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.