The 2025/2026 Academic Year deadline is September 30. Graduate and undergraduate students enrolled within the University of Maine System are eligible to apply for up to $150 in CORE Voucher funding that may be used on any CORE service.  A list of CORE services can be found HERE and are available to students studying in any discipline.  Each applicant needs to include a faculty advisor as a contact on their application who can verify the applicant’s project plan.

Funds will be available on October 13, 2025 and must be used no later than May 31, 2026. Funds will not be available after 5/31/26. Retroactive requests, reimbursements, and extensions will not be considered. CORE Vouchers are not applicable to Freezer Program orders. Awards are non-transferable. One application per applicant per academic year.

CORE serves as 91����’s central repository for major research equipment and facilities, for the purpose of advancing research and development. 

This funding is made available by the Office of the Vice President for Research and Dean of the Graduate School, Experiential Programs Innovation Central (EPIC), and the Hunter Family Fund.

ARCSIM has worked to bring the University of Maine System state of the art computing systems and the power to help drive research and education in the state. While ARCSIM is able to meet the needs of the system with its extensive computing infrastructure, installed at the University of Maine in Neville Hall, including servers, networking infrastructure, virtual machines, generators and more, ARCSIM is continually making efforts to update and improve these offerings. This approach allows researchers to expand the scope of their research, iterate quickly, and avoid lengthy queue delays. This need has become especially relevant as AI projects demand increasingly greater resources.

Two upgrades have recently been made to ARCSIM’s infrastructure that will aid in this effort. The first upgrade has been the installation of 4 AMD EPYC CPUs with 96 cores on an individual chip. This offers higher and more efficient performance than previous on-premise offerings, with two 48 core processors which will continue to operate.

“Researchers iterate a lot and if they have to put something in a queue and the cluster is too busy making them wait that means they are less productive,” explained Chris Dalton, ARCSIM’s cyberinfrastructure engineer. “These are state of the art processing cores. Researchers will get the latest architecture with the fastest results.”

In addition to this upgrade, ARCSIM has installed new storage servers. This brings their raw storage capacity from nearly three petabytes to over seven petabytes. Storage is an important part of ARCSIM’s work as many research projects produce and work with an abundant amount of digital data. While this may be an exorbitant amount of storage now, it will ensure ARCSIM is prepared for the future as there is ever more demand on resources. In the meantime, ARCSIM and the system participate in the Open Storage Networks and Open Science Grid, which allow researchers from across the country to utilize unused resources at other universities and institutes but reserves priority for ARCSIM and the system on their own equipment. 

ARCSIM will continue to make strategic investments in its infrastructure as it works to best serve the system’s research and education community. ARCSIM’s team of specialists encourage individuals to contact them if they are interested in utilizing the equipment or learning more about how they can work with ARCSIM on their projects. 

You can contact ARCSIM at um.arcsim@maine.edu. 

91����’s Advanced Research Computing Security and Information Management unit (ARCSIM) merged with the Advanced Computing Group (ACG) in October 2024. This merger is focused towards creating more efficient and effective services for the entire University of Maine System. With that comes the addition of Forrest Flagg and Chris Dalton to the ARCSIM team. Their engagement ensures the continuation of service for hardware and other systems. 

Flagg, a cloud system administrator, completed his undergraduate and graduate degrees in computer engineering at 91���� and is responsible for building, running and maintaining ARCSIM’s virtual machine and data storage infrastructure. ARCSIM has two virtual machine offerings, one geared towards research and education and another allowing researchers to work with compliant HIPAA data. The CEPH storage cluster is foundational to many of ARCSIM’s services, and the unit is continuing to expand and upgrade the cluster. Currently, Flagg is overseeing an upgrade that expands the storage cluster from nearly three petabytes of raw storage to more than seven petabytes.

Dalton serves as ARCSIM’s cyberinfrastructure engineer maintaining and administering ARCSIM’s on-premise high-performance computing (HPC) compute clusters. ARCSIM operates two HPC clusters currently, Katahdin and Penobscot. The Penobscot cluster, which Dalton implemented in 2024, will eventually replace the Katahdin cluster. In addition to these responsibilities, Dalton serves as a liaison between ARCSIM and peer organizations like the Open Science Grid (OSG). 

Their collective expertise will help extend and expand ARCSIM’s services throughout the University of Maine System. With them comes an immense amount of institutional knowledge and strong relationships across the system and broader research community. Flagg and Dalton will help shape the future of  ARCSIM as the unit works to further streamline processes, improve offerings and services. Collectively, the unit aims to enable the University of Maine System and its research and education mission by offering capable, competitive, and accessible research computing services. 

