Laminar 2.0: Serverless Stream Processing with Enhanced Code Search and Recommendations

Daniel Rotchford; Samuel Evans; Rosa Filgueira

Laminar 2.0: Serverless Stream Processing with Enhanced Code Search and Recommendations

Daniel Rotchford, Samuel Evans, Rosa Filgueira^*

^*Corresponding author for this work

EPCC

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper presents Laminar 2.0, an enhanced serverless framework for running dispel4py streaming work- flows. Building on Laminar 1.0, this version introduces im- proved dependency management, client-server functionality, and advanced deep learning models for semantic search. Key inno- vations include a structural code-to-code search using simpli- fied parse syntax trees (SPTs) for detecting similar Processing Elements (PEs) or workflows, even from incomplete code. Ad- ditionally, Laminar 2.0 optimizes text-to-code search through better preprocessing of PEs. Our evaluation shows significant performance improvements over the previous version.

Original language	English
Pages	1
Number of pages	8
Publication status	Published - Nov 2024
Event	19th Workshop on Workflows in Support of Large-Scale Science - Atlanta, GA, USA - Co-located with SC24, Atlanta, United States Duration: 18 Nov 2024 → 18 Nov 2024 https://works-workshop.org

Workshop

Workshop	19th Workshop on Workflows in Support of Large-Scale Science
Abbreviated title	WORKS 2024
Country/Territory	United States
City	Atlanta
Period	18/11/24 → 18/11/24
Internet address	https://works-workshop.org

Keywords / Materials (for Non-textual outputs)

Serverless computing
Streaming Workflows
Semantic Code Search
Laminar
dispel4py

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Laminar-WORSK24Submitted manuscript, 5.56 MBLicence: Creative Commons: Attribution Non-Commercial (CC-BY-NC)

Cite this

@conference{1328bf85784e49cb8e7b01b08e3c7e5a,

title = "Laminar 2.0: Serverless Stream Processing with Enhanced Code Search and Recommendations",

abstract = "This paper presents Laminar 2.0, an enhanced serverless framework for running dispel4py streaming work- flows. Building on Laminar 1.0, this version introduces im- proved dependency management, client-server functionality, and advanced deep learning models for semantic search. Key inno- vations include a structural code-to-code search using simpli- fied parse syntax trees (SPTs) for detecting similar Processing Elements (PEs) or workflows, even from incomplete code. Ad- ditionally, Laminar 2.0 optimizes text-to-code search through better preprocessing of PEs. Our evaluation shows significant performance improvements over the previous version.",

keywords = "Serverless computing, Streaming Workflows, Semantic Code Search, Laminar, dispel4py",

author = "Daniel Rotchford and Samuel Evans and Rosa Filgueira",

year = "2024",

month = nov,

language = "English",

pages = "1",

note = "19th Workshop on Workflows in Support of Large-Scale Science, WORKS 2024 ; Conference date: 18-11-2024 Through 18-11-2024",

url = "https://works-workshop.org",

}

TY - CONF

T1 - Laminar 2.0: Serverless Stream Processing with Enhanced Code Search and Recommendations

AU - Rotchford, Daniel

AU - Evans, Samuel

AU - Filgueira, Rosa

PY - 2024/11

Y1 - 2024/11

N2 - This paper presents Laminar 2.0, an enhanced serverless framework for running dispel4py streaming work- flows. Building on Laminar 1.0, this version introduces im- proved dependency management, client-server functionality, and advanced deep learning models for semantic search. Key inno- vations include a structural code-to-code search using simpli- fied parse syntax trees (SPTs) for detecting similar Processing Elements (PEs) or workflows, even from incomplete code. Ad- ditionally, Laminar 2.0 optimizes text-to-code search through better preprocessing of PEs. Our evaluation shows significant performance improvements over the previous version.

AB - This paper presents Laminar 2.0, an enhanced serverless framework for running dispel4py streaming work- flows. Building on Laminar 1.0, this version introduces im- proved dependency management, client-server functionality, and advanced deep learning models for semantic search. Key inno- vations include a structural code-to-code search using simpli- fied parse syntax trees (SPTs) for detecting similar Processing Elements (PEs) or workflows, even from incomplete code. Ad- ditionally, Laminar 2.0 optimizes text-to-code search through better preprocessing of PEs. Our evaluation shows significant performance improvements over the previous version.

KW - Serverless computing

KW - Streaming Workflows

KW - Semantic Code Search

KW - Laminar

KW - dispel4py

UR - https://conferences.computer.org/sc-wpub/pdfs/SC-W2024-6oZmigAQfgJ1GhPL0yE3pS/555400c088/555400c088.pdf

M3 - Paper

SP - 1

T2 - 19th Workshop on Workflows in Support of Large-Scale Science

Y2 - 18 November 2024 through 18 November 2024

ER -

Laminar 2.0: Serverless Stream Processing with Enhanced Code Search and Recommendations

Abstract

Workshop

Keywords / Materials (for Non-textual outputs)

Access to Document

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