Runtime Algorithm Scheduling by Data Characteristics and SLOs
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Solution Overview
Problem
Existing data processing techniques struggle to dynamically and adaptively select the most efficient implementation of algorithms based on data characteristics, leading to suboptimal performance and resource utilization.
Innovation Solution
Implement programmable circuitry that analyzes data objects on-the-fly, generates metadata, and uses load balancer circuitry to dynamically select the optimal algorithm implementation based on service level objectives and available resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single algorithm implementation is used for all data types, then device complexity is reduced, but processing efficiency and performance deteriorate
Solution Approach 1:
The system dynamically selects algorithm implementations based on runtime data characteristics rather than using a static single implementation. The load balancer circuitry monitors data properties and adjusts algorithm selection in real-time, transforming the system from static to dynamic to optimize processing efficiency for different data types.
Solution Approach 2:
The system changes the parameter of algorithm selection based on data characteristics. Different algorithm implementations are chosen depending on the specific parameters of the input data (e.g., data format, size, type), allowing the system to adapt its processing approach to match the data being handled.
2Adaptability or versatility
If data analysis is performed on-the-fly before processing, then algorithm selection accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary analysis of data characteristics before the main processing algorithm is applied. By analyzing data properties upfront and selecting the appropriate algorithm implementation in advance, the system prepares the optimal processing path without adding significant overhead to the overall processing time.
Solution Approach 2:
The load balancer circuitry acts as an intermediary between data input and algorithm execution. It receives data, analyzes characteristics, selects the appropriate algorithm implementation, and routes it to the processing unit, thereby decoupling the analysis time from the main processing time and reducing the impact on overall throughput.
3Productivity
If multiple algorithm implementations are maintained for different data types, then processing efficiency is improved, but resource utilization deteriorates
Solution Approach 1:
The system maintains multiple algorithm implementations but uses a universal load balancer circuitry to manage them all. This load balancer serves as a multi-functional component that can route different data types to appropriate algorithms, allowing the system to have specialized processing capabilities while using a single resource management interface.
Solution Approach 2:
The system implements self-service through automatic algorithm selection based on data characteristics. The load balancer autonomously analyzes incoming data and selects the most efficient algorithm implementation without requiring external intervention or manual configuration, thereby optimizing resource utilization while maintaining multiple algorithm options.
Data Source
AI summary
Systems, apparatus, articles of manufacture, and methods are disclosed to schedule algorithms based on characteristics of data. An example compute device includes circuitry to determine at least one characteristic of a data object to be processed and adjust metadata associated with the data object to indicate that the data object has the at least one characteristic. Additionally, the example compute device includes machine-readable instructions and at least one programmable circuit to be programmed by the machine-readable instructions to select at least one of two or more programmable circuits to process the data object based on (a) at least one service level objective associated with the data object, (b) the metadata associated with the data object, and (c) telemetry data associated with the two or more programmable circuits.