About

Thomas J. Hacker, Ph.D., is a Professor of Computer & Information Technology at Purdue University in West Lafayette, Indiana. His research interests encompass cloud computing, operating systems, computer networking, high-performance computing, and cyber infrastructure. He holds a B.S. in Physics and a B.S. in Computer Science from Oakland University, and both an M.S. and Ph.D. in Computer Science & Engineering from the University of Michigan. Throughout his career, he has received numerous awards including the NSF CAREER Award, Purdue Seed for Success Awards, and recognition as a Purdue Faculty Scholar. Dr. Hacker has contributed to the academic community through his publications, book chapters, and conference presentations, focusing on advancing research infrastructure, cloud services, and data analysis in various engineering and computing domains.

Research topics

• Computer Science
• Computer Security
• Operating system
• World Wide Web
• Computer architecture
• Parallel computing

Selected publications

• EL2W: Extended Layer 2 Services for Bare-Metal Provisioning Over WAN

  2023-07-01

  article1st authorCorresponding

  Researchers are embracing deep learning in various interdisciplinary research domains, recognizing undeniable benefits offered by deep neural networks. However, in order to meet the substantial computational demands for processing deep learning models, researchers extensively rely on cloud servers. Nevertheless, the shared nature of cloud servers encourages research labs and facilities to establish private clouds, ensuring exclusive access to computational resources and safeguarding data privacy. Creating a private cloud from bare metal presents challenges with existing provisioning solutions. These solutions not only come with a set of complex installation and configuration steps but are also limited to a constrained local Ethernet broadcast domain for network loading, which may pose unforeseen difficulties and risks for researchers who do not specialize in computing. To address these issues, this paper introduces EL2W, Extended Layer 2 services to Wide area networks (WAN), a novel approach we developed following Infrastructure-as-Code (IaC) principles. EL2W aims to help automate the system installation procedure by reducing the repetitive configurations and setups using Infrastructure-as-Code based scripts and codes. In addition, EL2W can securely expand an Ethernet network’s logical and functional extent beyond the current physical limitations of Ethernet layer 2 networks. We describe the implementation and architecture of a remote bare metal provisioning system built upon secure extended layer 2 networks. Experimental results demonstrate the capability of EL2W for establishing a secure layer 2 connection to provide essential bare metal provisioning services, as well as the effectiveness of a local proxy cache server to reduce the operating system loading time.

  PublisherDOI

• Reflexive Lehrer*innenbildung. Versuch einer Lokalisierung in pragmatischer Absicht

  Verlag Julius Klinkhardt eBooks · 2022-01-01 · 7 citations

  book-chapterOpen access1st authorCorresponding

  Reflexion erscheint in der Lehrer*innenbildung als Inbegriff des Anzustrebenden, dessen Steigerung in jedem Fall ein Gewinn wäre. Allerdings bricht sich der Reflexionsoptimismus nicht nur an der strittigen Frage der Wirksamkeit der Reflexion. Die verbreitete Nobilitierung der Reflexivität als Selbstzweck, die hohen Erwartungen an die Realisierung höchster Reflexionsniveaus, die Verdichtung von Reflexionsanforderungen in der Moderne und die Ausblendung ihrer Grenzen und Nebenwirkungen werfen zudem die Frage auf, ob Reflexion in der Lehrer*innenbildung nicht unter der Hand zu einer quasi-technologischen Formel zur Sicherung einer Gewissheitspose an den Grenzen des Mach-, Plan- und Steuerbaren gerät. Pragmatisch-realistisch gesehen wäre Reflexion als das zu konzeptualisieren, was sie im besten Sinne sein kann: eine soziale Praxis. (DIPF/Orig.)

  PublisherOA PDFDOI

• Zur Ethik in pädagogischen Beziehungen – eine Einführung

  Verlag Julius Klinkhardt eBooks · 2022-08-01 · 1 citations

  book-chapterOpen access

  Berndt, Constanze [Hrsg.]; Häcker, Thomas [Hrsg.]; Walm, Maik [Hrsg.]: Ethik in pädagogischen Beziehungen. Bad Heilbrunn : Verlag Julius Klinkhardt 2022, S. 9-29 Pädagogische Teildisziplin: Allgemeine Erziehungswissenschaft; Bildungs- und Erziehungsphilosophie;

  PublisherOA PDFDOI

• OpenIaC: open infrastructure as code - the network is my computer

  Journal of Cloud Computing Advances Systems and Applications · 2022 · 15 citations

