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FlashAttention
conceptOptimization Technique
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Overview
Developed byTri Dao
Founded2022
LicenseBSD-3-Clause
Open source✓ Open Source
Use caseMemory-efficient attention computation
Integrates with
PyTorchTransformers
Knowledge graph stats
Claims20
Avg confidence92%
Avg freshness100%
Last updatedUpdated 4 days ago
Trust distribution
100% unverified
Governance
Not assessed
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FlashAttention

concept

Memory-efficient attention algorithm that reduces memory usage and increases speed

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primary use case

ValueTrustConfidenceFreshnessSources
Memory-efficient attention computation○UnverifiedHighFresh1
Accelerating transformer training○UnverifiedHighFresh1

alternative to

ValueTrustConfidenceFreshnessSources
Standard attention mechanisms○UnverifiedHighFresh1
Standard attention implementation○UnverifiedHighFresh1

developed by

ValueTrustConfidenceFreshnessSources
Tri Dao○UnverifiedHighFresh1
Stefano Ermon○UnverifiedHighFresh1
Christopher Ré○UnverifiedHighFresh1
Daniel Y. Fu○UnverifiedHighFresh1
Atri Rudra○UnverifiedHighFresh1

supports model

ValueTrustConfidenceFreshnessSources
Transformer models○UnverifiedHighFresh1
BERT○UnverifiedModerateFresh1
GPT○UnverifiedModerateFresh1

open source

ValueTrustConfidenceFreshnessSources
true○UnverifiedHighFresh1

license type

ValueTrustConfidenceFreshnessSources
BSD-3-Clause○UnverifiedHighFresh1

requires

ValueTrustConfidenceFreshnessSources
PyTorch○UnverifiedHighFresh1
CUDA○UnverifiedModerateFresh1

founded year

ValueTrustConfidenceFreshnessSources
2022○UnverifiedHighFresh1

integrates with

ValueTrustConfidenceFreshnessSources
PyTorch○UnverifiedHighFresh1
Transformers○UnverifiedModerateFresh1

based on

ValueTrustConfidenceFreshnessSources
Tiling technique○UnverifiedHighFresh1

Alternatives & Similar Tools

Standard attention mechanisms
alternative to
Compare →
Standard attention implementation
alternative to
Compare →

Commonly Used With

PyTorchTransformers

Related entities

Claim count: 20Last updated: 4/6/2026Edit history