Programmable Accumulator Routing for Conflict-Free GBDT Histograms
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Solution Overview
Problem
In machine learning algorithms like Gradient Boosting Decision Tree (GBDT), the process of node splitting is time-consuming, and existing hardware acceleration methods using dedicated accumulators are limited by resource constraints and precision issues, leading to data conflicts and reduced efficiency.
Innovation Solution
A programmable device with multiple accumulator circuits and a multiplexer that dynamically assigns feature values to accumulator circuits, reducing data conflicts by avoiding reassignment of accumulator circuits to the same feature, thereby improving pipeline efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated accumulators are employed to perform accumulation operation, then data conflicts are avoided, but resource limitations and precision constraints prevent direct implementation
Solution Approach 1:
The patent makes accumulator circuits programmable and configurable through a control unit, allowing the same hardware resources to be dynamically assigned to different features and accumulation operations. This multi-functionality enables the system to adapt to varying resource constraints and precision requirements while maintaining data conflict avoidance through proper resource management.
Solution Approach 2:
The patent introduces dynamic configuration of accumulator circuits through a control unit that can reassign accumulator resources based on runtime conditions. This dynamic approach allows the system to adapt resource allocation to changing data conflict patterns and operational requirements, overcoming the rigidity of dedicated accumulators while maintaining their conflict-avoidance benefits.
2Productivity
If pipeline optimization is applied to improve processing speed, then running time is reduced, but data dependence and data conflicts arise
Solution Approach 1:
The patent introduces a control unit as an intermediary that manages the interaction between pipeline stages and accumulator circuits. This control unit coordinates data flow through the pipeline, ensuring that accumulation operations are properly synchronized and that data dependencies are resolved before results are committed, thereby maintaining high processing speed while preventing data conflicts.
Solution Approach 2:
The patent implements feedback mechanisms through the control unit that monitor the state of accumulator circuits and pipeline stages. This feedback allows the system to detect potential data conflicts before they occur and adjust the pipeline execution accordingly, maintaining optimal processing speed while ensuring data integrity through conflict prevention.
3Productivity
If accumulator circuits are reassigned to the same feature during accumulation period, then resource utilization is improved, but data conflicts occur
Solution Approach 1:
The patent implements dynamic resource allocation where the control unit can reassign accumulator circuits to different features based on runtime conditions. This dynamic management allows high resource utilization by keeping accumulators busy with different features when appropriate, while preventing data conflicts through intelligent assignment that respects accumulation period constraints and data dependency relationships.
Data Source
AI summary
Provided are a programmable device for processing a data set, and a method for processing a data set. The programmable device includes a plurality of accumulation circuits, wherein each of the accumulation circuits includes a pipeline adder and a cache unit for storing a computation result of the pipeline adder; and a multiplexer for receiving in sequence data in a data set, dynamically determining a correlation between a plurality of features included in the data and the plurality of accumulation circuits, and respectively sending, according to the correlation, feature values of the plurality of features in the received data to corresponding accumulation circuits.