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Awards and Recognition | Mathematics and Computer Science Division

Two MCS technologies win R&D 100 awards for 2021

Two research teams from the Mathematics and Computer Science Division at Argonne National Laboratory have received 2021 R&D 100 Awards.

The R&D 100 Awards have served as the most prestigious innovation awards program for the past 58 years; their mission is to identify and honor the top 100 new technologies of the year.

The two MCS Division award-winning technologies – Mochi and SZ –  were selected under the Software/Service category .

Mochi, a Customizable Data Navigation Tool

Robert Ross, Philip Carns, Shane Snyder, Rob Latham, Matthieu Dorier

The Mochi project (https://​www​.mcs​.anl​.gov/​r​e​s​e​a​r​c​h​/​p​r​o​j​e​c​t​s​/​m​ochi/) provides a collection of specialized data services that scientists can select from and compose to suit their particular application requirements.  With Mochi, rather than  having to create a specific service  from scratch, researchers can process their data more rapidly, potentially decreasing the time to new scientific discovery. Mochi staff currently are exploring machine learning and artificial intelligence to improve the adaptability of Mochi’s data services on heterogeneous computer platforms.

The Mochi team includes researchers  at Argonne, Los Alamos National Laboratory, Carnegie Mellon University, and the HDF Group.

SZ: A Lossy Compression Framework for Scientific Data

Franck Cappello, Sheng Di

With increasing scales of scientific simulations and updates of instrument facilities, scientific applications and experiments are producing extremely large amounts of data, , at high velocity, that is difficult to store, transfer and analyze. The solution is data reduction, but simply dropping data can drastically alter scientific analysis. The challenge here is how to significantly reduce the scientific data size while keeping the information important to the users. The SZ lossy compression framework (https://​szcom​pres​sor​.org) provides an innovative solution to this problem. SZ is the first highly customizable and parametrizable lossy compression framework for scientific data (floating-point and integers). Through a series of specializations and optimizations, SZ significantly reduces the data size for many different use-cases, while still keeping the data valid for competition and scientific analysis. SZ has applications in simulations, artificial intelligence and instruments. The software has been widely adopted not only in the United States (including several national laboratories and research institutions) but also in other countries (including supercomputing centers in Germany, Spain and France) and by industry. Because of its flexible nature, SZ is also used as a research vehicle for developers of lossy compression algorithms. SZ development is mainly supported by the DOE/NNSA Exascale Computing Project.

For further information about Argonne’s R&D100 Award winners for 2021, see the Argonne website https://​www​.anl​.gov/​a​r​t​i​c​l​e​/​a​r​g​o​n​n​e​-​c​a​p​t​u​r​e​s​-​3​-​r​d​-​1​0​0​-​a​w​a​r​d​s​-​f​o​r​-​i​n​n​o​v​a​t​i​v​e​-​t​e​c​h​n​ology.

For a list of R&D 100 Award winners, see the pagehttps://​www​.rdworl​don​line​.com/​2​0​2​1​-​r​d​-​1​0​0​-​a​w​a​r​d​-​w​i​n​n​e​r​s​-​a​n​n​o​u​n​c​e​d​-​i​n​-​p​r​o​c​e​s​s​-​p​r​o​t​o​t​y​p​i​n​g​-​a​n​d​-​s​o​f​t​w​a​r​e​-​s​e​r​v​i​c​e​s​-​c​a​t​e​g​o​ries/.