughput and achieve optimal resource utilization by employing the underutilized residual resources.
Victoria A. White Head, Computing Division FermilabVideoguy
Global scientific collaborations are essential for particle physics experiments. Fermilab experiments involve over 200 institutions from around the world, with over half of physicists and a third of students coming from outside the US. Fermilab is working to support these collaborations through networks, grid computing, guest scientists programs, and outreach. Advances in information technology and global e-science are profoundly impacting many fields.
The Developing Needs for e-infrastructuresguest0dc425
The document discusses the developing needs for e-infrastructures to support research. It summarizes the key recommendations from the OSI report, which include providing researchers with access to resources, facilities to discover resources, confidence in resource quality and integrity, and assurance of future accessibility. The JISC committee is developing a new strategy to address priorities around integrating data from multiple sources and enabling collaboration across boundaries.
The document discusses Internet2, an advanced networking consortium that operates a 15,000 mile fiber optic network for research and education. It provides very high speed connectivity and collaboration technologies to facilitate large data sharing and frictionless research. Examples are given of life sciences projects utilizing Internet2's high-speed network for genomic research and agricultural applications involving terabytes of satellite and sensor data. The network is expanding to include cloud computing resources and supercomputing centers to enable global-scale distributed scientific computing and collaboration.
Cloud Standards in the Real World: Cloud Standards Testing for DevelopersAlan Sill
Learn about standards studied in the US National Science Foundation Cloud and Autonomic Computing Industry/University Cooperative Research Center Cloud Standards Testing Lab and how you can get involved to extend the successes from these results in your own cloud software settings. Presented at the O'Reilly OSCON 2014 Open Cloud Day.
Video available at https://www.youtube.com/watch?v=eD2h0SqC7tY
Facing data sharing in a heterogeneous research community: lights and shadows...Research Data Alliance
1) RITMARE is a large, multi-institutional Italian marine research project aiming to build a data management infrastructure to facilitate sharing of data across research communities.
2) Subproject 7 of RITMARE seeks to design an IT system that enables interoperability and data exchange without forcing a single model or centralization. Efforts have included developing a data policy, collecting researcher requirements, and creating tools and services.
3) While progress has been made in establishing nodes providing access to data and metadata, uptake by researchers has been less than expected due to insufficient technical support, lack of data-related incentives, and developing a data policy after the project began rather than at the outset.
OSFair2017 Workshop | The European Open Science Cloud Pilot Open Science Fair
Brian Matthews presents the European Open Science Cloud (EOSC) and the EOSCpilot | OSFair2017 Workshop
Workshop title: How FAIR friendly is your data catalogue?
Workshop overview:
This workshop will build upon the work planned by the EOSCpilot data interoperability task and the BlueBridge workshop held on April 3 at the RDA meeting. We will investigate common mechanisms for interoperation of data catalogues that preserve established community standards, norms and resources, while simplifying the process of being/becoming FAIR. Can we have a simple interoperability architecture based on a common set of metadata types? What are the minimum metadata requirements to expose FAIR data to EOSC services and EOSC users?
DAY 3 - PARALLEL SESSION 6 & 7
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
Extending Globus into a Site-wide Automated Data Infrastructure.pdfGlobus
The Rosalind Franklin Institute hosts a variety of scientific instruments, which allow us to capture a multifaceted and multilevel view of biological systems, generating around 70 terabytes of data a month. Distributed solutions, such as Globus and Ceph, facilitates storage, access, and transfer of large amount of data. However, we still must deal with the heterogeneity of the file formats and directory structure at acquisition, which is optimised for fast recording, rather than for efficient storage and processing. Our data infrastructure includes local storage at the instruments and workstations, distributed object stores with POSIX and S3 access, remote storage on HPCs, and taped backup. This can pose a challenge in ensuring fast, secure, and efficient data transfer. Globus allows us to handle this heterogeneity, while its Python SDK allows us to automate our data infrastructure using Globus microservices integrated with our data access models. Our data management workflows are becoming increasingly complex and heterogenous, including desktop PCs, virtual machines, and offsite HPCs, as well as several open-source software tools with different computing and data structure requirements. This complexity commands that data is annotated with enough details about the experiments and the analysis to ensure efficient and reproducible workflows. This talk explores how we extend Globus into different parts of our data lifecycle to create a secure, scalable, and high performing automated data infrastructure that can provide FAIR[1,2] data for all our science.
