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Unity: joint algebraic and parallelization search for DNN training

Represented computation and communication in parallel computation graphs, generated small algebraic/parallel substitutions from operator specifications, checked them with an automated prover and searched their compositions hierarchically.

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Represented computation and communication in parallel computation graphs, generated small algebraic/parallel substitutions from operator specifications, checked them with an automated prover and searched their compositions hierarchically.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

Verification is relative to supplied operator axioms, not an independently replayed proof of arbitrary floating-point execution. Fingerprints generate candidates but do not prove equivalence. The finite generated basis and hierarchical search do not establish globally optimal training runtime. Extends TASO/FlexFlow rather than inventing all graph rewriting or parallelization.

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People and systems

Colin Unger; Zhihao Jia; Wei Wu; Sina Lin; Mandeep Baines; Carlos Efrain Quintero Narvaez; Vinay Ramakrishnaiah; Nirmal Prajapati; Pat McCormick; Jamaludin Mohd-Yusof; Xi Luo; Dheevatsa Mudigere; Jongsoo Park; Misha Smelyanskiy; Alex Aiken

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

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English catalogue narrative

Unity: joint algebraic and parallelization search for DNN training

Represented computation and communication in parallel computation graphs, generated small algebraic/parallel substitutions from operator specifications, checked them with an automated prover and searched their compositions hierarchically.

Scientific scope

Verification is relative to supplied operator axioms, not an independently replayed proof of arbitrary floating-point execution. Fingerprints generate candidates but do not prove equivalence. The finite generated basis and hierarchical search do not establish globally optimal training runtime. Extends TASO/FlexFlow rather than inventing all graph rewriting or parallelization.

Reading status

This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.

People and systems

Colin Unger; Zhihao Jia; Wei Wu; Sina Lin; Mandeep Baines; Carlos Efrain Quintero Narvaez; Vinay Ramakrishnaiah; Nirmal Prajapati; Pat McCormick; Jamaludin Mohd-Yusof; Xi Luo; Dheevatsa Mudigere; Jongsoo Park; Misha Smelyanskiy; Alex Aiken

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

Original sources