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Over the past few decades, the IR community has been making a continuous effort to improve the efficiency of search in large collections of documents. Query processing is still one of the main bottlenecks in large-scale search systems. The top-k document retrieval problem, which can be defined as reporting the k most relevant documents from a collection for a given query, can be extremely expensive, as it involves scoring large amounts of documents. In this work, we investigate the top-k document retrieval problem from several angles with the aim of improving the efficiency of this task in large-scale search systems. Finally, we briefly describe our initial findings and conclude by proposing future directions to follow.
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Dr. Top-k: Delegate-Centric Top-k on GPUs
- Award ID(s):
- 2000722
- PAR ID:
- 10312019
- Date Published:
- Journal Name:
- The International Conference for High Performance Computing, Networking, Storage and Analysis (SC 21)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3458817.3476141
