Towards an Optimizer for MLbase (Hướng tới một bộ tối ưu cho MLbase) - Ameet Talwalkar

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자료 내용

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Towards an OpBmizer for MLbase Ameet Talwalkar Collaborators: Evan Sparks, Michael Franklin, Michael I. Jordan, Tim Kraska UC Berkeley

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Problem: Scalable implementa.ons Me difficult for ML Developers…ML Contract + Code The Language of Technical Computing ML MATLAB® is a high-level language and interactive environment for numerical com- Key Features putation, visualization, and programming. Using MATLAB, you can analyze data, t )JHIMFWFMMBOHVBHFGPSOVNFSJDBM t #VJMUJOHSBQIJDTGPSWJTVBMJ[JOHEBUB develop algorithms, and create models and DPNQVUBUJPO WJTVBMJ[BUJPO BOEBQ- BOEUPPMTGPSDSFBUJOHDVTUPNQMPUT applications. The language, tools, and built- QMJDBUJPOEFWFMPQNFOU t %FWFMPQNFOUUPPMTGPSJNQSPWJOH in math functions enable you to explore t *OUFSBDUJWFFOWJSPONFOUGPSJUFSBUJWF DPEFRVBMJUZBOENBJOUBJOBCJMJUZ multiple approaches and reach a solution FYQMPSBUJPO EFTJHO BOEQSPCMFN BOENBYJNJ[JOHQFSGPSNBODF faster than with spreadsheets or traditional TPMWJOH t 5PPMTGPSCVJMEJOHBQQMJDBUJPOTXJUI programming languages, such as C/C++ or t .BUIFNBUJDBMGVODUJPOTGPSMJOFBS DVTUPNHSBQIJDBMJOUFSGBDFT Java™.You can use MATLAB for a range of applications, including signal processing and - BMHFCSBGJMUFSJOHJOUFHSBUJPOPQUJNJ[BUJPOTUBUJTUJDTBOETPMWJOH'PVSJFSOVNFSJDBMPSEJOBSZBOBMZTJT  t 'VODUJPOTCBTFEQMJDBUJPOTBMHPSJUINTGPSBOEJOUFHSBUJOHMBOHVBHFTXJUIFYUFSOBM."5-"#TVDIBTBQ$-  S EJGGFSFOUJBMFRVBUJPOT communications, image and video process- +BWB /&5 BOE.JDSPTPGU®&YDFM® ing, control systems, test and measurement, computational finance, and computational biology. More than a million engineers and scientists in industry and academia use MATLAB, the language of technical computing. MATLAB Overview 2:04 Analyzing and visualizing data using the MATLAB desktop. The MATLAB environment also lets you write programs and develop algorithms and applications.

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Problem: Scalable implementa.ons Me difficult for ML Developers…ML Contract + Code ML S CHALLENGE: Can we simplify distributed ML development?

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Problem: ML is difficult for End Users… Too many Too many algorithms… knobs… Too many ways to preprocess…

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Problem: ML is difficult for End Users… Too many Too many algorithms… knobs… Too many ways to preprocess… Difficult to debug…

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Problem: ML is difficult for End Users… Too many Too many algorithms… knobs… Too many ways to preprocess… Difficult to debug… Doesn’t scale…

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Problem: ML is difficult for End Users… Too many Too many algorithms… knobs… Too many ways to preprocess… Difficult to debug… CHALLENGE: Can we automate ML pipeline construcBonDoesn’t scale…?

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MLbase MLbase aims to simplify development and deployment of ML pipelines Apache Spark Spark: Cluster compuBng system designed for iteraBve computaBon 4

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MLbase MLbase aims to simplify development and deployment of ML MLlib pipelines Apache Spark Spark: Cluster compuBng system designed for iteraBve computaBon MLlib: Spark’s core ML library 4

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MLbase MLbase aims to simplify development MLI and deployment of ML MLlib pipelines Apache Spark Spark: Cluster compuBng system designed for iteraBve computaBon MLlib: Spark’s core ML library MLI: API to simplify ML development 4

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MLbase MLOpt MLbase aims to simplify development MLI and deployment of ML MLlib pipelines Apache Spark Spark: Cluster compuBng system designed for iteraBve computaBon MLlib: Spark’s core ML library MLI: API to simplify ML development MLOpt: DeclaraBve layer that aims to automate ML pipeline construcBon via search over feature extractors and models 4

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MLbase MLOpt MLbase aims to simplify development MLI and deployment of ML MLlib MLOpt and MLI arepipelines Apache Spark Spark: Cluster compuBng system designed for iteraBve computaBonexperimental testbeds MLlib: Spark’s core ML library MLI: API to simplify ML development MLOpt: DeclaraBve layer that aims to automate ML pipeline construcBon via search over feature extractors and models 4

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MLlib + Scalable and fast + Simple development environment + Part of Spark’s robust ecosystem MLlib GraphX Spark SparkSQL (machine (graph) Streaming learning) Apache Spark 6

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