2010-12-01: Energy-efficient cloud computing using hardware
diversity and elastic scalability (GreenClouds) grant awarded: NWO
page, in
news section (Dutch)
GreenClouds @ VU & UvA
The GreenClouds project studies how to reduce the energy footprint of
modern High Performance Computing systems (like Clouds) that are
distributed, elastically scalable, and contain a variety of hardware
(accelerators and hybrid networks). The project takes a system-level
approach and studies the problem of how to map high-performance
applications onto such distributed systems, taking both performance and
energy consumption into account. We will explore three ideas to reduce
energy:
Exploit the diversity of computing architectures (e.g. GPUs,
multicores) to run computations on those architectures that perform
them in the most energy-efficient way;
Dynamically adapt the number of resources to the application
needs accounting for computational and energy efficiency;
Use optical and photonic networks to transport data and
computations in a more energy-efficient way.
The project will create the GreenClouds Knowledge Base System (GKBS)
based on semantic web technology, which will provide detailed
information on the energy characteristics of various applications
(e.g., obtained from previous execution runs) and the different parts
of the distributed system, including the network. Also, the project
will study a broad range of applications and determine which classes of
applications can reduce their energy consumption using accelerators.
Finally, it will study energy reductions through dynamic adaptation of
computing and networking resources. The project will make extensive use
of the DAS-4 infrastructure, which is a wide-area testbed for computer
scientists, to be equipped with many types of accelerators, a photonic
network, and energy sensors.
The results of the project will be utilized by the SARA national HPC
center that operates a supercomputer, clusters, accelerator systems,
and an HPC cloud. Today, the costs of energy over the lifetime of these
systems are already larger than their acquisition costs, so reducing
energy is vitally important for centers like SARA. Moreover, the
results will be utilized in DAS-4 itself.
Student
Projects @ UvA
Vesselin Hadjitodorov, Ralph Koning and Paola Grosso, "Power
measuremeents in DAS4 experimantal cluster.", UvA SNE RP jan 2011.
