Control Word Templates for 2D Compute Element Task Execution
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Solution Overview
Problem
Traditional processing architectures, such as Von Neumann configurations, are poorly matched to complex processing tasks and inflexible, leading to inefficiencies in data handling and computation, particularly in large-scale data processing operations.
Innovation Solution
Utilizing a two-dimensional array of compute elements controlled by customized control word templates, generated by a compiler, which include associative memories and topological sets to enable efficient execution of tasks and subtasks, reducing latency and enabling autonomous operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional Von Neumann processing architecture is used, then device simplicity is maintained, but processing efficiency deteriorates due to poor matching with complex processing tasks and inflexibility in data handling
Solution Approach 1:
The processing architecture is segmented into multiple compute elements arranged in a two-dimensional array, where each compute element can be independently controlled. This segmentation allows parallel processing of complex tasks while maintaining manageable complexity through modular organization.
Solution Approach 2:
The architecture transitions from traditional single-dimensional sequential processing to a two-dimensional array of compute elements. This dimensional change enables simultaneous multi-threaded execution and provides flexible data handling pathways, dramatically improving processing efficiency for complex tasks.
2Productivity
If customized control word templates are used to enable fine-grained control, then processing efficiency improves through autonomous operation, but device complexity increases due to template generation and management requirements
Solution Approach 1:
Control word templates are pre-generated by a compiler before execution. These templates contain pre-configured instructions for specific processing operations, allowing compute elements to execute tasks autonomously without runtime interpretation. This preliminary preparation enables fast execution while centralizing the complexity in the compilation phase.
Solution Approach 2:
Each compute element is equipped with an associative memory that stores and executes control word templates autonomously. The compute elements self-configure and self-execute based on the stored templates, eliminating the need for complex runtime control mechanisms and enabling independent operation.
3Loss of time
If associative memories are integrated in each compute element, then load latency is eliminated enabling autonomous operation, but device complexity increases due to memory integration requirements
Solution Approach 1:
An associative memory is nested within each compute element, creating a hierarchical memory structure. This nesting allows each compute element to have immediate access to its control word template without external memory access, eliminating load latency while organizing memory resources efficiently across the array.
Data Source
AI summary
Techniques for task processing based on compute element processing using control word templates are disclosed. One or more control word templates are generated for use in a two-dimensional array of compute elements. Each compute element within the array is known to a compiler and is coupled to its neighboring compute elements within the array of compute elements. Each control word template designates a topological set of compute elements from the array of compute elements. The one or more control word templates are customized with a specific set of compute element operations. The one or more control word templates that were customized are stored. The specific set of compute element operations is executed on the topological set of compute elements. The one or more control word templates that were stored are reused. The one or more control word templates that were stored are modified and executed using compute elements.