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Article summary:

1. SciSpace is a proposed scientific collaboration workspace for geo-distributed HPC data centers, which provides a global view of information shared from multiple sites under a single workspace.

2. SciSpace supports native data-access to gain high-performance when data read or write is required in native data center namespace, and implements search and discovery service to optimize scientific collaborations across HPC data centers.

3. Evaluation results show average 36% performance boost when the proposed native-data access is employed in collaborations, and SciSpace is shown to be feasible using real scientific datasets and applications.

Article analysis:

The article “SciSpace: A Scientific Collaboration Workspace for Geo-Distributed HPC Data Centers” presents an interesting concept of a collaboration workspace for geographically dispersed HPC data centers. The article provides an overview of the proposed system, its design goals, and implementation details, as well as evaluation results showing improved performance when using the proposed system.

The article appears to be reliable overall, with clear explanations of the concepts presented and evidence provided to support the claims made. The authors provide detailed descriptions of their design goals and implementation details, as well as evaluation results showing improved performance when using the proposed system. Additionally, they provide references to related work in order to demonstrate how their approach differs from existing solutions.

However, there are some potential biases that should be noted in this article. For example, while the authors do mention some potential risks associated with their approach (e.g., security risks), they do not explore these risks in depth or discuss possible solutions for mitigating them. Additionally, while they do provide references to related work in order to demonstrate how their approach differs from existing solutions, they do not present both sides equally; instead they focus primarily on highlighting the advantages of their own approach over existing solutions without exploring any potential drawbacks or limitations that may exist with their own approach. Finally, it should also be noted that while the authors provide evidence supporting their claims (e.g., evaluation results), it is unclear if this evidence was obtained through rigorous testing or if it was simply anecdotal evidence based on limited testing scenarios; thus it would be beneficial if more detailed information about the testing process was provided in order to better assess the reliability of these claims.