TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhysCodeb.10
TI  - Automatic transformation of irreducible representations for efficient contraction of tensors with cyclic group symmetry
PY  - 2023/02/24
UR  - https://www.scipost.org/SciPostPhysCodeb.10
JF  - SciPost Physics Codebases
JA  - SciPost Phys. Codebases
SP  - 10
A1  - Gao, Yang
AU  - Helms, Phillip
AU  - Chan, Garnet Kin-Lic
AU  - Solomonik, Edgar
AB  - Tensor contractions are ubiquitous in computational chemistry and physics, where tensors generally represent states or operators and contractions express the algebra of these quantities. In this context, the states and operators often preserve physical conservation laws, which are manifested as group symmetries in the tensors. These group symmetries imply that each tensor has block sparsity and can be stored in a reduced form. For nontrivial contractions, the memory footprint and cost are lowered, respectively, by a linear and a quadratic factor in the number of symmetry sectors. State-of-the-art tensor contraction software libraries exploit this opportunity by iterating over blocks or using general block-sparse tensor representations. Both approaches entail overhead in performance and code complexity. With intuition aided by tensor diagrams, we present a technique, irreducible representation alignment, which enables efficient handling of Abelian group symmetries via only dense tensors, by using contraction-specific reduced forms. This technique yields a general algorithm for arbitrary group symmetric contractions, which we implement in Python and apply to a variety of representative contractions from quantum chemistry and tensor network methods. As a consequence of relying on only dense tensor contractions, we can easily make use of efficient batched matrix multiplication via Intel's MKL and distributed tensor contraction via the Cyclops library, achieving good efficiency and parallel scalability on up to 4096 Knights Landing cores of a supercomputer.
ER  -

@Article{10.21468/SciPostPhysCodeb.10,
	title={{Automatic transformation of irreducible representations for efficient contraction of tensors with cyclic group symmetry}},
	author={Yang Gao and Phillip Helms and Garnet Kin-Lic Chan and Edgar Solomonik},
	journal={SciPost Phys. Codebases},
	pages={10},
	year={2023},
	publisher={SciPost},
	doi={10.21468/SciPostPhysCodeb.10},
	url={https://scipost.org/10.21468/SciPostPhysCodeb.10},
}

@Article{10.21468/SciPostPhysCodeb.10-r1.3,
	title={{Codebase release 1.3 for SymTensor}},
	author={Yang Gao and Phillip Helms and Garnet Kin-Lic Chan and Edgar Solomonik},
	journal={SciPost Phys. Codebases},
	pages={10-r1.3},
	year={2023},
	publisher={SciPost},
	doi={10.21468/SciPostPhysCodeb.10-r1.3},
	url={https://scipost.org/10.21468/SciPostPhysCodeb.10-r1.3},
}