Argonne National Laboratory

Science Highlights

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The importance of being flexible

A team of researchers from Argonne National Laboratory, Arizona State University, and the University of Chicago developed a two-stage framework to evaluate the benefits of battery storage in power systems with renewable resources.

December 5, 2016
MG-RAST version 4.0 released

The new version of the metagenomics analysis server MG-RAST was released November 15, 2016. metagenomics analysis server MG-RAST was released November 15, 2016. The release followed an open beta testing period and feedback from numerous users.

MG-RAST is an open-source automated system for processing metagenome sequence data, which then can be used for analyses ranging from phylogenetic profiling and comparisons to functional annotations and metabolic reconstructions. To date, MG-RAST has processed more than 265,000 data sets for more than 20,000 users.

Indeed, many of the new features of MG-RAST 4.0 are designed specifically to make life easier for the users. For example, instead of having to wait for the results of each parameter change, the user can now download the complete abundance profiles of selected datasets, where the data can be filtered quickly. The new myData page is equally helpful. With it, the user can view running jobs, completed studies, and news; link to a more detailed view; and quickly search for a particular dataset. And the new version of metaZen will give the user direct feedback and input help when creating metadata spreadsheets.

“We’re especially proud of the redesigned metagenome analysis page,” said Folker Meyer, a senior computational scientist in the Mathematics and Computer Science (MCS) Division at Argonne National Laboratory and founder of the MG-RAST project. He noted that all the user’s data now has provenance information, as well as multiple download options including the images and the data used to produce them. Moreover, all the technical details of the data progression through the MG-RAST pipeline are provided on the processing receipt page.

“This version of MG-RAST is built around a RESTful API and is deployed as a set of interacting containers” said Andreas Wilke, a fellow researcher in the MCS Division at Argonne. He pointed out the use of containers in the workflow component of MG-RAST that allows hitherto unknown performance and flexibility. “It is this newfound flexibility that enables a series of additional workflows that will add additional capabilities,” he said.

The new server was announced on the web at is available at

December 5, 2016
MCS Division researchers awarded INCITE supercomputing time

Two researchers in the Mathematics and Computer Science Division at Argonne National Laboratory will participate in computational research projects involving advanced simulation and analysis on the U.S. Department of Energy leadership-class computers.

November 29, 2016
Cappello named a fellow of the IEEE

Franck Cappello, a senior computer scientist in the Mathematics and Computer Science Division at Argonne National Laboratory, has been named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE).

November 23, 2016
Argonne/University of Chicago team wins workshop best paper at SC2016

A team of researchers from Argonne National Laboratory and the University of Chicago has received a best paper award at Supercomputing 2016 in Salt Lake City, Utah. SC is the premier international conference on high-performance computing, networking, storage, and analysis.

November 23, 2016
Argonne’s Ian Foster to lead new exascale co-design center

The Co-Design Center for Online Data Analysis and Reduction at the Exascale was named today as one of four co-design centers to be funded by the U.S. Department of Energy’s Exascale Computing Project.

November 16, 2016
It takes increasingly powerful computing resources to perform more and more complex simulations of nuclear reactor fuel assemblies. This image shows the coolant-flow pressure distribution in a 217-pin wire-wrapped subassembly. (Image by Paul Fischer)
Exascale Computing Project announces $48 million to establish four exascale co-design centers

DOE’s Exascale Computing Project is announcing it has selected four co-design centers as part of a 4-year $48 million funding award, including one to be led by Argonne.

November 11, 2016
NekCEM/Nek5000 wins 2016 R&D 100 Award

The project NekCEM/Nek5000: Scalable High-Order Simulation Codes has received a 2016 R&D 100 Award.The project NekCEM/Nek5000: Scalable High-Order Simulation Codes has received a 2016 R&D 100 Award, given by R&D Magazine to 100 top new technologies for the year.
Nek5000/NekCEM is a joint effort of Misun Min and her team in Argonne’s Mathematics and Computer Science Division in partnership with Paul Fischer (now at the University of Illinois at Urbana-Champaign).
The NekCEM/Nek5000 high-performance software package allows accurate and efficient simulation of electromagnetics, fluid flow, thermal convection, combustion, and magnetohydrodynamics. A key feature of the package is its ability to run on platforms ranging from PCs to the world's largest parallel computers. NekCEM is used for simulating electromagnetic devices such as solar panels and nanoparticle systems. Nek5000 is designed to simulate fluid flows in applications including nuclear thermal hydraulics in reactor cores, combustion, and ocean currents.
The award was announced at the R&D 100 Awards and Technology Conference in Oxon Hill, Maryland, on November 3.
Argonne received two other 2016 R&D 100 awards. For the full description, see the website

November 10, 2016
Why negative results matter

In a report of the ERROR2015 workshop, which appeared in a special issue of Concurrency and Computing; Practice and Experiences, the authors argued that the failure to report negative results is in itself a failure.

November 9, 2016
MCS researchers play major role at SC16

The Mathematics and Computer Science Division at Argonne National Laboratory are well represented at SC16, the premier annual conference in high-performance computing, networking, storage and analysis.

November 2, 2016