To learn more about the ARCSIM-ACG merger please visit the ARCSIM website. 

Upgrades to Hardware and Services

Research computing services hosted from the data center in Neville Hall at the 91���� campus have served as a cornerstone for researchers across the University of Maine System (UMS) for many years. A wave of upgrades to hardware and services is in its final stages with interest to better serve the UMS community. Here’s an overview of what’s available.

High-Performance Computing (HPC)

The centerpiece of ARCSIM’s HPC capabilities is the Penobscot cluster, which offers unparalleled computing power through its user-friendly Open OnDemand web interface and SLURM job scheduler. With over 100 compute nodes and more than 4,000 CPU cores, ARCSIM ensures that researchers have the computational muscle they need for their work. The nodes are organized into six primary partitions to optimize performance:

• epyc-genoa: 4 AMD EPYC 4 Genoa systems, each with 96 cores and 384GB of RAM.
• epyc: 14 AMD EPYC 3 Milan systems, each with 96 cores and 512GB of RAM.
• epyc-hm: 4 AMD EPYC 3 Milan systems, each with 32 cores and 1TB of RAM.
• skylake: 8 Intel Skylake systems, each with 36 cores and 256GB of RAM.
• haswell: 88 Intel Haswell and Broadwell systems with 24-28 cores and 64-128GB of RAM.
• gpu: 6 GPU nodes featuring 29 NVIDIA GPUs of various types, including:
  • 14 A100 GPUs (8 with 40GB VRAM, 6 with 80GB VRAM)
  • 3 L40 GPUs with 48GB VRAM
  • 4 A30 GPUs with 24GB VRAM
  • 8 RTX2080 GPUs with 11GB VRAM

The diversity of these resources ensures that researchers can tackle everything from traditional computational tasks to cutting-edge AI and machine learning projects.

Virtual Machines (VMs)

ARCSIM’s local virtual machine services are also available, offering researchers and educators flexible and powerful options for remote workstations, compute servers, and data dissemination. Hosted on the same high-performance infrastructure as the HPC systems, the VM cloud supports up to 1,000 virtual machines with configurations ranging from 1vCPU and 3GB of RAM to 16vCPU and 48GB of RAM.

For developers needing GPU capabilities, ARCSIM provides 12 NVIDIA T4 GPUs (16GB VRAM each), which are ideal for tasks such as GPGPU programming with CUDA and running smaller large language models (LLMs) locally. Specialized VMs are also available for handling HIPAA-compliant data, ensuring secure and compliant workflows.

Advanced Storage Solutions

The backbone of ARCSIM’s infrastructure is its high-performance CEPH storage cluster, which supports HPC and VM services while offering scalable and reliable storage for researchers. The cluster currently boasts 2.9PB of raw capacity, with an expansion planned for early 2025 that will increase capacity to over 7PB. Key features include:

• High throughput and low latency for optimal performance.
• Redundancy and resilience to ensure data availability, even during hardware upgrades or replacements.
• Accessibility across UMS via multiple protocols, including S3 buckets, network shares, and SCP.

Whether researchers need archival storage or high-speed working space, ARCSIM’s storage solutions are designed to meet their needs.

Collaborations and External Resources

In addition to its robust internal resources, ARCSIM partners with several leading organizations to offer researchers access to national computing and storage resources:

• Ohio Supercomputer Center (OSC): OSC supports research in computational science and supercomputing, offering home directory storage (500GB per user), shared project storage in 0.5TB increments, and specialized staff expertise across emerging disciplines. Details on OSC’s storage options and clusters can be found on their documentation page.
  
• Texas Advanced Computing Center (TACC): TACC is a premier center for computational excellence, providing systems such as STAMPEDE3 and FRONTERA, along with a range of storage solutions like Corral for project data storage and Ranch for archival needs.
  
• ACCESS Program (Advanced Cyberinfrastructure Coordination Ecosystem: Services and Support): Funded by the National Science Foundation, ACCESS offers high-performance computing clusters, cloud infrastructure, and storage resources at no cost to researchers and educators. ARCSIM serves as a local ACCESS Campus Champion, facilitating access and helping researchers secure allocations. Visit the ACCESS program page for more details or contact ARCSIM for assistance.

These partnerships extend ARCSIM’s capabilities, ensuring that researchers have access to world-class resources for their projects.