  • Computer Science
  • Computer Science
  • Computer Security

  Abstract Modern information systems are built fron a complex composition of networks, infrastructure, devices, services, and applications, interconnected by data flows that are often private and financially sensitive. The 5G networks, which can create hyperlocalized services, have highlighted many of the deficiencies of current practices in use today to create and operate information systems. Emerging cloud computing techniques, such as Infrastructure-as-Code (IaC) and elastic computing, offer a path for a future re-imagining of how we create, deploy, secure, operate, and retire information systems. In this paper, we articulate the position that a comprehensive new approach is needed for all OSI layers from layer 2 up to applications that are built on underlying principles that include reproducibility, continuous integration/continuous delivery, auditability, and versioning. There are obvious needs to redesign and optimize the protocols from the network layer to the application layer. Our vision seeks to augment existing Cloud Computing and Networking solutions with support for multiple cloud infrastructures and seamless integration of cloud-based microservices. To address these issues, we propose an approach named Open Infrastructure as Code (OpenIaC), which is an attempt to provide a common open forum to integrate and build on advances in cloud computing and blockchain to address the needs of modern information architectures. The main mission of our OpenIaC approach is to provide services based on the principles of Zero Trust Architecture (ZTA) among the federation of connected resources based on Decentralized Identity (DID). Our objectives include the creation of an open-source hub with fine-grained access control for an open and connected infrastructure of shared resources (sensing, storage, computing, 3D printing, etc.) managed by blockchains and federations. Our proposed approach has the potential to provide a path for developing new platforms, business models, and a modernized information ecosystem necessary for 5G networks.

  PublisherOA PDFDOI

• Machine-Supported Bridge Inspection Image Documentation Using Artificial Intelligence

  Transportation Research Record Journal of the Transportation Research Board · 2022-12-06 · 7 citations

  article

  The purpose of a routine bridge inspection is to assess the physical and functional condition of a bridge according to a regularly scheduled interval. The Federal Highway Administration (FHWA) requires these inspections to be conducted at least every 2 years. Inspectors use simple tools and visual inspection techniques to determine the conditions of both the elements of the bridge structure and the bridge overall. While in the field, the data is collected in the form of images and notes; after the field work is complete, inspectors need to generate a report based on these data to document their findings. The report generation process includes several tasks: (1) evaluating the condition rating of each bridge element according to FHWA Recording and Coding Guide for Structure Inventory and Appraisal of the Nation’s Bridges; and (2) updating and organizing the bridge inspection images for the report. Both of tasks are time-consuming. This study focuses on assisting with the latter task by developing an artificial intelligence (AI)-based method to rapidly organize bridge inspection images and generate a report. In this paper, an image organization schema based on the FHWA Recording and Coding Guide for the Structure Inventory and Appraisal of the Nation’s Bridges and the Manual for Bridge Element Inspection is described, and several convolutional neural network-based classifiers are trained with real inspection images collected in the field. Additionally, exchangeable image file (EXIF) information is automatically extracted to organize inspection images according to their time stamp. Finally, the Automated Bridge Image Reporting Tool (ABIRT) is described as a browser-based system built on the trained classifiers. Inspectors can directly upload images to this tool and rapidly obtain organized images and associated inspection report with the support of a computer which has an internet connection. The authors provide recommendations to inspectors for gathering future images to make the best use of this tool.

  PublisherDOI

• Multioutput Image Classification to Support Postearthquake Reconnaissance

  Journal of Performance of Constructed Facilities · 2022-10-12 · 4 citations

  article

  After hazard events, large numbers of images are collected by reconnaissance teams to document the post-event state of structures, and to assess their performance and improve design procedures and codes. The majority of these data are captured as images and manually labeled. This highly repetitive task requires considerable domain expertise and time. Advances in deep learning have enabled researchers to rapidly classify reconnaissance images. Thus far, these classification methods are limited to a simple classification schema in which the classes are all either mutually exclusive or independent. To date, an efficient classification system of a complex schema containing many classes arranged in a multi-level hierarchical structure is not available to support earthquake reconnaissance. To address this gap, this paper introduces a comprehensive classification schema and a multi-output deep convolutional neural network (DCNN) model for rapid postearthquake image classification. In contrast to past work, herein a single multi-output DCNN classification model with a hierarchy-aware prediction was trained to enable the rapid organization of images. The performance of the proposed multi-output model was validated through comparisons with multi-label and multi-class models using an F1-score. As result, the multi-output model outperformed other models. Then, the multi-output model was deployed to a web-based platform called the Automated Reconnaissance Image Organizer, which can be used to easily organize earthquake reconnaissance images.

  PublisherDOI

• Building the Research Innovation Workforce: Challenges and Recommendations from a Virtual Workshop to Advance the Research Computing Community

  Practice and Experience in Advanced Research Computing · 2022-07-08 · 1 citations

  articleOpen access1st authorCorresponding

  The workforce for research computing, cyberinfrastructure, and data analytics is a complex global ecosystem comprised of workers across academia, national laboratories, and industry. To explore the underlying factors that affect the growth and vitality of this workforce ecosystem, we conducted an NSF funded virtual workshop during the third quarter of 2020 attended by 100 participants. The workshop identified challenges affecting the workforce pipeline and ecosystem and generated recommendations to help address these challenges. This paper provides a summary of the workshop, challenges, and recommendations.

