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Ioan Raicu

Researcher at Illinois Institute of Technology

Publications -  144
Citations -  8771

Ioan Raicu is an academic researcher from Illinois Institute of Technology. The author has contributed to research in topics: Scalability & Cloud computing. The author has an hindex of 40, co-authored 141 publications receiving 8460 citations. Previous affiliations of Ioan Raicu include Wayne State University & Northwestern University.

Papers
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Proceedings ArticleDOI

Cloud Computing and Grid Computing 360-Degree Compared

TL;DR: In this article, the authors compare and contrast cloud computing with grid computing from various angles and give insights into the essential characteristics of both the two technologies, and compare the advantages of grid computing and cloud computing.
Proceedings ArticleDOI

The Globus Striped GridFTP Framework and Server

TL;DR: It is argued that this combination of performance and modular structure make the Globus GridFTP framework both a good foundation on which to build tools and applications, and a unique testbed for the study of innovative data management techniques and network protocols.
Proceedings ArticleDOI

Swift: Fast, Reliable, Loosely Coupled Parallel Computation

TL;DR: Swift adopts and adapts ideas first explored in the GriPhyN virtual data system, improving on that system in many regards and describes application experiences and performance experiments that quantify the cost of Swift operations.
Proceedings ArticleDOI

Falkon: a Fast and Light-weight tasK executiON framework

TL;DR: Falkon's integration of multi-level scheduling and streamlined dispatchers delivers performance not provided by any other system, and large-scale astronomy and medical applications executed under Falkon by the Swift parallel programming system achieve up to 90% reduction in end-to-end run time.
Proceedings ArticleDOI

Many-task computing for grids and supercomputers

TL;DR: Many-task computing aims to bridge the gap between two computing paradigms, high throughput computing and high performance computing, drawing attention to the many computations that are heterogeneous but not ldquohappilyrdquo parallel.