1. https://doi.org/10.1038/sdata.2016.18
2. https://www.go-fair.org/fair-principles
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Globus Compute with Integrated Research Infrastructure (IRI) workflowsGlobus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and I will give a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Reactive Documents and Computational Pipelines - Bridging the GapGlobus
As scientific discovery and experimentation become increasingly reliant on computational methods, the static nature of traditional publications renders them progressively fragmented and unreproducible. How can workflow automation tools, such as Globus, be leveraged to address these issues and potentially create a new, higher-value form of publication? LivePublication leverages Globus’s custom Action Provider integrations and Compute nodes to capture semantic and provenance information during distributed flow executions. This information is then embedded within an RO-crate and interfaced with a programmatic document, creating a seamless pipeline from instruments, to computation, to publication.
Innovating Inference at Exascale - Remote Triggering of Large Language Models...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Implementations of Fused Deposition Modeling in real worldEmerging Tech
The presentation showcases the diverse real-world applications of Fused Deposition Modeling (FDM) across multiple industries:
1. **Manufacturing**: FDM is utilized in manufacturing for rapid prototyping, creating custom tools and fixtures, and producing functional end-use parts. Companies leverage its cost-effectiveness and flexibility to streamline production processes.
2. **Medical**: In the medical field, FDM is used to create patient-specific anatomical models, surgical guides, and prosthetics. Its ability to produce precise and biocompatible parts supports advancements in personalized healthcare solutions.
3. **Education**: FDM plays a crucial role in education by enabling students to learn about design and engineering through hands-on 3D printing projects. It promotes innovation and practical skill development in STEM disciplines.
4. **Science**: Researchers use FDM to prototype equipment for scientific experiments, build custom laboratory tools, and create models for visualization and testing purposes. It facilitates rapid iteration and customization in scientific endeavors.
5. **Automotive**: Automotive manufacturers employ FDM for prototyping vehicle components, tooling for assembly lines, and customized parts. It speeds up the design validation process and enhances efficiency in automotive engineering.
6. **Consumer Electronics**: FDM is utilized in consumer electronics for designing and prototyping product enclosures, casings, and internal components. It enables rapid iteration and customization to meet evolving consumer demands.
7. **Robotics**: Robotics engineers leverage FDM to prototype robot parts, create lightweight and durable components, and customize robot designs for specific applications. It supports innovation and optimization in robotic systems.
8. **Aerospace**: In aerospace, FDM is used to manufacture lightweight parts, complex geometries, and prototypes of aircraft components. It contributes to cost reduction, faster production cycles, and weight savings in aerospace engineering.
9. **Architecture**: Architects utilize FDM for creating detailed architectural models, prototypes of building components, and intricate designs. It aids in visualizing concepts, testing structural integrity, and communicating design ideas effectively.
Each industry example demonstrates how FDM enhances innovation, accelerates product development, and addresses specific challenges through advanced manufacturing capabilities.
Support en anglais diffusé lors de l'événement 100% IA organisé dans les locaux parisiens d'Iguane Solutions, le mardi 2 juillet 2024 :
- Présentation de notre plateforme IA plug and play : ses fonctionnalités avancées, telles que son interface utilisateur intuitive, son copilot puissant et des outils de monitoring performants.
- REX client : Cyril Janssens, CTO d’ easybourse, partage son expérience d’utilisation de notre plateforme IA plug & play.
Scaling Connections in PostgreSQL Postgres Bangalore(PGBLR) Meetup-2 - MydbopsMydbops
This presentation, delivered at the Postgres Bangalore (PGBLR) Meetup-2 on June 29th, 2024, dives deep into connection pooling for PostgreSQL databases. Aakash M, a PostgreSQL Tech Lead at Mydbops, explores the challenges of managing numerous connections and explains how connection pooling optimizes performance and resource utilization.
Key Takeaways:
* Understand why connection pooling is essential for high-traffic applications
* Explore various connection poolers available for PostgreSQL, including pgbouncer
* Learn the configuration options and functionalities of pgbouncer
* Discover best practices for monitoring and troubleshooting connection pooling setups
* Gain insights into real-world use cases and considerations for production environments
This presentation is ideal for:
* Database administrators (DBAs)
* Developers working with PostgreSQL
* DevOps engineers
* Anyone interested in optimizing PostgreSQL performance
Contact info@mydbops.com for PostgreSQL Managed, Consulting and Remote DBA Services
Understanding Insider Security Threats: Types, Examples, Effects, and Mitigat...Bert Blevins
Today’s digitally connected world presents a wide range of security challenges for enterprises. Insider security threats are particularly noteworthy because they have the potential to cause significant harm. Unlike external threats, insider risks originate from within the company, making them more subtle and challenging to identify. This blog aims to provide a comprehensive understanding of insider security threats, including their types, examples, effects, and mitigation techniques.
