Reconfigurable Data Stream Processing Resources for Parallel Handling
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Solution Overview
Problem
Modern digital communication devices designed for real-time data stream processing often underutilize their hardware resources due to limitations in bandwidth allocation and network configuration, which restrict parallel processing to only one or two data streams, despite being capable of handling multiple streams.
Innovation Solution
A data stream processing device with a plurality of data providing units, processing units, and control circuitry that allows for flexible operation modes, enabling simultaneous processing of multiple data streams by reconfiguring and combining FIR filters and linear channel equalizers to form either independent or combined filters with longer tap lengths, optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If additional hardware resources are added to achieve flexibility in processing different data streams, then adaptability is improved, but device cost increases
Solution Approach 1:
The patent implements parallel processing engines that can be dynamically configured to handle different data stream processing tasks. The same hardware resources (multipliers, adders, arithmetic units) are reused across multiple processing engines through reconfiguration, allowing a single device to perform various filtering and processing operations on different data streams without requiring dedicated hardware for each function.
Solution Approach 2:
The patent employs reconfigurable processing engines that can dynamically change their configuration and operation mode based on the processing requirements. The system can adaptively allocate resources to handle varying numbers of data streams (from one to multiple streams) by reconfiguring the parallel processing engines, thereby maintaining flexibility without permanently over-provisioning hardware resources.
2Productivity
If parallel processing engines are added to process multiple data streams simultaneously, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent divides the processing system into multiple parallel processing engines, each capable of independently processing data streams. These engines are segmented into functional units (data providing units, processing units) that can be individually configured and allocated. This segmentation allows the system to scale processing capacity by activating specific numbers and combinations of engines based on workload requirements, rather than requiring a monolithic complex structure.
Solution Approach 2:
The patent combines multiple processing engines into a unified reconfigurable system where resources are shared and dynamically allocated. The data providing units and processing units from different engines can be merged and reassigned to handle different numbers of data streams simultaneously, allowing efficient resource utilization while maintaining parallel processing capability.
3Adaptability or versatility
If the device is configured for many parallel data streams, then adaptability is improved, but resource utilization deteriorates when limited to one or two streams
Solution Approach 1:
The patent implements dynamic resource allocation where the parallel processing engines can be actively configured based on the actual number of data streams being processed. When only one or two streams are present, the system dynamically deactivates or reconfigures excess engine resources, preventing waste. The same hardware infrastructure supports both single-stream and multi-stream operations by adaptively adjusting the active processing capacity.
Solution Approach 2:
The patent changes operational parameters (number of active processing engines, data flow configuration) based on workload conditions. The system monitors and adjusts its configuration to match the actual processing requirements, transitioning between different operational modes (single stream, dual stream, multi-stream) by reconfiguring the parallel engines, thereby optimizing resource utilization across varying load conditions.
Data Source
AI summary
A data stream processing device includes a plurality of data providing units, a plurality of processing units, and control circuitry. The data providing units are configured to output data values received via a plurality of data inputs, respectively. The processing units are configured to generate data outputs based on the data values, respectively. The control circuitry includes a mode selection input and is configured to simultaneously provide data values of different data streams to the data inputs of the data providing units, respectively, in response to the mode selection input receiving a signal indicating a first mode, and simultaneously provide a plurality of successive groups of data values of one of the data streams to the data inputs of the data providing units, respectively, in response to the mode selection input not receiving the signal indicating the first mode.