Supporting the Research Community

ARCSIM’s upgraded hardware and services reflect its ongoing commitment to empowering researchers throughout the University of Maine System. With decades of experience among its staff and a robust infrastructure that continues to evolve, ARCSIM provides the tools necessary for groundbreaking research and innovation.

To learn more or to start leveraging these resources for your research, visit ARCSIM’s website or reach out to their team directly.

91����’s Advanced Research Computing, Security, and Information Management (ARCSIM) team provides technological assistance and reporting to 91���� researchers and their collaborators. In 2022, ARCSIM recruited Jeanine McGann as an information systems analyst. While her projects have been an instrumental part of 91����’s transition to web-based platforms, McGann’s academic journey did not begin with computer science.

During her graduate studies at University of New Mexico, McGann worked for the Long Term Ecological Research (LTER) Network, which introduced her to working with data, using web-based systems, and to tools such as Linux, SQL/MySQL, and PHP programming. After McGann finished graduate school, she worked for several universities on National Science Foundation grant-funded projects, developing a close familiarity with academic research environments.

As an information systems analyst, McGann provides technical support and data analysis for research information management and the Office of Research Administration (ORA) at 91����. Alongside Kevin Wentworth, ARCSIM’s assistant director, McGann works on a variety of projects. One of the biggest projects has been bringing a new research management system, Kuali, online. Kuali is a web-based system for proposal submissions and award management. The process of migrating data from the old system to Kuali began when McGann first arrived at 91����, and she has done extensive administrative and technical work to assist in the project, including attending a Kuali Days conference in California last April. While the system has been challenging to implement due to many moving parts, “It’s been a very positive experience,” McGann remarked. “I’ve gotten to work with many different people, hear different perspectives, and learn what people are doing in their work.”

In addition to Kuali, McGann has been collaborating with Wentworth and the University of Southern Maine on creating a new research portal. The new portal allows for monthly financial reviews and cost transfers, with the eventual goal of integrating research reporting as well. McGann is also working on supporting REDCap at 91����, a web-based platform for surveys used in different 91���� labs, especially within the psychology department, for research purposes. 

While her work for ARCSIM is different from the environmental data work McGann did prior to joining 91����, she finds that 91���� is a good fit for her due to the large amount of ecological research going on. “I can still contribute to that as a support service to researchers. It worked out as its own little niche.” McGann hopes to eventually incorporate more of the environmental and ecological data management work she has done in future projects, but, she says, that is down the road. “ARCSIM is involved in a lot of different collaborations around campus. There will be  future opportunities to incorporate that element of my work.”

In recent years, the University of Maine’s Advanced Research Computing, Security, and Information Management (ARCSIM) unit has expanded the services available to 91���� and the University of Maine System. Their most recent expansion introduces new artificial intelligence (AI) and Machine Learning consultation resources. This is possible through the addition of graduate assistant Zafaryab Haider. Haider is pursuing a Ph.D. in Electrical and Computer Engineering with his advisor, Prabuddha Chakraborty, assistant professor of electrical and computer engineering at 91����, and will be working year-round with ARCSIM as a resource for faculty and students interested in using AI and machine learning in their research. For the next two years, Haider will consult with researchers, connecting them to resources and recommending how they can best leverage AI and machine learning for their work. 

Before coming to 91����, Haider was an assistant professor at Aligarh Muslim University (AMU) in Aligarh, India where he taught courses on computer networks, data structures, information security, and coding. After seven years of teaching, Haider decided to pursue a Ph.D. in the United States.

Haider’s experience with AI and information security makes him an ideal fit for his position within ARCSIM. While teaching in India, Haider guided projects on AI related to healthcare. He was contacted by the Malaria Lab in AMU to implement an AI model. While this was a science-based application, Haider believes that AI is applicable to any field, as long as one has good datasets and clear prediction goals. Haider explained that any repetitive job can be performed using AI, whether that is inferring information, making predictions, or giving some amount of insight. “It’s a good assistant,” Haider stated. “It can give you a good direction to think about, analyze, and get some information. But you can’t completely trust it or make decisions based on its outcomes.”