Advanced Techniques for Cyber Security Analysis and Anomaly DetectionBert Blevins
Cybersecurity is a major concern in today's connected digital world. Threats to organizations are constantly evolving and have the potential to compromise sensitive information, disrupt operations, and lead to significant financial losses. Traditional cybersecurity techniques often fall short against modern attackers. Therefore, advanced techniques for cyber security analysis and anomaly detection are essential for protecting digital assets. This blog explores these cutting-edge methods, providing a comprehensive overview of their application and importance.
Best Practices for Effectively Running dbt in Airflow.pdfTatiana Al-Chueyr
As a popular open-source library for analytics engineering, dbt is often used in combination with Airflow. Orchestrating and executing dbt models as DAGs ensures an additional layer of control over tasks, observability, and provides a reliable, scalable environment to run dbt models.
This webinar will cover a step-by-step guide to Cosmos, an open source package from Astronomer that helps you easily run your dbt Core projects as Airflow DAGs and Task Groups, all with just a few lines of code. We’ll walk through:
- Standard ways of running dbt (and when to utilize other methods)
- How Cosmos can be used to run and visualize your dbt projects in Airflow
- Common challenges and how to address them, including performance, dependency conflicts, and more
- How running dbt projects in Airflow helps with cost optimization
Webinar given on 9 July 2024
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
Details of description part II: Describing images in practice - Tech Forum 2024BookNet Canada
This presentation explores the practical application of image description techniques. Familiar guidelines will be demonstrated in practice, and descriptions will be developed “live”! If you have learned a lot about the theory of image description techniques but want to feel more confident putting them into practice, this is the presentation for you. There will be useful, actionable information for everyone, whether you are working with authors, colleagues, alone, or leveraging AI as a collaborator.
Link to presentation recording and transcript: https://bnctechforum.ca/sessions/details-of-description-part-ii-describing-images-in-practice/
Presented by BookNet Canada on June 25, 2024, with support from the Department of Canadian Heritage.
Quantum Communications Q&A with Gemini LLM. These are based on Shannon's Noisy channel Theorem and offers how the classical theory applies to the quantum world.
Sustainability requires ingenuity and stewardship. Did you know Pigging Solutions pigging systems help you achieve your sustainable manufacturing goals AND provide rapid return on investment.
How? Our systems recover over 99% of product in transfer piping. Recovering trapped product from transfer lines that would otherwise become flush-waste, means you can increase batch yields and eliminate flush waste. From raw materials to finished product, if you can pump it, we can pig it.
The DealBook is our annual overview of the Ukrainian tech investment industry. This edition comprehensively covers the full year 2023 and the first deals of 2024.
Measuring the Impact of Network Latency at TwitterScyllaDB
Widya Salim and Victor Ma will outline the causal impact analysis, framework, and key learnings used to quantify the impact of reducing Twitter's network latency.
UiPath Community Day Kraków: Devs4Devs ConferenceUiPathCommunity
We are honored to launch and host this event for our UiPath Polish Community, with the help of our partners - Proservartner!
We certainly hope we have managed to spike your interest in the subjects to be presented and the incredible networking opportunities at hand, too!
Check out our proposed agenda below 👇👇
08:30 ☕ Welcome coffee (30')
09:00 Opening note/ Intro to UiPath Community (10')
Cristina Vidu, Global Manager, Marketing Community @UiPath
Dawid Kot, Digital Transformation Lead @Proservartner
09:10 Cloud migration - Proservartner & DOVISTA case study (30')
Marcin Drozdowski, Automation CoE Manager @DOVISTA
Pawel Kamiński, RPA developer @DOVISTA
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
09:40 From bottlenecks to breakthroughs: Citizen Development in action (25')
Pawel Poplawski, Director, Improvement and Automation @McCormick & Company
Michał Cieślak, Senior Manager, Automation Programs @McCormick & Company
10:05 Next-level bots: API integration in UiPath Studio (30')
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
10:35 ☕ Coffee Break (15')
10:50 Document Understanding with my RPA Companion (45')
Ewa Gruszka, Enterprise Sales Specialist, AI & ML @UiPath
11:35 Power up your Robots: GenAI and GPT in REFramework (45')
Krzysztof Karaszewski, Global RPA Product Manager
12:20 🍕 Lunch Break (1hr)
13:20 From Concept to Quality: UiPath Test Suite for AI-powered Knowledge Bots (30')
Kamil Miśko, UiPath MVP, Senior RPA Developer @Zurich Insurance
13:50 Communications Mining - focus on AI capabilities (30')
Thomasz Wierzbicki, Business Analyst @Office Samurai
14:20 Polish MVP panel: Insights on MVP award achievements and career profiling
INDIAN AIR FORCE FIGHTER PLANES LIST.pdfjackson110191
These fighter aircraft have uses outside of traditional combat situations. They are essential in defending India's territorial integrity, averting dangers, and delivering aid to those in need during natural calamities. Additionally, the IAF improves its interoperability and fortifies international military alliances by working together and conducting joint exercises with other air forces.
