Dynamic Reduction Engine Allocation in Switch Multicast Trees
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Solution Overview
Problem
Existing network architectures face challenges in accommodating large numbers of computing endpoints due to inefficiencies in managing and allocating resources, particularly when errors occur, leading to high setup and teardown costs and prolonged latency in processing data.
Innovation Solution
A reduction engine is dynamically allocated within a network switch, utilizing a multicast session to arm engines along a multicast tree, allowing for efficient, scalable, and error-tolerant reduction operations without software intervention, reducing latency by an order of magnitude.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional network architectures are used to accommodate large numbers of computing endpoints, then network coverage is expanded, but resource management inefficiency increases and setup/teardown costs increase
Solution Approach 1:
The reduction engine performs self-arming along the multicast tree without requiring software intervention. When a multicast frame is received, the engine automatically configures itself to perform reduction operations, eliminating the need for manual setup and teardown commands from software controllers.
Solution Approach 2:
The system pre-configures reduction engines along the multicast tree in advance. When data needs to be processed, the engines are already positioned and ready to perform reduction operations immediately, eliminating setup time and enabling faster data processing.
2Quantity of substance
If conventional resource allocation methods are used, then network resources are provided, but setup and teardown times are prolonged
Solution Approach 1:
The reduction engine automatically configures itself upon receiving a multicast frame without requiring software intervention. This self-arming mechanism eliminates manual setup and teardown operations, significantly reducing the time required to allocate and release network resources.
Solution Approach 2:
The reduction engine maintains continuous operation along the multicast tree once armed. It continuously processes reduction operations on incoming data frames without interruption, eliminating idle setup and teardown phases and enabling uninterrupted data processing.
3Ease of operation
If software-based resource management is used, then resource allocation is controlled, but latency in processing data increases
Solution Approach 1:
The reduction engine performs self-configuration and self-management without requiring software intervention. Once armed by a multicast frame, the engine autonomously processes reduction operations on data frames, eliminating software processing delays and significantly improving data processing speed.
Solution Approach 2:
The patent replaces software-based resource management with a hardware-based reduction engine that operates independently. This substitution eliminates software intervention in the data processing path, reducing latency and improving processing speed while maintaining ease of operation through the multicast framing mechanism.
Data Source
AI summary
A switch equipped with a reduction engine capable of being dynamically allocated in a network is provided. During operation, the reduction engine can be dynamically armed based on a multicast frame. As a result, the network can facilitate an efficient and scalable environment for high performance computing.