The Yottabyte Research Cloud is a partnership between ARC and Yottabyte that will provide U-M researchers with high performance, secure and flexible computing environments that enable the analysis of sensitive data sets restricted by federal privacy laws, proprietary access agreements, or confidentiality requirements.
The system is built on Yottabyte’s software-defined infrastructure, known as yCenter and YottaBlox, and represents U-M’s first use of software-defined infrastructure for research, allowing the on-the-fly personalized configuration of any-scale computing resources. Yottabyte donated $5.5 million worth of hardware and software to U-M to setup the system, and U-M contributed another $2 million to support delivery of services to researchers and for general operations.
yCenter SDI software translates the physical CPU, RAM and storage components of YottaBlox appliances into definable and configurable virtual resource groups that may be used to build multi-tenant, multi-site cloud infrastructures. Each yCenter instance manages clusters of physical hyper-converged, compute, storage and network fabric YottaBlox. These resources are organized and represented virtually into one or many virtual nodes, tenants, virtual datacenters (VDC) and virtual machine (VM) resource containers.
See the Sept. 2016 press release for more information.
The system deploys 40 high performance Hyperconverged YottaBlox nodes (H2400i-E5), each consisting of two, Intel Xeon E5-2680V4 CPU (1,120 cores total), 512GB DDR4 2400MHz RAM (20,480GB total), dual port 40GbE network adapters (80 total) and (2) 800GB NVMe SSD DC P3700 drives (64TB); and 20 storage YottaBlox nodes (S2400i-E5-HDD), each consisting of two, Intel Xeon E5-2620V4 CPU (320 cores total), 128 GB DDR4 2133MHz RAM (2,560 GB total), quad port 10GbE network adapters (80 total), (2) 800 GB DC S3610 SSD (32 TB total) and 12 x 6 TB 7200 RPM (1,440TB total).
The Yottabyte Research Cloud is currently under development. ARC-TS will expand Yottabyte Research Cloud service offerings over the next several months; the target date for full-scale deployment is early 2017.