Type I Howard Cascade Parallel Data Distribution
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Solution Overview
Problem
Current parallel processing systems face inefficiencies in data transmission due to the limitations of true broadcast methods, which result in data errors and performance degradation, and tree broadcast methods are not optimal for balancing computational element performance.
Innovation Solution
The use of a Type I Howard Cascade, which employs a mathematical forest of binomial or other function trees, allowing for safe and efficient data scattering and gathering operations by dynamically adjusting communication channels and processing power, thereby improving performance beyond industry standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If true broadcast is used for data transmission, then data can be transmitted to all computational elements simultaneously, but data transmission errors occur and reliability deteriorates
Solution Approach 1:
The patent segments the single true broadcast operation into multiple tree broadcast operations organized in a forest structure. Each tree in the forest handles a subset of computational elements, allowing data to be transmitted in smaller, more reliable units while maintaining overall system-wide distribution. This segmentation reduces the error probability in each individual transmission path.
Solution Approach 2:
The patent introduces intermediary computational elements that act as relay points in the tree broadcast structure. These intermediaries receive data from the root, verify its integrity, and then forward it to their respective subtrees. This intermediary layer provides error detection and correction capabilities that were absent in direct true broadcast.
2Reliability
If error correcting code is used in true broadcast, then data reliability improves, but transmission overhead increases and performance degrades
Solution Approach 1:
By segmenting the broadcast into multiple smaller tree operations, the patent reduces the amount of data that needs error correction in each individual transmission. The error correcting code is applied to smaller data units in each tree broadcast, reducing the overhead ratio compared to applying ECC to the entire dataset in a single true broadcast.
Solution Approach 2:
The patent applies error correction partially - only to the extent necessary in each tree broadcast operation rather than over-correcting the entire dataset at once. This partial application of error correction maintains reliability while minimizing the performance overhead associated with redundant data transmission.
3Reliability
If tree broadcast is used for data transmission, then data transmission reliability improves, but transmission time increases compared to true broadcast
Solution Approach 1:
The patent merges multiple tree broadcasts into a forest structure that operates in parallel. By combining several independent tree operations that can execute simultaneously, the system achieves reliability comparable to or better than single tree broadcast while reducing the total transmission time through parallel execution, approaching the speed of true broadcast.
Solution Approach 2:
The forest structure enables periodic data transmission waves through different trees in the forest. While one tree is transmitting, another can be preparing or receiving, creating a pipelined effect that reduces idle time and improves overall transmission efficiency compared to sequential tree operations.
4Reliability
If standard tree broadcast is used for scatter and gather exchanges, then safe data transmission is achieved, but computational element performance is not optimally balanced
Solution Approach 1:
The patent assigns different roles and data processing responsibilities to different computational elements based on their position in the forest structure. Some elements serve as roots, others as intermediaries, and others as leaf nodes, with each having optimized functions for their specific location. This local specialization balances the workload and utilizes the capabilities of each computational element more effectively.
Solution Approach 2:
The forest structure is dynamically configured to balance computational element performance. The system can adjust which computational elements serve as roots or intermediaries based on their current processing capabilities and workload, allowing flexible load balancing while maintaining the reliable tree broadcast mechanism throughout the system.
Data Source
AI summary
A method using for performing a scatter-type data distribution among a cluster of computational devices. A number of nodes (equal to a value Cg, the number of tree generator channels) are initially generated, each connected to an initial generator, to create respective initial root nodes of an initial tree structure. Data is transmitted from the initial generator to each of the initial root nodes. Cg root nodes, each connected to a respective new generator, are generated to create respective roots of Cg newly generated tree structures. Each of the tree structures is expanded by generating Ct (the number of communication channels per node in each tree structure) new nodes connected to each node generated in each previous step. Data is then transmitted to each of the new nodes from an immediately preceding one of the nodes, and from each new generator to an associated root node.