As a consultant, Haider is able to work with researchers to help identify the most suitable algorithms and model sizes that can be applied to researchers’ datasets. This variety is mainly due to the advancements in AI, including Large Language Models (LLMs) like Generative Pre-Trained Transformer (GPT) and other options such as Convolutional Neural Networks (CNNs). With LLMs, rather than needing to teach the AI everything, the user fine-tunes the model to their specific data sets, simplifying the process. Similarly, CNNs are highly effective for tasks such as image recognition and can be tailored to specific needs. The range of model sizes available today varies greatly depending on the project’s requirements. Some open models use over 70 billion parameters, which may exceed the computational resources of many universities for training. Current models run by tech giants like Google and others may use 550 billion parameter models, and that number is only growing. There is a tradeoff between size and accuracy. Larger models often promise greater accuracy, while also increase the potential for errors due to their complexity. “Ultimately, the more computational resources you have, the better,” Haider remarked. “And the University is doing a good job of trying to acquire more for its researchers.”

To learn more about how Haider and ARCSIM can support different research projects, click here. To request service for a research project, click here. You can also reach out to ARCSIM at um.arcsim@maine.edu. 

The research enterprise at the University of Maine has experienced rapid growth in recent years, and with that growth comes accompanying computing, data security, and operational needs. The Advanced Research Computing, Security, and Information Management (ARCSIM), led by Director Shane Moeykens, has been taking steps to meet these needs by further expanding the research computing resources and related services, and making them available to the University of Maine System faculty, staff, and students. As part of 91����’s Coordinated Operating Research Entities (CORE), ARCSIM plays a crucial role in enabling research capacity growth, and its services are available to the entire University of Maine System (UMS).

Across disciplines, demand for high-performance computing (HPC) has significantly increased. To meet this need, ARCSIM has established strategic partnerships with national centers and other organizations over the last five years. For example, partnering with the Ohio Supercomputing Center (OSC) allows Maine researchers to access the massively parallel computing systems often needed by researchers at an R1 institution like 91����. Centers like OSC are not new. Nor are hybrid computing environments, where researchers have a plethora of remote and locally-based hardware solutions available to support their work. This type of access model extends back 25+ years in the private sector, but introducing this type of model in academia, crossing state boundaries, was at minimum very uncommon when first proposed.

Highlighting the innovative aspects of the approach, Laura Jackson, the HPC services leader on the ARCSIM team, became the first non-Ohio-based , complementing her role as an NSF ACCESS Campus Champion. Strategic relationships open up new opportunities for Maine researchers, including access to the scales of hardware that simply do not exist in Maine given the rural nature of our state and the inherent costs for building and maintaining these types of systems. Hybrid computing environments can reduce capital expenditure (CAPEX) and operating expense (OPEX) costs while simultaneously providing greater reliability and  scalable compute access critical to meeting aggressive project deadlines. 

While OSC may be a suitable solution for many, UMS has diverse computing needs. ARCSIM is advancing other computing solutions, like a new GPU cluster housed in Barrows Hall at 91����, and is always pursuing new opportunities to be knowledgeable and proficient with leading computing options, such as Amazon Web Services, Google Cloud Platform, and others. This approach helps ARCSIM to be a one-stop shop for recommendations that best fit the needs of each researcher and project.

The rise in computing activity has increased the need for improved security and awareness to combat the persistent threats to research infrastructure and data. This sentiment is clearly reflected by the presence of heightened security requirements for external research funding. Melissa Kimble, an ARCSIM Senior Research Data Security Analyst, tracks the newest in security regulations and threats, and is an active member of leading cybersecurity groups. Integral to her work is her partnership with the Information Security Office, led by the UMS Chief Information Security Officer, John Forker. This joint effort recognizes that cybersecurity must be approached collectively as a system. A collaborative approach helps our academic community manage a dynamic set of evolving requirements, such as the emerging National Security Presidential Memorandum 33 (NSPM-33) directive, which will impact all US universities who are engaged in at least $50M annual Federal research funding. Based on the draft requirements, universities will have a year from publication of the final requirements to implement and self-certify in order to receive new, or maintain current Federal science and engineering support. 91���� exceeds this threshold and is currently engaged in the preliminary planning for this upcoming directive. For institutions operating below this threshold, there may still be implications, considering a single research grant may span multiple campuses within UMS, even when only one is above the $50M threshold.

ARCSIM is changing how research happens through more than one approach. It recently expanded access to REDCap, a secure survey and database system, which gives researchers new tools to conduct online surveys. Providing the community with the tools it needs is central to ARCSIM’s mission. This can be as simple as making quality of life improvements. For instance, ARCSIM and UMS:IT have worked together to streamline how non-standard research computing devices are purchased at 91����, ensuring that faculty and students have access to the technology they need to innovate.

