8,817 research outputs found
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 efforts in HPC cloud aim to understand the
cost-benefit of moving resource-intensive applications from on-premise
environments to public cloud platforms. Industry trends show hybrid
environments are the natural path to get the best of the on-premise and cloud
resources---steady (and sensitive) workloads can run on on-premise resources
and peak demand can leverage remote resources in a pay-as-you-go manner.
Nevertheless, there are plenty of questions to be answered in HPC cloud, which
range from how to extract the best performance of an unknown underlying
platform to what services are essential to make its usage easier. Moreover, the
discussion on the right pricing and contractual models to fit small and large
users is relevant for the sustainability of HPC clouds. This paper brings a
survey and taxonomy of efforts in HPC cloud and a vision on what we believe is
ahead of us, including a set of research challenges that, once tackled, can
help advance businesses and scientific discoveries. This becomes particularly
relevant due to the fast increasing wave of new HPC applications coming from
big data and artificial intelligence.Comment: 29 pages, 5 figures, Published in ACM Computing Surveys (CSUR
Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services
One of the most widely-implemented service standards provided by the Open
Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS).
WMS is widely employed globally, but there is limited knowledge of the global
distribution, adoption status or the service quality of these online WMS
resources. To fill this void, we investigated global WMSs resources and
performed distributed performance monitoring of these services. This paper
explicates a distributed monitoring framework that was used to monitor 46,296
WMSs continuously for over one year and a crawling method to discover these
WMSs. We analyzed server locations, provider types, themes, the spatiotemporal
coverage of map layers and the service versions for 41,703 valid WMSs.
Furthermore, we appraised the stability and performance of basic operations for
1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major
reasons for request errors and performance issues, as well as the relationship
between service response times and the spatiotemporal distribution of client
monitoring sites. This paper will help service providers, end users and
developers of standards to grasp the status of global WMS resources, as well as
to understand the adoption status of OGC standards. The conclusions drawn in
this paper can benefit geospatial resource discovery, service performance
evaluation and guide service performance improvements.Comment: 24 pages; 15 figure
- …