Sep 24, 2017 · Experiments show that SLAQ achieves an average quality improvement of up to 73% and an average delay reduction of up to 44% on a large set of ML ...
Feb 13, 2018 · We describe SLAQ, a cluster scheduling system for approximate ML training jobs that aims to maximize the overall job quality. When allocating ...
Sep 24, 2017 · SLAQ can use its quality- driven scheduling for many of the ML algorithms avail- able in MLlib [5], Spark's machine learning package. In fact, ...
We present SLAQ, a cluster scheduling system for ML training ... SLAQ is a quality-driven scheduling system designed for large- ... Quality-Driven Scheduling for ...
SLAQ is described, a cluster scheduling system for approximate ML training jobs that aims to maximize the overall job quality and leverages the iterative ...
[PDF] SLAQ: Quality-Driven Scheduling for Distributed Machine Learning
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SLAQ: Quality-Driven Scheduling for. Distributed Machine Learning. Haoyu Zhang ... SLAQ: quality-aware scheduling. • Intuition: in the context of approximate ML ...
We describe SLAQ, a cluster scheduling system for approximate ML training jobs that aims to maximize the overall job quality. When allocating cluster resources, ...
Feb 13, 2018 · 1 Background and Motivation. Machine learning (ML) is an increasingly important tool for large-scale data analytics.
Jul 27, 2023 · This paper presents SLAQ, which is a cluster scheduling framework that hosts multi-tenant approximate ML training jobs running on shared ...
Feb 13, 2018 · We describe SLAQ, a cluster scheduling system for approximate ML training jobs that aims to maximize the overall job quality. When allocating ...