Learn more about ARC-TS offerings:
August 18 @ 2:00 pm - 4:30 pm
A BlueJeans link will be sent to all registered participants. 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…
August 19 @ 2:00 pm - 4:00 pm
This workshop will introduce participants to using R for presenting data-driven results, with an eye toward reproducible methods. After an introduction to concepts related to reproducible programming and research, demonstrations of…
September 22 @ 10:00 am - 12:00 pm
This workshop will introduce you to the NumPy library in Python, which is useful in scientific computing. We will cover NumPy’s n-dimensional array object and associated functions in depth, along…
October 13 @ 10:00 am - 12:00 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 the popular library TensorFlow. In this workshop, participants will learn…
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
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.
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.
ARC-TS Overview and Update on Storage Services and Development of the Great Lakes HPC Cluster
ARC-TS Director Brock Palen speaks at a DDN Storage event at the SC18 conference in Dallas.
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.