Predictive performance modeling for distributed batch processing using black box monitoring and machine learning
In many domains, the previous decade was characterized by increasing data volumes and
growing complexity of data analyses, creating new demands for batch processing on …
growing complexity of data analyses, creating new demands for batch processing on …
Sustainable computing across datacenters: A review of enabling models and techniques
The growth rate in big data and internet of things (IoT) is far exceeding the computer
performance rate at which modern processors can compute on the massive amount of data …
performance rate at which modern processors can compute on the massive amount of data …
Greenslot: scheduling energy consumption in green datacenters
In this paper, we propose GreenSlot, a parallel batch job scheduler for a datacenter
powered by a photovoltaic solar array and the electrical grid (as a backup). GreenSlot …
powered by a photovoltaic solar array and the electrical grid (as a backup). GreenSlot …
On the use of machine learning to predict the time and resources consumed by applications
A Matsunaga, JAB Fortes - 2010 10th IEEE/ACM International …, 2010 - ieeexplore.ieee.org
Most data centers, clouds and grids consist of multiple generations of computing systems,
each with different performance profiles, posing a challenge to job schedulers in achieving …
each with different performance profiles, posing a challenge to job schedulers in achieving …
Failure-aware resource provisioning for hybrid cloud infrastructure
Hybrid Cloud computing is receiving increasing attention in recent days. In order to realize
the full potential of the hybrid Cloud platform, an architectural framework for efficiently …
the full potential of the hybrid Cloud platform, an architectural framework for efficiently …
Online cost-efficient scheduling of deadline-constrained workloads on hybrid clouds
R Van den Bossche, K Vanmechelen… - Future Generation …, 2013 - Elsevier
Cloud computing has found broad acceptance in both industry and research, with public
cloud offerings now often used in conjunction with privately owned infrastructure. Technical …
cloud offerings now often used in conjunction with privately owned infrastructure. Technical …
Stratus: Cost-aware container scheduling in the public cloud
Stratus is a new cluster scheduler specialized for orchestrating batch job execution on virtual
clusters, dynamically allocated collections of virtual machine instances on public IaaS …
clusters, dynamically allocated collections of virtual machine instances on public IaaS …
Improving backfilling by using machine learning to predict running times
E Gaussier, D Glesser, V Reis, D Trystram - Proceedings of the …, 2015 - dl.acm.org
The job management system is the HPC middleware responsible for distributing computing
power to applications. While such systems generate an ever increasing amount of data, they …
power to applications. While such systems generate an ever increasing amount of data, they …
Spatio-temporal thermal-aware job scheduling to minimize energy consumption in virtualized heterogeneous data centers
Job scheduling in data centers can be considered from a cyber–physical point of view, as it
affects the data center's computing performance (ie the cyber aspect) and energy efficiency …
affects the data center's computing performance (ie the cyber aspect) and energy efficiency …
Supporting GPU sharing in cloud environments with a transparent runtime consolidation framework
Driven by the emergence of GPUs as a major player in high performance computing and the
rapidly growing popularity of cloud environments, GPU instances are now being offered by …
rapidly growing popularity of cloud environments, GPU instances are now being offered by …