English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The amount of data generated by numerical simulations in various scientificdomains such as molecular dynamics, climate modeling, biology, or astrophysics,led to a fundamental redesign of application workflows. The throughput and thecapacity of storage subsystems have not evolved as fast as the computing powerin extreme-scale supercomputers. As a result, the classical post-hoc analysisof simulation outputs became highly inefficient. In-situ workflows have thenemerged as a solution in which simulation and data analytics are intertwinedthrough shared computing resources, thus lower latencies. Determining the bestallocation, i.e., how many resources to allocate to each component of anin-situ workflow; and mapping, i.e., where and at which frequency to run thedata analytics component, is a complex task whose performance assessment iscrucial to the efficient execution of in-situ workflows. However, such aperformance evaluation of different allocation and mapping strategies usuallyrelies either on directly running them on the targeted execution environments,which can rapidly become extremely time-and resource-consuming, or on resortingto the simulation of simplified models of the components of an in-situworkflow, which can lack of realism. In both cases, the validity of theperformance evaluation is limited. To address this issue, we introduceSIM-SITU, a framework for the faithful simulation of in-situ workflows. Thisframework builds on the SimGrid toolkit and benefits of several importantfeatures of this versatile simulation tool. We designed SIM-SITU to reflect thetypical structure of in-situ workflows and thanks to its modular design,SIM-SITU has the necessary flexibility to easily and faithfully evaluate thebehavior and performance of various allocation and mapping strategies forin-situ workflows. We illustrate the simulation capabilities of SIM-SITU on aMolecular Dynamics use case. We study the impact of different allocation andmapping strategies on performance and show how users can leverage SIM-SITU todetermine interesting tradeoffs when designing their in-situ workflow.

SIM-SITU: A Framework for the Faithful Simulation of in-situ Workflows