Choose our Linux Web Hosting for a seamless and successful online presencerajancomputerfbd
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The Department of Energy's Integrated Research Infrastructure (IRI)
1. The Department of Energy’s
Integrated Research Infrastructure (IRI)
GlobusWorld, Chicago, Illinois
Ben Brown, Director, Facilities Division, ASCR
May 7, 2024
Energy/gov/science
2. Energy.gov/science
The imperative of integration
DOE’s Research Infrastructure
Integration … what does it really mean?
IRI: is it just the Grid, or something more?
Researchers and their data
IRI = Integrated Research Infrastructure
Computing = high performance computing, data, and networking
3. Energy.gov/science
Energy.gov/science
Our Mission:
Deliver scientific discoveries
and major scientific tools to
transform our understanding
of nature and advance the
energy, economic, and
national security of the
United States.
More than 34,000 researchers
supported at more than 300
institutions and 17 DOE
national laboratories
More than 39,500
users of 28 Office of
Science scientific
user facilities
$8.24B
FY 2024 enacted
Steward 10 of the
17 DOE national
laboratories
3
5. Energy.gov/science
DOE is a system of independent national laboratories
It is one of the happy incidents of the federal system that
a single courageous state may, if its citizens choose,
serve as a laboratory; and try novel social and economic
experiments without risk to the rest of the country.
Justice Louis D. Brandeis, 1932
8. The ASCR Facilities enterprise thrives in partnerships that
accelerate discovery and innovation.
Argonne Leadership Computing Facility
Energy Sciences Network
Oak Ridge Leadership Computing Facility
National Energy Research Scientific Computing Center
High Performance Data Facility
18. Energy.gov/science
Linking distributed resources is becoming paramount to
modern collaborative science, to integrated science.
Accelerating discovery & innovation
Democratizing access
Drawing new talent
Advancing open science
The challenges of our time call upon DOE and its national
laboratories to be an open innovation ecosystem.
18
19. Energy.gov/science
DOE’s Integrated Research Infrastructure (IRI) Vision:
To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and
securely in novel ways to radically accelerate discovery and innovation
New modes of
integrated science
Researchers
Edge
Sensors
Computing
Testbeds
Experimental and Observational
User Facilities
Advanced
Computing
Advanced
Networking
AI Tools
Digital Twins
High Performance
Data Facility
Cloud
Computing
Software
Data Management
Data Repositories
PuRE Data Assets
AI-enabled insight from
integrating vast data sources
Rapid data analysis and
steering of experiments
Novel workflows using
multiple user facilities
Software and
Applications
Local
Campus
Computing
19
20. Energy.gov/science
DOE’s Integrated Research Infrastructure (IRI) Vision:
To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and
securely in novel ways to radically accelerate discovery and innovation
20
New modes of
integrated science
Researchers
Edge
Sensors
Computing
Testbeds
Experimental and Observational
User Facilities
Advanced
Computing
Advanced
Networking
AI Tools
Digital Twins
High Performance
Data Facility
Cloud
Computing
Software
Data Management
Data Repositories
PuRE Data Assets
AI-enabled insight from
integrating vast data sources
Rapid data analysis and
steering of experiments
Novel workflows using
multiple user facilities
Software and
Applications
Local
Campus
Computing
The IRI Vision:
It’s about empowering people.
It’s about data.
22. Energy.gov/science
The IRI Blueprint Activity created a framework for IRI implementation
User experience practice will ensure relentless attention to user
perspectives and needs through requirements gathering,user-
centric (co)-design,continuous feedback,and other means.
