Higher education institutions face unparalleled challenges. The shift to the digital campus, well underway prior to the onset of COVID-19, accelerated during the pandemic. With the transition come increased costs and more intense competition to attract and retain students. At the same time, the battle for grants and other sources of funding for research remains fierce.

Collectively, these circumstances place tremendous financial and resource pressures on many higher education institutions, which can affect research headcounts and IT budgets. But research continues to be the lifeblood of many institutions. As HPE's Vice President and General Manager Americas High Performance Compute and AI, Steve Hershkowitz, says, "The complexity and groundbreaking nature of research requires a high-performance computing infrastructure of hardware and software. One with the flexibility, scalability, graphical processing power, and architecture to seamlessly incorporate artificial intelligence (AI) and other advanced technologies from the on-premises labs to data centers, colocation facilities, the edge, and on to the cloud – and back again."

Therein lies the conundrum. To win the day, higher education institutions need more, but may well have to make do with less. How can they navigate this contradictory environment?

Success depends on changing the research business model. Too often, the IT infrastructure supporting research becomes siloed. Assets procured with funds from a grant become dedicated to the associated research endeavor. As a result, asset availability rises, but utilization sinks. Capacity sits idle, wasting a valuable resource.

In addition, the siloed procurement approach creates islands of infrastructure, each likely unique in composition. These infrastructure islands inhibit collaboration amongst research teams, add to IT's management and maintenance burden, and limit the opportunities to benefit from economies of scale – all of which actually may place a drag on research, rather than give it the speed it deserves.

Higher education institutions must consider moving away from siloes and towards the adoption of a "better together" research business model that helps bridge the gaps between islands. The better together model relies on a shared-use platform accessible across research departments. Instead of acquiring stand-alone assets with grants and other sources of funding, departments funnel those dollars into an equivalent expansion of the platform. They can do so directly, by allocating funds to a central purchasing group. Or, they can do so indirectly through buy-in programs, by following the specifications generated by a centralized research organization and executing purchases accordingly. In this scenario, assets still can be tracked to grants, yet incorporated seamlessly into the growing shared infrastructure to avoid creating islands.

By pooling assets into the shared use platform, higher education institutions can achieve higher resource utilization across the board, without sacrificing resource availability for any individual research endeavor. At the same time, they may be able to cut acquisition and maintenance costs by building a more tightly integrated infrastructure, better leveraging compute and network assets, and starting to rationalize their vendor portfolios.

The better together model works best with the right platform as its foundation to meet the varied requirements spanning all research departments and initiatives. The platform demands servers, like those from HPE, that offer a unified architecture to turbocharge traditional and modern workloads, from data center to edge. One that delivers a high-performance, cost-effective, and scalable infrastructure that fuses compute and graphics acceleration – like NVIDIA's AI and accelerated computing solutions for enterprise IT – along with high-speed, secure networking. One that is fully-integrated with industry-leading IT and DevOps frameworks. One that incorporates best-in-class AI compute hardware and software with full-stack innovation. One with a proven track record of exascale-level deployments that meet the increasingly stringent security, compliance, and reliability imperatives similar to those needed by higher education institutions ready to adopt a shared use platform.

"AI technology is reshaping nearly every industry, having become an important part of higher education, enabling groundbreaking research that will help solve the most complex and important social and societal challenges, and developing the AI-enabled workforce," said Cheryl Martin, Global Director, Business Development Higher Education and Research at NVIDIA. "Forward-looking institutions must invest in shared use platforms that provide all AI has to offer, or else risk being left behind."

To compete in the rapidly-changing world of higher education research, institutions must seek every possible advantage. The better together model empowers researchers, teams, and departments to innovate, collaborate, and accelerate – raising the institution's profile, helping drive talent and revenue to the institution, addressing the budgetary realities the institution faces, and positioning the institution for ongoing success.