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.
“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.
Insights from this data will enable CGIAR to see and
increasingly predict how food security challenges are unfolding
from the COVID-19 crisis to inform policy makers, food relief
actors, and other stakeholders. Using CGIAR’s existing technology,
emissions analysis on one point on the Earth could take four to
five hours to run. Today, CGIAR can run multiple analyses over
multiple points with sufficient frequency to inform timely action
on food security.
“At HPE, our purpose is to advance the way people live and work,
and we are committed to applying technology to help address some of
society’s toughest challenges,” said Janice Zdankus, VP, Innovation
for Social Impact, HPE. “One of our focus areas is world hunger,
inspired by results from Purdue University's 1,400-acre research
farm and its application of precision agriculture to increase crop
yields while drastically conserving resources. With CGIAR, we saw
the opportunity to apply innovative technologies, like HPE’s
Memory-Driven Computing Sandbox to drive faster insights and help
address this incredibly complex challenge.”
While the pandemic has caused immediate and near-term issues
that must be addressed, the future of food security must be
evaluated on a longer horizon as well. Mapping and predicting
climate risk, vulnerability, and adaptation options are top
priorities for CGIAR.
“Building monitoring and modeling capabilities is critical,”
said King. “The whole world was caught flat footed during the
pandemic because we found that there were huge gaps in timely, good
quality data to monitor and respond quickly to the myriad – and
very different – food system disruptions unfolding as a result of
the COVID crisis. The global community of food security actors has
begun to build up capabilities for more timely, localized diagnosis
and response to food security challenges, and complement these with
mapping and predicting risks and vulnerabilities of potential
climate shocks to food security on a longer time horizon. We will
be able to highlight the best options for vulnerable farmers in
those areas to adapt to changing conditions and help equip them for
that before the next crisis arises.”
For instance, CGIAR leverages models to predict the kinds of
climate hazards (disaster events like cyclones, floods, and
droughts) that will likely threaten small-holder farmers in
developing economies. CGIAR then helps policy makers and the
at-risk farmers themselves prepare for these types of climatic
shocks so that the impact to the food system is minimized.
As the year 2030 approaches, global efforts to achieve the
Sustainable Development Goal zero hunger must be digitally
powered.
“The global community is finding we need to look at these data
types together and with greater frequency to inform targeted
investments that build resilience for small-holder farmers,” said
King. “There’s a lot of work to be done in creating the analytic
underpinnings to enable zero hunger.”
About Hewlett Packard Enterprise
Hewlett Packard Enterprise is the global edge-to-cloud
platform-as-a-service company that helps organizations accelerate
outcomes by unlocking value from all of their data, everywhere.
Built on decades of reimagining the future and innovating to
advance the way we live and work, HPE delivers unique, open and
intelligent technology solutions, with a consistent experience
across all clouds and edges, to help customers develop new business
models, engage in new ways, and increase operational performance.
For more information, visit: www.hpe.com.
About the CGIAR Platform for Big Data in Agriculture
The CGIAR Platform for Big Data in Agriculture embraces the
power of big data analytics, supporting CGIAR as it becomes a
leader in generating actionable data-driven insights. It builds
capacity throughout CGIAR to generate and manage big data,
assisting CGIAR and its partners’ efforts to comply with open
access/open data principles to unlock important research and
datasets. It also empowers researchers to strengthen data
analytical capacity, developing practical big data tools and
services in a coordinated way, and it addresses critical gaps, both
organizational and technical, expanding the horizon of CGIAR
research. The Platform is co-led by the Alliance of Bioversity
International and the International Center for Tropical Agriculture
(CIAT) and the International Food Policy Research Institute
(IFPRI). CGIAR is a global research partnership for a food-secure
future dedicated to reducing poverty, enhancing food and nutrition
security and improving natural resources. The Alliance of
Bioversity International and CIAT and IFPRI are CGIAR Research
Centers.
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version on businesswire.com: https://www.businesswire.com/news/home/20200924005280/en/
Lindsey Berryhill Lindsey.Berryhill@hpe.com 706.773.3601
Hewlett Packard Enterprise (NYSE:HPE)
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