Powering Scientific Discovery: How Data Infrastructure is Accelerating Breakthrough Research

Behind every major scientific breakthrough today, whether it’s advancing human health, understanding the environment, or decoding the secrets of life itself, there’s an invisible but critical foundation: computational infrastructure.

In a recent webinar I had the opportunity to speak with leaders from three of the world’s most innovative research institutions: the Innovative Genomics Institute at UC Berkeley; Lawrence Berkeley National Laboratory; and the Joint Genome Institute. Together, these organizations are pushing the boundaries of genomics, climate research, and computational science. And one thing quickly became clear in our discussion: the success of their work depends not only on world-class scientists, but on the ability to manage and scale massive amounts of data effortlessly.

These aren’t ordinary IT challenges. Whether it’s processing terabytes of genomic sequences or supporting complex, multi-user HPC environments, the reality is the same: researchers can’t afford to wait on infrastructure. As Georg Rath from JGI shared, jobs that used to take over 24 hours to run on their legacy systems were reduced to just 30 minutes, an order-of-magnitude improvement that translates directly to faster research and happier scientists.

For Rohan Sachdeva at IGI, it wasn’t just about speed, but about giving researchers visibility and control over their data without the overhead of complex systems. He spoke about the burden his team faced trying to wrangle billions of files, often relying on homegrown scripts just to answer simple questions about storage usage. Shifting to a modern data platform meant his team could focus less on managing infrastructure—and more on supporting breakthrough genomic research.

What stood out in our conversation wasn’t just the technology, but the operational shift. These organizations aren’t just consuming data; they are data-driven. They rely on modern data platforms that eliminate complexity, enable seamless collaboration, and provide real-time insight into how resources are being used. For them, scalable, flash-first architectures like VAST’s aren’t about storage—they’re about enabling science at speed and scale.

If you’re part of the HPC or research community and want to hear how leading institutions are building the next generation of data-driven science, I invite you to watch the full webinar.