4 research outputs found
Trace-Driven Simulation for Energy Consumption in High Throughput Computing Systems
High Throughput Computing (HTC) is a powerful paradigm allowing vast quantities of independent work to be performed simultaneously. However, until recently little evaluation has been performed on the energy impact of HTC. Many organisations now seek to minimise energy consumption across their IT infrastructure though it is unclear how this will affect the usability of HTC systems. We present here HTC-Sim, a simulation system which allows the evaluation of different energy reduction policies across an HTC system comprising a collection of computational resources dedicated to HTC work and resources provided through cycle scavenging -- a Desktop Grid. We demonstrate that our simulation software scales linearly with increasing HTC workload
Operating policies for energy efficient large scale computing
PhD ThesisEnergy costs now dominate IT infrastructure total cost of ownership, with datacentre
operators predicted to spend more on energy than hardware infrastructure in the
next five years. With Western European datacentre power consumption estimated at
56 TWh/year in 2007 and projected to double by 2020, improvements in energy efficiency
of IT operations is imperative. The issue is further compounded by social and
political factors and strict environmental legislation governing organisations.
One such example of large IT systems includes high-throughput cycle stealing distributed
systems such as HTCondor and BOINC, which allow organisations to leverage
spare capacity on existing infrastructure to undertake valuable computation.
As a consequence of increased scrutiny of the energy impact of these systems, aggressive
power management policies are often employed to reduce the energy impact
of institutional clusters, but in doing so these policies severely restrict the computational
resources available for high-throughput systems. These policies are often configured
to quickly transition servers and end-user cluster machines into low power
states after only short idle periods, further compounding the issue of reliability.
In this thesis, we evaluate operating policies for energy efficiency in large-scale
computing environments by means of trace-driven discrete event simulation, leveraging
real-world workload traces collected within Newcastle University.
The major contributions of this thesis are as follows:
i) Evaluation of novel energy efficient management policies for a decentralised
peer-to-peer (P2P) BitTorrent environment.
ii) Introduce a novel simulation environment for the evaluation of energy efficiency
of large scale high-throughput computing systems, and propose a generalisable
model of energy consumption in high-throughput computing systems.
iii
iii) Proposal and evaluation of resource allocation strategies for energy consumption
in high-throughput computing systems for a real workload.
iv) Proposal and evaluation for a realworkload ofmechanisms to reduce wasted task
execution within high-throughput computing systems to reduce energy consumption.
v) Evaluation of the impact of fault tolerance mechanisms on energy consumption
Improving energy-efficiency of grid computing clusters
Electricity is a significant cost in high performance computing. It can easily exceed the cost of hardware during hardware lifetime. We have studied energy efficiency in a grid computing cluster and noticed that optimising the system configuration can both decrease energy consumption per job and increase throughput. The goal with the proposed saving scheme was that it is easy to implement in normal HPC clusters. Our tests showed that the savings can be up to 25%. The tests were done with real-life high-energy physics jobs