Sharon Broude GevaDirector of Advanced Research Computing (ARC)University of Michigansgeva@umich.eduhttp://arc.umich.edu

NewAdvanced Research

Computing Projects & Services at U-M

2015 CASC Fall Meeting - 10/15/2015

Advanced Research Computing

U-M Data Science Initiative

● U-M investment of $100M over next 5 years○ Hire 35 new faculty over the next four years and

engage existing faculty across campus;○ Support interdisciplinary data-related research

initiatives and foster new methodological approaches to big data;

○ provide new educational opportunities for students pursuing careers in data science;

○ expand U-M’s research computing capacity; and○ strengthen data management, storage,

analytics, and training resources.● 1500+ registrants for kick-off symposium last week

U-M Data Science Initiative

Faculty affiliates, challenge grants, graduate certificate, industry engagement

Data Science infrastructure build and operations

Data Science consultants and training

CC*DNI Award: MI-OSiRIS

● PI: Shawn McKee (U-M Physics, ARC)● Co-PI’s: Swany (IU), Gossman (WSU), Merz

(MSU)● $4.9 Million (NSF)● Will provide a distributed, multi-institutional storage

IF that allows researchers at any of the three campuses to read, write, manage, and share data from their computing facility locations

● Goal - Provide transparent high-performance access to the same storage IF from well-connected locations on any of the three campuses

CC*DNI Award: MI-OSiRIS

● Will include network discovery, monitoring and management tools and creative use of CEPH features

● Users get customized data interfaces for their multi-institutional data needs

● Seamless rebalancing and expansion of storage● Data sharing, archiving, security, and life-cycle

management implemented and maintained with single distributed service

● Data IF view for each research domain can be optimized

CC*DNI Award: MI-OSiRIS

Center for Network and Storage-Enabled Collaborative Computational Science

Build and operations at U-M

MRI Award: ConFlux

● PI: Karthik Duraisamy (Aerospace Engineering)● $3.5 Million ($2.42M NSF + $1.04M cost-share) ● Designed to enable HPC simulations to interface

with large datasets while running● To refine complex physics-based models with Big

Data techniques (For cardiovascular disease; turbulence; clouds, rainfall, climate; dark matter, dark energy; material property prediction)

● CPU’s + GPU’s, large memory, ultra-fast interconnect, 3 PB hard drive

● Optimized hardware for machine learning● Plan to expand availability to researchers and

schools outside the grant team

MRI Award: ConFlux

Center for Data-Driven Computational Physics

Technical design, build, and operations

Turbo: High Performance Research Storage

● Isilon scalable storage for U-M researchers● Configured to be easily shareable with on-campus

resources such as the Flux HPC cluster, as well as off-campus systems and collaborators

● Performance sufficient for both IO-intensive operations and bulk file access, allowing researchers to work with data in place and avoid excessive data staging

● Primary tiered storage - Hybrid w/SSDs● Tuned for large files (1MB or greater) but capable of

handling small files (e.g., documents, spreadsheets, etc.)

Turbo: High Performance Research Storage

● NFSv3 and NFSv4 access (for Linux, Mavericks, Yosemite, Windows 7+)

● NFSv4 w/Kerberos access (Linux and Mavericks)● Two security levels:

○ regulated and/or sensitive data (PHI only w/Kerberos)

○ non-sensitive data ● Globus available for volumes that do not contain

PHI, for sharing and hosting data for external collaborators and institutes.

● Currently 1PB usable, replicated to 1PB DR● Cost: $19.20 / TB / Month (Optional daily snapshots

available at no cost)

Turbo: High Performance Research Storage

Technical design, build, and operations