See http://arc-ts.umich.edu/summer-2018-maintenance/ for more information
WHAT’S NEW
Several U-M faculty affiliated with MIDAS will participate in the KDD2018 Conference in London in August. The meeting is held by the Associate for Computing Machinery's Special Interest Group in…
To accommodate updates to software, hardware, and operating systems, Flux, Armis, ConFlux, Flux Hadoop, and their storage systems (/home and /scratch) will be unavailable starting at 9 a.m. Sunday, August…
The Michigan Institute for Computational Discovery and Engineering has awarded its second round of Catalyst Grants, providing between $80,000 and $90,000 each to seven innovative projects in computational science. The…
The image competition for the Coalition for Academic Scientific Computation (CASC) 2019 annual brochure is now open. Winning images will be featured in the brochure, which is distributed to industry,…
July 26 @ 2:00 pm - 5:00 pm
This workshop will develop introductory concepts, tools, and techniques to model spatially referenced data observed over a regular or irregular grid. We will cover models such as spatial autoregressive that…
August 5 @ 8:00 am - August 9 @ 5:00 pm
To accommodate updates to software, hardware, and operating systems, Flux, Armis, ConFlux, Flux Hadoop, and their storage systems (/home and /scratch) will be unavailable starting at 9 a.m. Sunday, August...
August 6 @ 8:30 am - 4:30 pm
Please join us for the second annual Single-cell Genomic Data Analytics Symposium. The day long symposium will highlight researchers from U-M and around the world whose work is on the…
August 28 @ 2:00 pm - 4:30 pm
Geostatistics deals with continuous variation over space and emphasizes the idea of spatial correlation via covariance. It is widely used for spatial interpolation. We will use ArcGIS and R to…
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ARC-TS Highlights
U-M partners with Cavium on Big Data computing platform
A new partnership between the University of Michigan and Cavium Inc., a San Jose-based provider of semiconductor products, will create a powerful new Big Data computing cluster available to all U-M researchers.
The $3.5 million ThunderX computing cluster will enable U-M researchers to, for example, process massive amounts of data generated by remote sensors in distributed manufacturing environments, or by test fleets of automated and connected vehicles.
The cluster will run the Hortonworks Data Platform providing Spark, Hadoop MapReduce and other tools for large-scale data processing.
Learn about data science infrastructure and consulting resources
ARC-TS Director Brock Palen and CSCAR Director Kerby Shedden speak at the MIDAS 2017 Research Forum
U-M enjoys successful SC17 conference in Denver
Several University of Michigan researchers and professional IT staff attended the Supercomputing 17 (SC17) conference in Denver from Nov. 12-17, participating in a number of different ways, including demonstrations, presentations and tutorials.
Flux cluster available to undergraduates
Service available at no cost
Under ARC-TS’s new Flux for Undergraduates program, student groups and individuals with faculty sponsors can access Flux for free.
Yottabyte Research Cloud able to accept HIPAA-aligned data
ARC-TS is pleased to announce that the Yottabyte Research Cloud (YBRC) computing platform is now HIPAA-compliant. This means that YBRC and its associated services can accept restricted data, enabling secure data analysis on Windows and Linux virtual desktops as well as secure hosting of databases and data ingestion.
The new capability ensures the security of restricted data through the creation of firewalled network enclaves, allowing HIPAA-aligned data to be analyzed safely and securely in YBRC’s flexible, robust and scalable environment. Within each network enclave, researchers have access to Windows and Linux virtual desktops that can contain any software required for their analysis pipeline.
ARC-TS expands data-science platform
ARC-TS has expanded its data science computing platform, giving all U-M researchers new capabilities to host structured and unstructured databases, and to ingest, store, query and analyze large datasets.
The new platform features a flexible, robust and scalable database environment, and a set of data pipeline tools that can ingest and process large amounts of data from sensors, mobile devices and wearables, and other sources of streaming data. The platform leverages the advanced virtualization capabilities of ARC-TS’s Yottabyte Research Cloud (YBRC) infrastructure, and is supported by U-M’s Data Science Initiative launched in 2015.
