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Hogwild!: lock-free asynchronous stochastic updates for sparse objectives

Allowed concurrent sparse shared-memory stochastic updates without global locks, with convergence analysis for a specified asynchronous sampling model and empirical parallel implementations.

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Allowed concurrent sparse shared-memory stochastic updates without global locks, with convergence analysis for a specified asynchronous sampling model and empirical parallel implementations.

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

Scientific scope

Pinned 2011 v1 front orders Feng Niu / Benjamin Recht / Christopher Ré / Stephen J. Wright. Theory assumes convex separable terms, smooth strongly convex objective, bounded gradients/delay, atomic component additions and sparse overlap. Analyzed with-replacement single-coordinate model differs from practical without-replacement full-edge updates. Not convergence for arbitrary dense/nonconvex/asynchronous programs or hardware data-race safety.

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People and systems

Feng Niu; Benjamin Recht; Christopher Ré; Stephen J. Wright

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

Hogwild!: lock-free asynchronous stochastic updates for sparse objectives

Allowed concurrent sparse shared-memory stochastic updates without global locks, with convergence analysis for a specified asynchronous sampling model and empirical parallel implementations.

Scientific scope

Pinned 2011 v1 front orders Feng Niu / Benjamin Recht / Christopher Ré / Stephen J. Wright. Theory assumes convex separable terms, smooth strongly convex objective, bounded gradients/delay, atomic component additions and sparse overlap. Analyzed with-replacement single-coordinate model differs from practical without-replacement full-edge updates. Not convergence for arbitrary dense/nonconvex/asynchronous programs or hardware data-race safety.

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

Feng Niu; Benjamin Recht; Christopher Ré; Stephen J. Wright

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