Functional Verification for Pre-Alignment Filtering in Memory

doi:10.4121/84a4f4f9-f09a-4487-a1ee-4bfe7e734301.v1
The doi 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: 10.4121/84a4f4f9-f09a-4487-a1ee-4bfe7e734301
Datacite citation style:
Shahroodi, Taha; Miao, Michael (2023): Functional Verification for Pre-Alignment Filtering in Memory. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/84a4f4f9-f09a-4487-a1ee-4bfe7e734301.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

Functional Verification for Pre-Alignment Filtering in Memory used for the evaluation of the papers titled RattlesnakeJake: A Fast and Accurate Pre-Alignment Filter Suitable for Computation-in-Memory, SieveMem : A Computation-in-Memory Architecture for Fast and Accurate Pre-Alignment , and the M.Sc. thesis of Michael Miao at QCE department.  

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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