Enhanced Distributed Computation for Machine Learning: Coded Strategies and Multidisciplinary Impact
This article explores methods to accelerate distributed computation, focusing on its application in machine learning. It discusses two primary concepts: coded multiplication and data shuffling, along with a non-linear core to Random Access Memory (RAM) approach, presenting new avenues for future res...
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| Main Author: | Tian Xiaolin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
|
| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/04/itmconf_iwadi2024_03026.pdf |
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