2021 International Conference on Field-Programmable Technology (ICFPT) 2021
DOI: 10.1109/icfpt52863.2021.9609699
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A High-Performance and Flexible FPGA Inference Accelerator for Decision Forests Based on Prior Feature Space Partitioning

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Cited by 4 publications
(1 citation statement)
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“…In RF, individual decision trees can be evaluated independently in their reasoning process, thereby making them wellsuited for parallelized acceleration on an FPGA [17], [20], [30], [31]. In most previous studies, the decision tree data comprising tree structures, decision nodes, and leaf nodes is stored in on-chip memory to allow multiple processing elements (PEs) perform the inference task in parallel.…”
Section: B Hardware Accelerator For Rf Classifiermentioning
confidence: 99%
“…In RF, individual decision trees can be evaluated independently in their reasoning process, thereby making them wellsuited for parallelized acceleration on an FPGA [17], [20], [30], [31]. In most previous studies, the decision tree data comprising tree structures, decision nodes, and leaf nodes is stored in on-chip memory to allow multiple processing elements (PEs) perform the inference task in parallel.…”
Section: B Hardware Accelerator For Rf Classifiermentioning
confidence: 99%