Supercomputing Availability Boost in America: Insights on Federal Government Measures

The Center for Data Innovation recently hosted a panel discussion focusing on increasing access to high-performance computing (HPC) resources for AI researchers in the U.S. The discussion, led by Hodan Omaar, highlighted the report titled "How the United States Can Increase Access to Supercomputing."

One of the key issues addressed was the current funding situation for HPC. With the investment made by the NSF and DOE only able to support a third of the researchers who need access, a lack of federal funding is preventing these organisations from building an adequate supply of HPC resources. Panelists agreed that Congress should significantly increase funding for HPC to both NSF and DOE.

The report suggests tripling federal funding for HPC to $10 billion over the next 5 years, but Nvidia's Cheryl Martin points out that this figure will need to grow over time. Andrew Jones from Microsoft emphasised that funding must be matched with strategic planning and operational processes for HPC and AI capabilities.

Another issue discussed was the gender and diversity imbalance in the HPC community. This imbalance is causing a gap in the number of qualified candidates from underrepresented groups entering the HPC workforce. Long-term initiatives are needed to address the leaky pipeline hindering qualified candidates from underrepresented groups with computer science backgrounds.

The report also identifies three problems limiting AI researchers from accessing HPC resources. Firstly, access to HPC is concentrated in states with leading academic institutions. Secondly, cloud-based computing architectures are not well-suited to all applications. Lastly, without a clear strategy for acquiring state-of-the-art computing infrastructure, software, and experts, disparate initiatives may impede researchers from being more productive and innovating at higher rates.

To address these issues, the report suggests exploring cloud computing options to diversify HPC resources for AI researchers. Providing access to cloud services for AI researchers across the country can provide more researchers with the tools they need. Additionally, HPC and AI workforce development programs should be established at a broader scale to include K-12 and minority-serving institutions.

A promising example of collaboration is Nvidia's partnership with the University of Florida to launch an AI supercomputer. This partnership serves as a model for universities, industry, and government collaboration in building and providing HPC resources.

The current U.S. initiatives to reduce geographic inequality in providing HPC resources for AI researchers include the America’s AI Action Plan announced in July 2025, focusing on innovation, infrastructure, and international diplomacy to maintain AI leadership and promote broader access. Additionally, there is ongoing congressional debate on AI regulations and proposals such as establishing a Public AI Wealth Fund to ensure public benefits from AI advancements and promote equitable access to AI technology infrastructure across regions.

However, it's important to note that AI researchers in states with fewer leading universities and less computer science funding, such as Alabama, Indiana, or Utah, are less able to pursue their research goals. Without proper support and resources, these researchers may face significant challenges in advancing AI research and innovation.

In conclusion, increasing access to high-performance computing resources for AI researchers in the United States requires significant investment, strategic planning, and collaboration between academia, industry, and government. By addressing the issues of funding, diversity, and geographic inequality, the U.S. can ensure a more equitable and innovative future in AI research.

Supercomputing Availability Boost in America: Insights on Federal Government Measures