  PublisherOA PDFDOI

• OpenIaC: Open Infrastructure as Code - The Network is My Computer

  Research Square (Research Square) · 2021 · 5 citations

  • Computer Science
  • Computer Science
  • Computer Security

  Abstract Modern information systems are built fron a complex composition of networks, infrastructure, devices, services, and applications, interconnected by data flows that are often private and financially sensitive. The 5G networks, which can create hyperlocalized services, have highlighted many of the deficiencies of current practices in use today to create and operate information systems. Emerging cloud computing techniques, such as Infrastructure-as-Code (IaC) and elastic computing, o↵er a path for a future re-imagining of how we create, deploy, secure, operate, and retire information systems. In this paper, we articulate the position that a comprehensive new approach is needed for all OSI layers from layer 2 up to applications that are built on underlying principles that include reproducibility, continuous integration/continuous delivery, auditability, and versioning. There are obvious needs to redesign and optimize the protocols from the network layer to the application layer. Our vision seeks to augment existing Cloud Computing and Networking solutions with support for multiple cloud infrastructures and seamless integration of cloud-based microservices. To address these issues, we propose an approach named Open Infrastructure as Code (OpenIaC), which is an attempt to provide a common open forum to integrate and build on advances in cloud computing and blockchain to address the needs of modern information architectures. The main mission of our OpenIaC approach is to provide services based on the principles of Zero Trust Architecture (ZTA) among the federation of connected resources based on Decentralized Identity (DID). Our objectives include the creation of an open-source hub with fine-grained access control for an open and connected infrastructure of shared resources (sensing, storage, computing, 3D printing, etc.) managed by blockchains and federations. Our proposed approach has the potential to provide a path for developing new platforms, business models, and a modernized information ecosystem necessary for 5G networks.

  PublisherOA PDFDOI

• The “Geddes” Composable Platform - An Evolution of Community Clusters for a Composable World

  2020-11-01 · 2 citations

  article

  New usage patterns of computing for research have emerged that rely on the availability of flexible, elastic, and highly specialized services, that may not be well suited to traditional batch HPC. A new approach that updates and evolves the research computing ecosystem is needed to respond to these needs. This new model, a Kubernetes-based "Community Composable Platform", builds upon Purdue's Community Cluster program to provide cost effective, highly responsive, and customizable composable computing solutions for domain science and education in a variety of communities.

  PublisherDOI

• Exploring the Use of Virtual Machines and Virtual Clusters for High Performance Computing Education.

  2020-09-04

  articleOpen access1st authorCorresponding

  High performance computing systems have been based on commodity computing hardware since the introduction of Beowulf systems in the mid-1990's. The emergence of virtualization and cloud computing technologies now make it possible to build high performance computing cluster systems across a collection of virtual machines. This paper will explore the pedagogical and technological issues involved in the use of virtualization and cloud computing technologies for HPC education, focusing on: mixed use of physical and virtual computing environments; high performance networking fabrics; pedagogical limitations of virtual and cloud computing; the development of an effective teaching laboratory for virtual clustering; and the performance and reliability constraints of a mixed virtual cluster environment. The paper will describe the use of virtualization software, specifically Xen, OpenVZ, and VMware, and an assessment of the viability of the Eucalyptus, NIMBUS, and OpenNebula cloud computing systems for use for virtual clusters for HPC education. This paper explores these questions, and discusses the issues involved in the adoption of virtualization and cloud computing technologies for HPC education, and describes experiences and lessons learned from the use of four virtualization and cloud computing systems: Eucalyptus, OpenNebula, NIMBUS, and VMware.

  PublisherOA PDFDOI

Recent grants

• CAREER: Aon - An Integrative Approach to Petascale Fault Tolerance

  NSF · $409k · 2010–2017

Frequent coauthors

• Tomasz Włodarczyk

  18 shared

• Raymond A. Hansen

  Purdue University System

  18 shared

• Alejandra J. Magana

  Bridge University

  18 shared

• Oluwatosin Alabi

  Purdue University West Lafayette

  16 shared

• Manaz Taleyarkhan

  Purdue University West Lafayette

  16 shared

• Jason St. John

  Fermi National Accelerator Laboratory

  11 shared

• Shirley J. Dyke

  Purdue University West Lafayette

  7 shared

• Brian D. Athey

  University of Michigan–Ann Arbor

  7 shared

Awards & honors

• Purdue Seed for Success Award (2013)
• Faculty Fellow, Purdue Polytechnic Institute (2013)
• Purdue Seed for Success Award (2012)
• ASEE Information Systems Division Best Paper Award (2012)
• Purdue University Faculty Scholar (2012)