News

28
Jul
2015

The full potential of cloud computing to directly impact science, medicine, transportation, and other industries has yet to be realized. To help investigate and develop this promising cloud computing future, the Computation Institute (CI) at the University of Chicago and Argonne National Laboratory and the Texas Advanced Computing Center (TACC) at The University of Texas at Austin today announced that the new experimental testbed, called Chameleon, is in full production for researchers across the country.

10
Jul
2015

Distinguished Fellow is the highest rank achievable by an Argonne researcher, a rare honor that acknowledges influential discoveries and technical leadership. Once a year, the national laboratory names a maximum of four staff members to this highly select company, placing them among Nobelists, R&D 100 winners, and holders of more than 800 patents.

24
Jun
2015

The CI’s 2014-15 Inside the Discovery Cloud speaker series focused on collaboration, presenting pairs of speakers who are working together to unlock new knowledge through computation. Attendees heard about how new computational approaches are changing medicine, biology, social science, public policy, and more, and discover opportunities for new collaborations and student research projects. View the videos of these stimulating talks.

Research

Globus logo

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.

XSEDE logo

The Extreme Science and Engineering Discovery Environment (XSEDE) is the most advanced, powerful, and robust collection of integrated advanced digital resources and services in the world. It is a single virtual system that scientists can use to interactively share computing resources, data, and expertise.

The OpenAD/F project seeks to develop a modular, open-source tool for the automatic generation of adjoint code from Fortran 95 source code. Discrete adjoint computations are used for sensitivity analysis and to provide the gradients used in geophysical state estimation. Because derivatives are needed with respect to millions or billions of independent variables, finite different approximations are impractical: a gradient computation that would take minutes or hours using an adjoint computation would take months or years using finite differences.

Researcher Spotlight