ARCSIM’s focus is not restricted to the researchers themselves. A similarly important charge for ARCSIM is improving the productivity of other support units, a strategy which indirectly benefits the research community. For example, ARCSIM launched Kuali with 91����’s Office of Research Administration, which will help UMS more efficiently process the record number of awards and research dollars coming in. It is also helping UMS better quantify itself. ARCSIM advances projects to produce and track research analytics, which play an important role in decision making, reporting, and positioning for future research success. 

Research computing, security, and information management will continue to change and transform over the years. ARCSIM is dedicated to making those changes happen smoothly, while providing each researcher with the resources and support needed to best meet their individual project requirements.

In 2023, the Advanced Research Computing, Security, and Information Management (ARCSIM) group partnered with Computer Science and Electrical & Computer Engineering faculty at 91���� to source a new GPU cluster from Cambridge Computer Services in Boston. Expanding GPU resources was given high priority to provide relief to faculty who are engaged with Artificial Intelligence (AI) and Machine Learning (ML) research, both of which greatly benefit from GPU-based hardware, which in recent years has been a critically scarce resource nationally. 

To bolster the startup of the new cluster, ARCSIM brought on board an undergraduate intern, Nathan Price, in late 2023. Originally from Delaware, Price is studying computer engineering at 91����, and brings to his position deep levels of experience and interest. As a hobby, Price maintains a Linux cluster at home, gaining skills and knowledge that directly translate to his internship.

Working closely with ARCSIM staff, Price has assisted with the physical buildout of the cluster. Price describes it as a puzzle. Much of his time is spent making sure all of the different components are communicating with each other, and this is not always easy. Configuration issues can take time to resolve, as he engages with vendors and seeks solutions. He is also working with ARCSIM staff to understand and define a suite of target user experiences, which is being leveraged to optimize the setup of the cluster.

Price takes pride in this work because of the importance of the research activities that the new cluster aims to support, and he sees his internship as a real growth opportunity. “This type of work is not something anyone gets to do as an undergraduate student,” remarked Price. “I am building a system that faculty will be using as an integral part of their research.” While there is some pressure in that, Price finds it exciting that he gets to use his knowledge to take on this challenge and grow through it.  

The internship is also helping Price consider his future. Price, a US ARMY veteran, explained, “I am not a traditional student, and this project has opened a lot of doors for me. I get to meet people whose full time job is working in high-performance computing at national centers like the Ohio Supercomputer Center. I am developing first hand experience in my chosen field by supporting this project.” This internship has also helped Price better understand what he likes about the HPC field and what steps he will need to take to reach his long term career goals. 

Once up and running in Spring 2024, the GPU cluster will be supported by Price and ARCSIM staff. This new computing platform will enable the work of AI/ML researchers, and provide the community with a co-located, accessible resource at 91����.

The Advanced Research Computing, Security, and Information Management (ARCSIM) group has recently expanded to reflect the enhanced compliance requirements of research work being conducted with the Department of Defense (DoD) Controlled Unclassified Information (CUI). In Fall 2023, Sammy Murphy, an IT Vulnerability Specialist, joined ARCSIM to focus on critical vulnerability management tasks in support of the University of Maine’s Advanced Structures and Composites Center (ASCC), one of the largest research centers within the University of Maine System.

With an increasing number of large, defense related grants being awarded to ASCC, managing security requirements and expectations is becoming a focal point of ARCSIM’s operations. Murphy graduated from 91���� with an interdisciplinary undergraduate degree focused on computer science and communication, and worked at ASCC as a student and then again after graduating. Murphy brings a familiarity and knowledge of ASCC to the ARCSIM team and has recently begun studying to complete a Systems Security Certified Practitioner (SSCP) certification as well.

A significant amount of federal funding awarded to ASCC is contingent on specific cybersecurity requirements. Working closely with Melissa Kimble, Senior Research Data Security Analyst, Murphy supports the IT Infrastructure required for these funding sources by monitoring device logs, threats, and security developments. Murphy explained, “Vulnerabilities can arise in many forms, including within software applications. If it is found that malicious actors are exploiting a certain vulnerability in an application, the application vendor will likely release an emergency security patch. We need to monitor logs, catch that, and patch it right away.” This effort ensures that ASCC meets cybersecurity requirements and that sensitive research data is safeguarded.

