Abstract: Numerous studies have proposed hardware architectures to accelerate sparse matrix multiplication, but these approaches often incur substantial area and power overhead, significantly ...
This is a benchmarking tool for Qdrant's sparse vector implementation using the NeurIPS 2023 datasets. This task is based on the common MSMARCO passage retrieval dataset, which has 8,841,823 text ...
Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...
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