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WHAT’S NEW
The Michigan Institute for Data Science (MIDAS) is pleased to announce the winners of its 2018 poster competition, which is held in conjunction with the MIDAS annual symposium. The symposium…
The University of Michigan has selected Dell EMC as lead vendor to supply its new $4.8 million Great Lakes computing cluster, which will serve researchers across campus. Mellanox Technologies will…
The Michigan Institute for Computational Discovery and Engineering (MICDE) is pleased to announce the 2018-2019 recipients of the MICDE Fellowships for students enrolled in the PhD in Scientific Computing or…
Advanced Research Computing - Technology Services (ARC-TS) is seeking pilot users for two new research storage services. The first, Locker, is group project storage focused on large data sets, and…
October 22 @ 12:00 pm - 1:00 pm
Bio: Padmini Rangamani is an associate professor in Mechanical Engineering at the University of California, San Diego. She joined the department in July 2014. Earlier, she was a UC Berkeley…
October 23 @ 2:00 pm - 4:00 pm
Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including…
October 24 @ 9:00 am - 11:00 am
We’ll discuss mixed model regression (also known as multi-level models or hierarchical linear models) in this session which is used for repeated measures data or data which has a clustering…
October 24 @ 3:00 pm - 4:00 pm
Bio: Juan Pablo Vielma is the Richard S. Leghorn (1939) Career Development Associate Professor at MIT Sloan School of Management and is affiliated to MIT’s Operations Research Center. Dr. Vielma…
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.
