DPU Status Tracking via Broadcast Messages for Self-Restart
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Centralized computing architectures face data processing limitations due to slow read and write speeds of traditional storage devices, leading to bottlenecks in data retrieval and processing.
Innovation Solution
A computing system comprising multiple data processing units (DPUs) each coupled to non-volatile memory, where one DPU executes persistent processes, generates broadcast messages to monitor status, and handles failures by transmitting restart commands and status inquiries to maintain DPU status tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If centralized computing architecture with traditional storage devices is used, then data processing can be performed, but read and write speeds are slow causing bottlenecks
Solution Approach 1:
The system divides the centralized computing architecture into multiple distributed Data Processing Units (DPUs), each capable of independent data processing. This segmentation eliminates the single-point bottleneck by distributing data processing tasks across multiple units, thereby improving overall data read and write speeds without creating centralized transfer bottlenecks.
Solution Approach 2:
The patent transitions from traditional hierarchical storage architecture to a multi-dimensional DPU architecture where data processing occurs at the edge of storage devices. Each DPU is directly coupled to non-volatile memory, creating a parallel processing dimension that eliminates the sequential data transfer bottleneck of centralized architectures.
2Productivity
If multiple DPUs are deployed for parallel processing, then data processing speed improves, but system reliability decreases due to potential failures
Solution Approach 1:
The system implements a feedback mechanism where DPUs periodically broadcast status messages to indicate their operational state. The first DPU monitors these broadcast messages and maintains a status table tracking the availability of other DPUs. This feedback loop enables real-time detection of DPU failures and triggers automatic restart commands, ensuring system reliability while maintaining parallel processing productivity.
Solution Approach 2:
When a DPU failure is detected through the absence of broadcast messages, the system automatically initiates restart commands to affected DPUs without requiring external intervention. This self-service mechanism ensures that productivity is rapidly restored after failures, maintaining high system availability while preserving the benefits of parallel processing.
3Reliability
If DPU failures occur, then system productivity decreases, but manual intervention increases device complexity
Solution Approach 1:
The system implements automatic failure detection and recovery mechanisms where the first DPU monitors broadcast messages from other DPUs and automatically sends restart commands when failures are detected. This self-service approach eliminates the need for manual failure management intervention, reducing operational complexity while maintaining high reliability through automated status monitoring and recovery procedures.
Data Source
AI summary
Systems and methods are disclosed for maintaining a status of a respective data processing unit (DPU) of a plurality of data processing units, each coupled to non-volatile memory. In some embodiments a first DPU is configured to execute one or more persistent processes, wherein the one or more processes persist in the non-volatile memory over power cycles, generate a first broadcast message upon completion of a first persistent process, transmit the first broadcast message to a set of DPUs associated with monitoring the first DPU, receive a second broadcast message from a second DPU of the set of DPUs and assign a value indicating an active status for the second DPU in a status table to track the status of each DPU of the set of DPUs.