Data Flow Manager for Multi-Core Processor Efficiency
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Solution Overview
Problem
Current digital signal processing systems for wireless communications, particularly in 5G and IoT devices, face challenges in achieving fast and efficient data flows due to hardware implementation specificity and high power consumption, especially in multi-core processors where memory access patterns are complex and inefficient.
Innovation Solution
A data flow manager is implemented to generate configuration packets that map processing elements to memory units and identify optimal data flows, allowing for concurrent processing and reduced power usage by utilizing shared memory spaces and selecting available processing elements based on their proximity and availability, thereby facilitating faster and more efficient data access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If customized signal processing methods are implemented for each hardware platform (ASIC, DSP, FPGA), then processing functionality is optimized for specific applications, but device complexity and implementation difficulty increase
Solution Approach 1:
The patent implements a universal processor architecture that can perform multiple signal processing functions through software configuration rather than hardware customization. The processor includes configurable components such as a window generator, weighting coefficient generator, and accumulator that can be programmed to perform different signal processing operations (e.g., RAKE combining, diversity combining) without requiring separate hardware implementations for each function.
Solution Approach 2:
The patent employs dynamic configuration of processing elements through control signals. The processor can dynamically adjust the operation of its components (e.g., enabling/disabling specific processing paths, configuring accumulation modes) based on the required signal processing task, allowing the same hardware to adapt to different processing requirements without physical reconfiguration.
2Productivity
If multiple separate hardware components are used to implement different portions of signal processing, then each component can be optimized for its specific function, but overall system complexity and integration difficulty increase
Solution Approach 1:
The patent merges multiple signal processing functions into a single integrated processor. The processor combines window generation, weighting coefficient application, accumulation, and combining operations in one unified hardware platform, eliminating the need for separate hardware components for each function and reducing integration complexity while maintaining processing efficiency.
3Speed
If conventional memory access patterns are used in multi-core processors, then memory structure is simple, but data access speed and processing efficiency decrease
Solution Approach 1:
The patent implements preliminary organization of data in memory with specific patterns that optimize access efficiency. Data is pre-arranged in memory locations that correspond to the processing requirements, allowing the processor to access required data elements in an optimized sequence without complex runtime memory management, thus improving access speed while controlling complexity.
Data Source
AI summary
Methods, apparatuses, and systems for implementing data flows in a processor are described herein. A data flow manager may be configured to generate a configuration packet for a compute operation based on status information regarding multiple processing elements of the processor. Accordingly, multiple processing elements of a processor may concurrently process data flows based on the configuration packet. For example, the multiple processing elements may implement a mapping of processing elements to memory, while also implementing identified paths, through the processor, for the data flows. After executing the compute operation at certain processing elements of the processor, the processing results may be provided. In speech signal processing operations, the processing results may be compared to phonemes to identify such components of human speech in the processing results. Once dynamically identified, the processing elements may continue comparing additional components of human speech to facilitate processing of an audio recording, for example.