Cloud Computing for parallel Scientific HPC Applications: Feasibility of Running Coupled Atmosphere-

By C. Evangelinos, C. Hill. 2008

327 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Big Data and cloud computing: innovation opportunities and challenges (2017, unknown): “…include supporting geodatabase management (Cary et al. 2010), retrieving and indexing spatial data (Wang et al. 2009), running climate models (Evangelinos and Hill 2008), supporting dust storm forecasting (Huang et al. 2013a), optimizing spatial web portals (Xia et al. 2015b) and even…”
High-Performance Cloud Computing: A View of Scientific Applications (2009, background): “Some studies investigated the benefit of using Cloud computing technologies by analyzing the performances of HPC scientific applications [13] or the cost of performing scientific experiments [14] on the Amazon Cloud infrastructure.”
Cost optimized provisioning of elastic resources for application workflows (2011, methodology): “For example, the Pegasus WMS [7] can manage the execution of complex application workflows on virtual machines acquired from Amazon EC2 [30] [31].”
Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud (2010, unknown): “Various groups have run both standard benchmark suites such as Linpack and NAS [5], [6], [7], [8], [9], and network performance tests [10].”
Toward a Unified Ontology of Cloud Computing (2008, background): “Additionally, studies like [54], [55] have evaluated the deployment and performance benefits of porting specific scientific parallel applications to Amazon’s EC2 cloud.”