Cyclops Tensor Framework: Reducing Communication and Eliminating Load Imbalance in Massively Parallel Contractions

Cyclops (cyclic-operations) Tensor Framework (CTF) 1 is a distributed library for tensor contractions. CTF aims to scale high-dimensional tensor contractions such as those required in the Coupled Cluster (CC) electronic structure method to massively-parallel supercomputers. The framework preserves t...

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Published in:2013 IEEE 27th International Symposium on Parallel and Distributed Processing pp. 813 - 824
Main Authors: Solomonik, Edgar, Matthews, Devin, Hammond, Jeff R., Demmel, James
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2013
Subjects:
Chemistry
Clustering algorithms
communication-avoiding algorithms
Coupled Cluster
Cyclops
Equations
Indexes
Manganese
Program processors
Tensile stress
tensor contractions
ISBN:146736066X, 9781467360661
ISSN:1530-2075
Online Access:Get full text
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Abstract Cyclops (cyclic-operations) Tensor Framework (CTF) 1 is a distributed library for tensor contractions. CTF aims to scale high-dimensional tensor contractions such as those required in the Coupled Cluster (CC) electronic structure method to massively-parallel supercomputers. The framework preserves tensor structure by subdividing tensors cyclically, producing a regular parallel decomposition. An internal virtualization layer provides completely general mapping support while maintaining ideal load balance. The mapping framework decides on the best mapping for each tensor contraction at run-time via explicit calculations of memory usage and communication volume. CTF employs a general redistribution kernel, which transposes tensors of any dimension between arbitrary distributed layouts, yet touches each piece of data only once. Sequential symmetric contractions are reduced to matrix multiplication calls via tensor index transpositions and partial unpacking. The user-level interface elegantly expresses arbitrary-dimensional generalized tensor contractions in the form of a domain specific language. We demonstrate performance of CC with single and double excitations on 8192 nodes of Blue Gene/Q and show that CTF outperforms NWChem on Cray XE6 supercomputers for benchmarked systems.
AbstractList Cyclops (cyclic-operations) Tensor Framework (CTF) 1 is a distributed library for tensor contractions. CTF aims to scale high-dimensional tensor contractions such as those required in the Coupled Cluster (CC) electronic structure method to massively-parallel supercomputers. The framework preserves tensor structure by subdividing tensors cyclically, producing a regular parallel decomposition. An internal virtualization layer provides completely general mapping support while maintaining ideal load balance. The mapping framework decides on the best mapping for each tensor contraction at run-time via explicit calculations of memory usage and communication volume. CTF employs a general redistribution kernel, which transposes tensors of any dimension between arbitrary distributed layouts, yet touches each piece of data only once. Sequential symmetric contractions are reduced to matrix multiplication calls via tensor index transpositions and partial unpacking. The user-level interface elegantly expresses arbitrary-dimensional generalized tensor contractions in the form of a domain specific language. We demonstrate performance of CC with single and double excitations on 8192 nodes of Blue Gene/Q and show that CTF outperforms NWChem on Cray XE6 supercomputers for benchmarked systems.
Author Hammond, Jeff R.
Matthews, Devin
Solomonik, Edgar
Demmel, James
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  surname: Solomonik
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  givenname: Devin
  surname: Matthews
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  organization: Austin Dept. Chem. & Biochem., Univ. of Texas, Austin, TX, USA
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  organization: Leadership Comput. Facility, Argonne Nat. Lab., Argonne, IL, USA
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  surname: Demmel
  fullname: Demmel, James
  organization: Berkeley Dept. EECS, Univ. of California, Berkeley, Berkeley, CA, USA
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Snippet Cyclops (cyclic-operations) Tensor Framework (CTF) 1 is a distributed library for tensor contractions. CTF aims to scale high-dimensional tensor contractions...
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StartPage 813
SubjectTerms Chemistry
Clustering algorithms
communication-avoiding algorithms
Coupled Cluster
Cyclops
Equations
Indexes
Manganese
Program processors
Tensile stress
tensor contractions
Title Cyclops Tensor Framework: Reducing Communication and Eliminating Load Imbalance in Massively Parallel Contractions
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