Rapid advancements in imaging technology have provided researchers with the ability to produce very high-resolution, time-varying, multidimensional datasets of the human brain. Population-based longitudinal studies using this data drive a continually-increasing demand for compute power.
SUN MICROSYSTEMS V20z CLUSTER & X2200 M2 CLUSTER
Today, LONI utilizes a 306-node, dual-processor SUN Microsystems V20z cluster, one of the largest V20z installations in the world. Each V20z compute node has dual 64-bit 2.4 gigahertz AMD Opteron 250 CPUs with 8 gigabytes of memory. LONI has additionally integrated an 80-node, eight-processor SUN Microsystems X2200 M2 installation. Each X2200 M2 has eight 64-bit 1.1 gigahertz AMD Opteron 2354 cores with 16 gigabytes of memory.
DELL DEVELOPMENT CLUSTER
In addition to the SUN clusters, LONI has a 64-node Dell development cluster, with each node using dual 64-bit 3.6 gigahertz Intel EM64T processors and 4 gigabytes of memory.
To augment the facility's cluster resources, LONI has a 64-processor SGI Origin 3800 SMP supercomputer with 32 gigabytes of memory. A comparable 32-processor SGI Onyx2 Reality Monster with 16 gigabytes of memory and a 6-processor SGI Onyx2 with 8 gigabytes of memory SMP supercomputers are utilized to drive graphics-intensive applications and interactive real-time multidimensional visualization of structural brain models and volumetric datasets.
LONI GRID MONITOR VISUALIZATION
The LONI Grid Monitor is a web applet that allows for real-time inspection of the status of the background computational Grid. The three-dimensional visualization gives users a quick, intuitive feel for the current usage of the cluster; each bar on the ring represents a single execution node, and the height of each bar represents that node's usage.
SUN GRID ENGINE
To facilitate the submission and execution of compute jobs in this heterogeneous compute environment, SUN's Grid Engine (SGE) is used to virtualize the resources above into a compute service. A grid layer sits atop the compute resources and submits jobs to available resources according to user-defined criteria such as CPU type, processor count, etc. The laboratory has successfully integrated the latest version of the LONI Pipeline (http://pipeline.loni.ucla.edu) with SGE using SUN's JGDI interface. This allows jobs to be natively submitted from the LONI Pipeline to the grid without the need for external scripts. Furthermore, the LONI Pipeline can directly control the grid, significantly increasing the operating environment's versatility and efficacy, and improving overall end-user experience.