FPGA-based ai algorithm programmable deployment architecture optimization method
By normalizing the target operator of the FPGA's artificial intelligence model into a product summation form, extracting the features of the computation segment and performing restricted rearrangement, the problem of the difficulty in dynamically adjusting the deployment scheme in the existing technology is solved, and more efficient resource utilization and operational stability are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHANGHAI LOVE VALLEY TECHNOLOGY CO LTD
- Filing Date
- 2026-03-30
- Publication Date
- 2026-06-26
AI Technical Summary
Existing FPGA-based AI model deployment solutions struggle to maintain intermediate computational continuity while enabling low-overhead, targeted dynamic adjustments, impacting deployment flexibility and operational efficiency.
By normalizing the target operator in the artificial intelligence model into a product summation form, the characteristics of the computation segment are extracted, a segment stability index is generated, and under the condition of keeping the numerical equivalence relationship and cumulative dependency relationship unchanged, the product terms are subjected to restricted rearrangement and mapped to the static computation area or local reconstruction area, generating arithmetic-level and deployment-level description files. At runtime, execution statistics are collected for dynamic adjustment.
It improves the utilization efficiency of on-chip computing resources, enhances on-chip storage reuse capabilities, improves bus bandwidth allocation, enhances deployment process consistency, and improves operational stability and adaptability.
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