Hewlett Packard Enterprise Advances the Global Food System Through Memory-Driven Computing With CGIAR

Nachrichtenquelle: Business Wire (engl.)
24.09.2020, 15:25  |  113   |   |   

Hewlett Packard Enterprise (NYSE: HPE) today announced a collaboration with global research partnership the CGIAR System Organization (CGIAR) to uncover insights about food security challenges, now intensified due to COVID-19. By applying HPE's Memory-Driven Computing Sandbox to CGIAR's data sets, HPE will help CGIAR accelerate solutions to these global challenges by enabling modeling of food systems.

One of the most pressing challenges facing the world today is ensuring a sustainable global food supply. Nearly 800 million people are chronically undernourished and 2 billion are micronutrient deficient, while the number of smaller farms, globally, is on the decline because profitability is so difficult. In short order, these problems will significantly worsen as the United Nations (UN) forecasts the world’s population will grow to 8.5 billion by 2030, and the World Economic Forum predicts a population of 9.8 billion by 2050, requiring 70 percent more food than is consumed today.

The problem has only worsened in light of the global COVID-19 pandemic. The crisis is affecting food systems and supply chains worldwide, but it is unfolding differently around the world, which means the problems cannot be solved with one universal solution.

CGIAR is a global research partnership of 14 non-profit agricultural research institutes working in over 100 countries on research into virtually every aspect of food security. In its 11 genebanks around the world, CGIAR preserves and regenerates 760,000 varieties of food crops that represent important genetic diversity available for building resilience in the global food supply.

To fully understand the situation today, CGIAR needs to generate a timely, high-frequency picture of what is happening in “food basket” locations – or areas of significant food production – around the world. A complete picture often requires data from multiple sources including crop performance, weather records, economic activity, and surveys.

Insights from this data help researchers answer questions like:

  • How is economic activity and food movement happening in food baskets on a weekly basis?
  • How can these analytics guide the agriculture sector and its most vulnerable participants in a period of increasing climate variability and extreme weather events?
  • How can public, private, and non-profit actors meaningfully share all of this data to enable better outcomes for all?
  • How can stakeholders track and measure progress toward the UN’s Sustainable Development Goals for zero hunger by 2030?

Answers to questions like these help CGIAR detect and predict food security challenges and guide collective action to solve them.

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