​Services Layer At The Edge (SLATE), a new $4 million project funded by the National Science Foundation and led by a team from the Enrico Fermi and Computation Institutes at University of Chicago, will provide technology that simplifies connecting university and laboratory data center capabilities to the national cyberinfrastructure ecosystem, enabling global research collaboration.


For decades, fierce debates have raged over the benefits of different programming languages over others: Java vs. C++; Python vs. Ruby; Flask vs. Django. While often waged with religious fervor by computer scientists and programmers, these debates tend to rely on anecdotal evidence, with very little rigorous comparison of programming approaches or the larger question of how software may augment human thinking.


A new grant from the National Science Foundation extends the Chameleon cloud computing testbed for another three years, allowing the project led by University of Chicago and Computation Institute scientists to enter its next phase of computer science innovation. Upgrades to hardware and services as well as new features will help scientists rigorously test new cloud computing platforms and networking protocols.


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The Discovery Cloud is CI Director Ian Foster's vision to deliver powerful computational tools and methods to every professional and amateur scientist around the world, fundamentally transforming the ecosystem of science. Globus is the first step towards realizing this vision.

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UC3 is an open computing framework for connecting users to shared Distributed High-Throughput Computing (DHTC) resources, both on- and off-campus.

Researchers frequently rely on large-scale and domain-specific workflows to conduct their science. These workflows may integrate a variety of independent software functions and external applications. However, developing and executing such workflows can be difficult, requiring complex orchestration and management of applications and data as well as customization for specific execution environments. Parsl (Parallel Scripting Library), a Python library for programming and executing data-oriented workflows in parallel, addresses these problems.

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