Resource co-operations practice is focused on creating new modes
of cooperation,collaboration,co-scheduling,and joint planning
across facilities and DOE programs.
Cybersecurity and federated access practice is focused on
creating novel solutions that enable seamless scientific collaboration
within a secure and trusted IRI ecosystem.
Workflows,interfaces,and automation practice is focused on
creating novel solutions that facilitate the dynamic assembly of
components across facilities into end-to-end IRI pipelines.
Scientific data life cycle practice is focused on ensuring that users
can manage their data and metadata across facilities from inception
to curation,archiving,dissemination,and publication.
Portable/scalable solutions practice is focused on ensuring that
transitions can be made across heterogeneous facilities (portability)
and from smaller to larger resources (scalability).
Time-sensitive pattern has urgency,
requiring real-time or end-to-end
performance with high reliability, e.g.,for
timely decision-making,experiment
steering, and virtual proximity.
Data integration-intensive pattern
requires combining and analyzing data
from multiple sources, e.g., sites,
experiments, and/or computational runs.
Long-term campaign pattern requires
sustained access to resources over a long
period to accomplish a well-defined
objective.
IRI Science Patterns (3) IRI Practice Areas (6)
Convened over 150 DOE national laboratory experts from all 28 SC
user facilities across 13 national laboratories to consider the
technological, policy, and sociological challenges to implementing IRI.
22
23. Energy.gov/science
Cross-facility partnerships are yielding early results
LBNL’s Superfacility project, ORNL’s INTERSECT project, and ANL’s NEXUS project, and a several other collaborations, are
active incubators for IRI design patterns. Here are a few cherry-picked highlights from the Supercomputing 23 conference
(November 12-17, 2023 in Denver):
FES: DIII-D user facility
• Has worked with ALCF to run post-shot analysis on Polaris at 16X the prior resolution and a completed the analysis between shots,
allowing the analysis result to be considered with every shot instead of every other shot.
• Has worked with NERSC to automate rapid plasma state reconstruction on Perlmutter. Previously these reconstructions were handcrafted
with 4,000 produced in the 15 years between 2008-22; they created over 20,000 automated reconstructions in the first 6 months.
BES: x-ray light sources
• LCLS is streaming data to NERSC (Perlmutter) and OLCF (Frontier) via ESnet to achieve wall clock speedups of data analysis; what would have
taken ~ 30 minutes at LCLS is now reduced to 5 minutes, fast enough to make adjustments between experiments.
• APS has worked with ALCF and has multiple beamlines running analyses in production on Polaris: X-ray Photon Correlation Spectroscopy, Laue
Depth reconstructions, X-ray Ptychography, High-Energy Diffraction Microscopy.
BES: electron microscopy
• The National Center for Electron Microscopy at the Molecular Foundry regularly streams data from their high-resolution electron microscope
directly into NERSC's compute nodes for immediate processing; this process is 14x faster than previous file transfer methods with a more
consistent transfer time.
24. Energy.gov/science
IRI Program value propositions (authored by the SC IRI Coordination Group)
For the taxpayer, for all of us:
Achieve greater productivity and avoid duplication of effort.
For the researcher:
Achieve transformational reduction in time to insight and complexity.
For program/RI/institutional leaders:
Achieve greater effectiveness and efficiency in coordinating efforts;
Achieve more nimble solutions than would be possible alone;
Gain leverage with partners who possess like requirements;
Avoid single points of failure; and
Gain access to expertise and shared experience.
24
25. Energy.gov/science
Vision Strategy Implement
Timeline of IRI Program Development
Jan 2020 Jan 2024
Jan 2022 Jan 2023
FY 2024 PBR advances IRI and the
High Performance Data Facility
SC IRI Blueprint Activity launch
IRI Blueprint Activity results
FY 2021 President’s Budget Request
includes Integrated Computation
and Data Infrastructure Initiative
ASCR IRI Task Force launch
Jan 2021
ASCR IRI Task Force report
IRI Program Development
HPDF
Selection
25
GO
Standup of the IRI Program is a DOE FY24-25 Agency Priority Goal
26. Energy.gov/science
1. Invest in IRI foundational infrastructure
2. Stand up the IRI Program governance and FY24 workstreams
3. Bring IRI projects into formal coordination
4. Deploy an IRI Science Testbed across the ASCR Facilities
These are all connected.
These are each essential.
IRI Program launch is a DOE FY24-25 Agency Priority Goal.
