Analytical Model for Pre-Alignment Filtering in Memory

DOI:10.4121/6cfdc8d8-67a1-48f0-ac77-87fb12bf316f.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/6cfdc8d8-67a1-48f0-ac77-87fb12bf316f
Datacite citation style:
Shahroodi, Taha; Miao, Michael (2023): Analytical Model for Pre-Alignment Filtering in Memory . Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/6cfdc8d8-67a1-48f0-ac77-87fb12bf316f.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Analytical Model for Pre-Alignment Filtering in Memory used for the evaluation of the paper titled RattlesnakeJake: A Fast and Accurate Pre-Alignment Filter Suitable for Computation-in-Memory and the M.Sc. thesis of Michael Miao at QCE department. This analytical model is used to calculate the resource requirements (tile sizes, etc.) for the architectures in the research presented in the paper and the thesis given a genomic dataset.

History

  • 2023-09-04 first online, published, posted

Publisher

4TU.ResearchData

Format

zipped shape files

Organizations

TU Delft, Faculty of Engineering, Mathematics and Computer Science (EEMCS/EWI), Department of Quantum & Computer Engineering (QCE)
Eidgenössische Technische Hochschule (ETH) Zürich

DATA - restricted access

Reason

Discussions in the Data Management Plan (DMP) Agreement. 

End User Licence Agreement

The data that support all the results within this paper and other findings of this study are available from the corresponding author upon reasonable request.

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