Hierarchical Multi-Core Processor for High-Speed Data Processing
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Solution Overview
Problem
Existing multi-core processor designs struggle to balance speed, adaptability, and flexibility, making them impractical for real-time high-speed and low-power applications, as they often require specific architecture and software optimization for each purpose, limiting their versatility and ability to adapt to new requirements and applications.
Innovation Solution
A multi-core processor with a tree-like structure featuring hierarchical computing planes, each containing compute, interconnect, and storage elements, allowing for hierarchical decomposition and mapping of application functions, and a programming method that optimizes load balancing and execution throughput by allocating resources and configuring interconnects based on data flow and control mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a single general purpose processor is used, then adaptability and flexibility are maintained, but processing speed cannot meet real-time computing requirements
Solution Approach 1:
The processor is divided into multiple independent computing cores (first core and second core) that can operate in parallel. Each core can execute different instructions simultaneously, enabling the system to achieve higher processing speeds while maintaining the ability to handle diverse applications through flexible task distribution across cores.
Solution Approach 2:
The patent introduces a hierarchical memory structure with multiple levels (first level memory, second level memory) and multiple memory controllers. This adds a dimensional aspect to data access by enabling parallel memory operations at different hierarchical levels, thereby increasing processing speed without sacrificing adaptability.
2Speed
If specialized cores are used to achieve high speed, then processing speed is improved, but flexibility and adaptability are reduced
Solution Approach 1:
The computing cores are designed with universal instruction set architecture that allows them to execute various types of instructions for different applications. The cores can be configured to handle both specialized high-speed computations and general-purpose tasks, achieving multi-functionality that balances speed and flexibility.
Solution Approach 2:
The processor includes dynamic task scheduling mechanisms that can allocate different computing cores to different applications based on real-time requirements. This dynamic configuration allows the system to optimize performance for specific workloads while maintaining the ability to adapt to changing application needs.
3Productivity
If architecture is designed specifically for intended purpose, then optimal device speed is achieved, but design costs cannot be amortized over multiple applications
Solution Approach 1:
The processor architecture is segmented into modular components including multiple independent cores, hierarchical memory subsystems, and separate memory controllers. This modularity allows the design to be optimized for high-speed performance in specific domains while maintaining the flexibility to reconfigure and amortize costs across multiple applications through software programming.
Solution Approach 2:
The system enables parameter changes in memory access patterns and data processing configurations through software control. By dynamically adjusting memory hierarchy utilization and data processing parameters, the processor can optimize performance for different applications without requiring hardware redesign, thereby amortizing design costs.
4Productivity
If hierarchical computing planes are implemented, then resource allocation and load balancing are optimized, but device complexity increases
Solution Approach 1:
The computing architecture is segmented into hierarchical levels with multiple computing planes, each handling specific computational tasks. This segmentation enables optimized resource allocation and load balancing by distributing work across different hierarchical levels, improving execution throughput while managing complexity through structured organization.
Solution Approach 2:
Memory controllers act as intermediary components between the hierarchical memory levels and the computing cores. These intermediaries manage data transfer and coordination between different hierarchical planes, enabling optimized resource allocation and load balancing while abstracting the complexity of the hierarchical structure from the computing cores.
Data Source
AI summary
A multi-core processor includes a tree-like structure having a plurality of computing cores arranged in hierarchical levels, the cores all having the same logical architecture. Each core can include computing, interconnecting, and/or storage elements. The functionality of an individual element can be supplied by an entire core in a lower level. A method for programming the processor includes hierarchically decomposing an application into interconnected sub-functions, mapping the sub-functions onto groups of cores at appropriate levels of the processor, and interconnecting the mapped sub-functions so as to hierarchically compose the complete application. Sub-functions can be sequential, concurrent, and/or pipelined. Interconnections can be static or dynamically switchable under program control. Interconnect elements can also be used to implement flow control as needed in pipelined operations to maintain data coherency. The decomposing and mapping process can be iterated on sub-functions so as to optimize load balancing, software performance, and hardware efficiency.