Memory Sled Filtering for Data Center Query Efficiency
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Solution Overview
Problem
Conventional data centers face inefficiencies and performance drag due to the need to move large volumes of data for composite queries, as they often transfer entire data sets across multiple nodes, which is inefficient and resource-intensive.
Innovation Solution
Implementing memory sleds within data centers that can filter data sets and provide filtered results to compute sleds, utilizing memory filtering logic to execute queries and reduce data transfer by only transmitting the necessary data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If entire data sets are transferred across multiple nodes for composite queries, then query results can be obtained, but data transmission volume increases and system efficiency decreases
Solution Approach 1:
The patent applies preliminary action by executing filter operations at the memory sled before data transfer. The memory filtering logic evaluates predicates and filters the data set in advance, so that only the necessary filtered results are transmitted to compute sleds. This prevents the need to transfer entire data sets, thereby reducing data transmission volume while maintaining query processing efficiency.
2Quantity of substance
If filter operations are executed at memory sleds, then data transmission is reduced, but additional memory filtering logic is required
Solution Approach 1:
The patent applies universality by designing memory sleds with multi-functionality. The memory sleds not only store data but also execute filter operations through integrated memory filtering logic. This allows the same hardware component to perform both storage and filtering functions, reducing the need for separate filtering infrastructure and minimizing the increase in device complexity.
Solution Approach 2:
The patent applies self-service by enabling memory sleds to autonomously perform filter operations on their stored data sets. The memory filtering logic resides within the memory sled itself, allowing it to independently evaluate predicates and filter data without requiring external processing. This self-service capability reduces data transmission needs while keeping the added complexity localized within existing memory sled components.
Data Source
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AI summary
Examples may include a data center in which memory sleds are provided with logic to filter data stored on the memory sled responsive to filtering requests from a compute sled. Memory sleds may include memory filtering logic arranged to receive filtering requests, filter data stored on the memory sled, and provide filtering results to the requesting entity. Additionally, a data center is provided in which fabric interconnect protocols in which sleds in the data center communicate is provided with filtering instructions such that compute sleds can request filtering on memory sleds.