HPC cloud for scientific and business applications: taxonomy, vision, and research challenges
High performance computing (HPC) clouds are becoming an alternative to on-premise
clusters for executing scientific applications and business analytics services. Most research …
clusters for executing scientific applications and business analytics services. Most research …
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 …
Carbonscaler: Leveraging cloud workload elasticity for optimizing carbon-efficiency
Cloud platforms are increasing their emphasis on sustainability and reducing their
operational carbon footprint. A common approach for reducing carbon emissions is to exploit …
operational carbon footprint. A common approach for reducing carbon emissions is to exploit …
Combining machine learning techniques and genetic algorithm for predicting run times of high performance computing jobs
This study proposes a novel approach combining Machine Learning (ML) techniques and
Genetic Algorithms (GA) for predicting High-Performance Computing (HPC) job run times …
Genetic Algorithms (GA) for predicting High-Performance Computing (HPC) job run times …
An adaptive task allocation technique for green cloud computing
The rapid growth of todays IT demands reflects the increased use of cloud data centers.
Reducing computational power consumption in cloud data center is one of the challenging …
Reducing computational power consumption in cloud data center is one of the challenging …
HPC-ENHANCED TRAINING OF LARGE AI MODELS IN THE CLOUD
AI has made significant strides in recent years, particularly in the development of large
models that require substantial computational resources for training. High-Performance …
models that require substantial computational resources for training. High-Performance …
Hybrid scheduling for scientific workflows on hybrid clouds
Scientific workflows consist of many interdependent tasks dictated by their data
dependencies. As these workflows are becoming resource-intensive in both data and …
dependencies. As these workflows are becoming resource-intensive in both data and …
Vm reassignment in hybrid clouds for large decentralised companies: A multi-objective challenge
Optimising the data centres of large IT organisations is complex as (i) they are composed of
various hosting departments with their own preferences and (ii) reassignment solutions can …
various hosting departments with their own preferences and (ii) reassignment solutions can …
[PDF][PDF] A Study of Job Failure Prediction at Job Submit-State and Job Start-State in High-Performance Computing System: Using Decision Tree Algorithms [J]
In High-Performance Computing (HPC) system, job failure is a major problem because it
means the losses in computation time, resources, and power. Job failure also degrades …
means the losses in computation time, resources, and power. Job failure also degrades …
Hel** HPC users specify job memory requirements via machine learning
Resource allocation in High Performance Computing (HPC) settings is still not easy for end-
users due to the wide variety of application and environment configuration options. Users …
users due to the wide variety of application and environment configuration options. Users …