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Conference papers
Analytical Cache Modeling and Tilesize Optimization for Tensor Contractions
Abstract : Data movement between processor and memory hierarchy
is a fundamental bottleneck that limits the performance of
many applications on modern computer architectures. Tiling
and loop permutation are key techniques for improving data
locality. However, selecting effective tile-sizes and loop permutations is particularly challenging for tensor contractions due
to the large number of loops. Even state-of-the-art compilers
usually produce sub-optimal tile-sizes and loop permutations,
as they rely on naive cost models. In this paper we provide an analytical model based approach to multi-level tile
size optimization and permutation selection for tensor contractions. Our experimental results show that this approach
achieves comparable or better performance than state-of-theart frameworks and libraries for tensor contractions.
Cited literature [19 references]
https://hal.inria.fr/hal-02418875
Contributor : Fabrice Rastello <>
Submitted on : Thursday, December 19, 2019 - 10:53:57 AM
Last modification on : Tuesday, May 11, 2021 - 11:37:50 AM
Long-term archiving on: : Friday, March 20, 2020 - 2:10:45 PM
Contributor : Fabrice Rastello <>
Submitted on : Thursday, December 19, 2019 - 10:53:57 AM
Last modification on : Tuesday, May 11, 2021 - 11:37:50 AM
Long-term archiving on: : Friday, March 20, 2020 - 2:10:45 PM
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