Christos Bellas
ABSTRACT
We investigate the problem of exact set similarity joins using a co-process CPU-GPU scheme. We focus on large instances of the problem, i.e., using datasets of >1M entries, which may take hours to complete if not approached with care, due to the inherent quadratic complexity of the problem. We introduce a novel CPU-GPU co-process scheme, which performs initial filtering and indexing on the CPU and delegates final verification to the GPU. Further, we show that this scheme improves upon the state-of-the-art in both the CPU and GPU standalone solutions in several cases.
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Index Terms
- Exact Set Similarity Joins for Large Datasets in the GPGPU paradigm
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