MAETA: Identifying and Mitigating the Memory Bottleneck in Scientific ML Models through Execution Trace Analysis

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-17
DOI
https://doi.org/10.5281/zenodo.15238363
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

MAETA: Identifying and Mitigating the Memory Bottleneck in Scientific ML Models through Execution Trace Analysis

Zenodo (CERN European Organization for Nuclear Research)
Scientific Computing and Data Management
article

MAETA: Identifying and Mitigating the Memory Bottleneck in Scientific ML Models through Execution Trace Analysis

article en

Abstract

No abstract available for this paper.
Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Scientific Computing and Data Management
DOIOpen Access PDFOpenAlex
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MAETA: Identifying and Mitigating the Memory Bottleneck in Scientific ML Models through Execution Trace Analysis · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS