AEGLE's Cloud Infrastructure for Resource Monitoring and Containerized Accelerated Analytics
Konstantina Koliogeorgi (National Technical University of Athens)
Dimosthenis Masouros (National Technical University of Athens)
Georgios Zervakis (National Technical University of Athens)
Sotirios Xydis (National Technical University of Athens)
Tobias Becker (Maxeler Technologies)
Georgi N. Gaydadjiev (Maxeler Technologies)
Dimitrios Soudris (National Technical University of Athens)
More Info
expand_more
Abstract
This paper presents the cloud infrastructure of the AEGLE project, that targets to integrate cloud technologies together with heterogeneous reconfigurable computing in large scale healthcare systems for Big Bio-Data analytics. AEGLEs engineering concept brings together the hot big-data engines with emerging acceleration technologies, putting the basis for personalized and integrated health-care services, while also promoting related research activities. We introduce the design of AEGLE's accelerated infrastructure along with the corresponding software and hardware acceleration stacks to support various big data analytics workloads showing that through effective resource containerization AEGLE's cloud infrastructure is able to support high heterogeneity regarding to storage types, execution engines, utilized tools and execution platforms. Special care is given to the integration of high performance accelerators within the overall software stack of AEGLE's infrastructure, which enable efficient execution of analytics, up to 140× according to our preliminary evaluations, over pure software executions.
No files available
Metadata only record. There are no files for this record.