Skip to content Skip to navigation

Networks and Distributed Systems

 

 

Associated Projects

Thu D. Nguyen

Parasol is a green micro-datacenter partially powered by solar energy and partially cooled by "free-cooling".  It comprises a small container, a set of solar panels, and batteries. The container lies on a steel structure placed on the roof of our building. The solar panels are mounted on top of the steel structure and shade the container from the sun. The container hosts two racks of energy-efficient servers (up to 160 of them) and networking equipment. The container uses free cooling whenever possible, and direct-exchange air conditioning otherwise.

Manish Parashar

The GreenHPC initiative at Rutgers is a research and educational initiative aiming at addressing several efforts in the intersection of energy efficiency, scalable computing and high performance computing. Key focus areas include (1) Energy efficiency of scientific data analysis pipelines at scale, (2) In-situ data analytics and co-processing at extreme scales and (3) Application-aware cross-layer power management for High Performance Computing systems .GreenHPC also acts as a forum for researchers and the educational community to exchange ideas and experiences on energy efficiency by disseminating research results, educational activities at different levels (PhD, MS, undergraduate - REU, K12 - GSET) and organizing events and editorial activities of related topics

DataSpaces is a programming system targeted at current large-scale systems and designed to support dynamic interaction and coordination patterns between scientific applications. DataSpaces essentially provides a semantically specialized shared-space abstraction using a set of staging nodes. This abstraction derives from the tuple-space model and can be associatively accessed by the interacting applications of a simulation workflow. DataSpaces also provides services including distributed in-memory associative object store, scalable messaging, as well as runtime mapping and scheduling of online data analysis operations.

The overreaching goal of CometCloud is to enable highly heterogeneous, dynamically federated computing and data platforms that can support end-to-end application workflows with diverse and dynamic changing application requirements. This is achieved through (a) autonomic on-demand federation of geographically distributed compute and data resources as needed by the application workflow, and (b) exposing the resulting software-defined federated cyberinfrastructure using elastic cloud abstractions and science-as-a-service platforms. As a result, CometCloud is able to create a nimble and dynamically programmable environment that autonomously evolves over time, adapting to changes in both the federated infrastructure and the application requirements.