Quantization-Aware Training Effects on Latency-Throughput Trade-offs in FPGA-Deployed Transformers

This report synthesises findings from 10 peer-reviewed papers addressing the following research question: How does quantization-aware training impact the latency-throughput trade-off of hls4ml-deployed transformer models on FPGA accelerators compared to post-training quantization. 9 claims were extracted from source literature; 9 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.7/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: How does quantization-aware training impact the latency-throughput trade-off of hls4ml-deployed transformer models on FPGA accelerators compared to post-training quantization?

Autonomous literature synthesis. Automated review score: 7.7/10. Full text and citation available at Assignee Research.