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[2211.05102] Efficiently Scaling Transformer Inference - arXiv

arxiv.org › cs
Nov 9, 2022 · Abstract:We study the problem of efficient generative inference for Transformer models, in one of its most challenging settings: large deep ...

Scholarly articles for Efficiently Scaling Transformer Inference.

scholar.google.com › citations
Efficiently scaling transformer inference
Pope · Cited by 243
… -inference: enabling efficient inference of transformer …
Aminabadi · Cited by 234
Easy and efficient transformer: Scalable inference …
Li · Cited by 12

[PDF] Efficiently Scaling Transformer Inference - MLSys Proceedings

proceedings.mlsys.org › paper › file
We study the problem of efficient generative inference for Transformer models, in one of its most challenging settings: large deep models, with tight latency ...

[PDF] Efficiently Scaling Transformer Inference - Semantic Scholar

www.semanticscholar.org › paper › Effic...
A simple analytical model for inference efficiency is developed to select the best multi-dimensional partitioning techniques optimized for TPU v4 slices ...

[PDF] Efficiently Scaling Transformer Inference - Minjia Zhang

minjiazhang.github.io › courses › E...
Feb 27, 2024 · How to scale to large batch sizes and sequences? Efficiently. • How to ensure low chip cost and high utilization? Page 3. Overview.

[PDF] CS-723 EFFICIENTLY SCALING TRANSFORMER INFERENCE

parsa.epfl.ch › ml_inf_at_scale
Iterative output generation. ▫ Each request runs a different number of iterations. ▫ Wasted computation for early finishing requests.

Efficient Inference of Extremely Large Transformer Models - YouTube

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Video for Efficiently Scaling Transformer Inference.
Duration: 28:16
Posted: Aug 16, 2023

MLSys Poster Efficiently Scaling Transformer Inference

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The MLSys Logo above may be used on presentations. Right-click and choose download. It is a vector graphic and may be used at any scale.

Large Transformer Model Inference Optimization - Lil'Log

lilianweng.github.io › posts › 2023-01-1...
Jan 10, 2023 · In this post, we will look into several approaches for making transformer inference more efficient. ... “Efficiently Scaling Transformer Inference ...
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Efficiently Scaling Transformer Inference · Issue #348 - GitHub

github.com › sys_reading › issues
Feb 28, 2024 · partialsum-$x$ means a given tensor has been contracted (summed) locally on each chip (over axis x not represented in the shape), but still ...
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Efficiently Scaling Transformer Inference - BibBase

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