Hewlett Packard Enterprise Advances the Global Food System Through Memory-Driven Computing With CGIAR - Seite 2
“Being able to create a picture in 200 cities or settlements in a short amount of time is dramatically different from what we can do with our existing compute resources,” said Brian King, coordinator of CGIAR’s Platform for Big Data in Agriculture. “Since the impacts of COVID-19 are unfolding differently by country, our ability to look at the situation both at the aggregate level and from an on-the-ground, local view is incredibly valuable. That capability enables a different way for us to operate as a research organization. But generating high-frequency insights across multiple distinct contexts at once demands compute power to support it and more compute capacity than we had. The Memory-Driven Computing Sandbox appeared at just the right time.”
While CGIAR has high-performance computing clusters at several of its Centers, it is seeing increased need to develop timely, localized information and analysis across an array of food security contexts in light of the pandemic, and this is beyond its existing compute resources. The Memory-Driven Computing Sandbox sets itself apart by giving every processor (up to 64 sockets) in the system access to a giant shared pool of memory – up to 48 terabytes – which is a sharp departure from today's systems. Typically, relatively small amounts of memory – just a few terabytes – are tethered to each processor; the resulting inefficiencies limit performance. By having all of the massive, diverse data sets available at one time in memory, users can clear computational bottlenecks that hinder research and discovery.
With access to the Sandbox – so named for the controlled environment it offers customers to experiment with advanced compute resources – CGIAR is building cross-cutting, high-frequency views of food systems linking crop modeling – including weather records and how crops performed and what the yield was, by year and location – survey data, and overall economic activity (e.g. movement of goods and people). CGIAR is monitoring emissions from up to 1,000 points across India and East Africa using public satellite data from space agencies. Changes in emissions indicate changes in economic activity that give researchers important context for understanding how food security challenges are unfolding by location. Equipped with this dynamic, unfolding picture, CGIAR is able to compare with crop and survey data to monitor how that individual crop will impact the broader food supply.
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