What work is related to research data management and LLM?
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Research data management (RDM) and Limited Local Memory (LLM) are two related areas of work. RDM involves activities and strategies for the storage, organization, and description of research data and materials, aiming to ensure their usability and facilitate collaboration . LLM architecture is a power-efficient, scalable memory multi-core architecture that utilizes scratch-pad like local memory controlled by software. Stack data management and heap data management are important problems in LLM architecture. Previous work has proposed schemes for managing stack data and heap data in LLM processors. These schemes aim to improve the management of stack and heap data, increase applicability, and reduce memory footprint. Experimental results on benchmark applications demonstrate the effectiveness of these schemes . Therefore, both RDM and LLM research focus on efficient and effective management of data and memory in different contexts.
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| Papers (4) | Insight |
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11 Sep 2011 26 Citations | The paper mentions that techniques have been developed to manage code, global variables, stack, and heap data in LLM architecture. However, it states that these techniques are not directly applicable to LLM architecture due to differences in memory architecture. |
| The provided paper does not mention any work related to research data management and LLM. The paper is about the findings and results of The University of Nottingham 2012 Research Data Management survey. | |
24 Oct 2010 | The provided paper does not discuss research data management related to LLM processors. |
| The paper does not mention any specific work related to research data management and LLM. |
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