ASCR is implementing IRI through these four major elements.
1
2
3
4
26
28. • First-of-its-kind DOE Office of Science user facility
• Distributed operations model will be essential to long-term success and
required performance levels
• Project structure integrated with JLab and LBNL staff
HPDF: Meeting the Greatest Needs
The DOE envisions a revolutionary ecosystem – the
Integrated Research Infrastructure – to deliver seamless,
secure interoperability across National Laboratory facilities
The 2023 IRI Architecture Blueprint Activity identified three
broad science patterns that demand research infrastructure
interoperability:
• Time-sensitive patterns
• Data-integration-intensive patterns
• Long-term campaign patterns
HPDF will enable analysis, preservation, and accessibility to the staggering
amounts of experimental data produced by SC facilities
Our mission:
To enable
and accelerate
scientific
discovery
by delivering
state-of-the-art
data
management
infrastructure,
capabilities,
and tools
29. Data science requires curated and annotated data that adheres to
FAIR principles, and data reuse will be an HPDF metric. Office of
Scientific and Technical Information services will complement HPDF
to provide full life cycle coverage.
Flexible & Full Life Cycle Coverage
• Management – A dynamic and scalable data
management infrastructure integrated with
the DOE computing ecosystem
• Capture – Dynamically allocatable data storage
and edge computing at the point of
generation
• Staging – Dynamic placement of data in
proximity to appropriate computing for
reduction, analysis, and processing
• Archiving – Extreme-scale distributed archiving
and cataloging of data with FAIR principles –
findability, accessibility, interoperability, and
reusability
• Processing – Resources for workflow and
automation for processing and analyses
of data at scale
Preserve
Long-term data
curation and archival
Transfer
Move and manage data
and dynamic data
streams
Publish
Fulfill FAIR principles
for scientific data
Clean and Process
Scalable scientific and
AI/ML workflows
Acquire and Prepare
Ingest experimental and
observational and
reprocessed data using
standard APIs
User Facilities
Science
Gateways Raw &
Derived Data
Hub
Analyze
Share
Refine
Release
Tiered
Storage
Compute
ESnet
30. Hub & Spoke Architecture: Seamless Service
• HPDF distributed infrastructure will
be designed to maximize planned
availability and resilience
• Resources will be optimized for
data processing and analysis
• Partnering with spoke sites will provide
seamless data life cycle services to
scientific users worldwide
• Working with IRI ensures a secure,
high-performance mesh data fabric that
enables data and workloads to flow
freely among the hub, spokes, and HPC
facilities
• Pilot activities and partnerships will help
refine the design as hub software and
hardware technology evolve
Community Structure
How strongly governed or united a community is
around a set of policies or goals for its data products
Organizational Structure
How the organization or institution is designed to
support their user community’s full data life cycle.
Funding Model(s)
How the spoke is funded, for what lifespan, and how
end users are supported (sub-awards, allocations,
etc.) to leverage its resources
Size
The size of a particular spoke will be shaped by the
confluence of anticipated user base, data volume
and velocity, and resources (staff, compute)
Data/Compute Resources
The types and extent of technical functionality a spoke supports for its user community.
Facets of Spoke Design
31. Energy.gov/science
Quotes from participants at one of the last Exascale Computing Project
meetings, reflecting on the journey (with some paraphrasing)
“Integration is not optional anymore.”
“ECP was the time to challenge assumptions … [and embark on a] holistic rethinking and
restructuring.”
“Be technically ambitious.”
“Dare to try, no matter what, because business as usual is almost guaranteed to fail.”
“You have to build not just the software, but also the communities around the software.”
“Invest seriously in automation.”
“For a scientist, code is not their main focus; it is a tool…. But nobody wants their code to
break.”
“In order to make progress, we developers have to be able to drop [support for old things].”
32. Energy.gov/science
Summing up where we stand today with IRI
IRI is envisioned as a long-term program, with a formal governance structure, to frame rich
partnerships in a seamless computing and data ecosystem for researchers.
The ASCR Facilities (ALCF, ESnet, NERSC, OLCF) are nucleating the IRI governance. Globus is
an important partner.
HPDF is a new major project to create a new DOE User Facility with a budget of $300M; the
project is just getting going.
In a deep sense, IRI is about creating – but not inventing from scratch –
a software (and middleware) ecosystem.
Leverage and lessons learned from well-executed and well-stewarded software and
middleware (like Globus!) are essential to developing a robust IRI.
Software is infrastructure!