Beyond vulnerability management, Murphy’s familiarity and knowledge of ASCC has been instrumental in evaluating existing policies and procedures that affect the center’s cybersecurity posture. This work has resulted in input and oversight of over 35 policies, a multi-stakeholder effort that has been expedited through Murphy’s expertise. These policies and procedures have been adapted to reflect current and pending cybersecurity requirements for the center.   

For Murphy, the best part is collaborating with colleagues on collectively understanding what threats are out there and how those threats can be best addressed and communicated. “Part of what I do is make this information digestible,” remarked Murphy. “It is important that people understand the threat, why we are concerned about it, and how we are addressing it.”

Shane Moeykens, ARCSIM Director, states, “Roles like Murphy’s will only become more important as research across the University of Maine System continues to grow. This growth is contingent on maintaining secure computing environments for research activities and data, and thereby preserving external funding and executing nationally important research activities.” 

by Stefania Irene Marthakis

Salimeh Yasaei Sekeh, Assistant Professor of Computing and Information Science at the University of Maine (91����), works in the field of Artificial Intelligence (AI) on projects ranging from robotics to biomedical engineering. Sekeh also serves on the Advanced Research Computing, Security and Information Management (ARCSIM) Advisory Board as a faculty member, where she provides guidance on AI-related computing resources such as High Productivity Computing Systems (HPCS).

The Sekeh Lab focuses on two areas of research: (1) Addressing the foundation of AI models by studying the obstacles within the current models and working to improve them (e.g., efficiency, reliability, performance precision, robustness). “How can we advance this AI model foundationally, so they can be reliable to address real world problems?” And (2) The application of AI, how AI can be applied to real world problems from fields such as forestry, medical science, agriculture, and marine science by using existing AI models as well as advancing the AI models from practical perspectives.

To create something that is automated and intelligent, you need to use a set of tools or systematic algorithms, which is Machine Learning (ML). Sekeh explained, “Machine Learning uses knowledge from different sciences such as computer sciences, mathematics, and statistics as well as optimization, computing, and analyses. You put these all together to build up the set of tools. AI models then try to make a decision intelligently using those tools. Machine Learning is an assistant to AI; AI cannot function without Machine Learning.”

The field of AI is expanding rapidly and the application of AI is found within a diverse set of disciplines within college departments. Currently at 91����, biomedical engineering, agriculture, marine science, and forestry projects are investigating and exploring opportunities in AI that can help them achieve their project’s vision. For example, INSPIRES (NSF EPSCoR RII Track-2 project) applies AI and ML techniques to hyperspectral forestry data to predict and label specific forestry regions of New England.

The biggest AI challenges universities and institutions (that are not tied to large companies), such as 91����, face is computing resources. “HPCS is a big challenge,” Sekeh stated. “You need a lot of computing resources, especially from an efficiency perspective, because you need to train your AI model on a tremendous amount of data.”

Beyond that there are other major challenges with AI models such as reasoning and trustworthiness, especially when it comes to critical sciences, for example, medical surgeries. There are also challenges in terms of social media and advertisement, and the effects on the behavior and education of younger generations. “The AI field is moving forward very rapidly,” Sekeh said, “and we are trying to catch up with these obstacles.”

Currently, the Sekeh Lab has a PC with one Graphics Processing Unit (GPU) for each graduate student, and the lab recently purchased one tower with three GPUs that the whole lab can use. Sometimes, the Sekeh Lab uses other available resources on and off campus.

“The major need for students in my lab is computer resources because it is tied to time. Time these days is the most precious thing we have,” Sekeh stated. “There is a huge difference when a student runs a code and it takes one week or it takes one day. This task is followed by evaluation and modification on the model, study the results and outcome, improve the model, and make a decision on the next steps based on the steps before. Just imagine, this sequence of actions on a project is getting delay after delay. When we have the right resources, we can act quickly and accomplish each step of the project efficiently.”

The other challenging aspect of computer resources and time is because the field of AI is growing so fast. If researchers are waiting for months for the results on a specific topic, there are a lot of papers out in scientific journals on that specific topic already. “You are basically behind on the advancement of certain topics within the AI community, which is a major concern, especially for Ph.D. students and PIs when they are actively doing research,” Sekeh explained.

Currently, Barrows Hall at 91���� is setting up a GPU Cluster (multiple computers or nodes connected with a high-speed network) with the opportunity for faculty to use in fall 2023. “The moment we get the chance to use those machines, we are on it,” Sekeh stated. “I think this is a great idea, and I strongly support this. We not only need one GPU Cluster, but I believe we need more computing resources like this to stay competitive.”