Prototyping an Edge-AI Controller Before Tape-Out
Specialized Engineering Scope & Mission Challenge
A fabless semiconductor startup developing an ultra-low-power neural processing unit (NPU) for edge devices needed to validate their architecture and develop production firmware long before final silicon returned from the foundry. Software simulators were too slow to execute real convolutional neural networks (CNNs), taking days to process a single video frame. Without a hardware emulation prototype, software and driver teams could not validate memory latency, bus arbitration, and quantization accuracy, putting customer product launch commitments at severe risk.
Granular Competency & Technical Requirement Matrix
Critical Engineering & Integration Complexities
- Fitting a multi-million-gate ASIC design into multi-FPGA partitions while managing inter-FPGA routing delays and pin limits.
- Reconciling ASIC clock trees and gated clocks with FPGA global clock routing architecture.
- Diagnosing intermittent race conditions between high-speed AXI DMA channels and external DDR memory under heavy inference loads.
- Real-time debugging constraints where logic analyzer buffer depths are limited during full model execution.
Engineered Delivery & Execution Workflow
RTL Partitioning & Clock Mapping
Restructured ASIC RTL, transforming gated clock cells into FPGA-compatible clock enables across UltraScale+ FPGAs.
Memory & Host Interface Synthesis
Configured hard memory controllers for DDR4 and PCIe Gen 4 interconnects with host test PCs.
Timing Closure & Place-and-Route
Solved challenging timing violations and setup/hold constraints across high-utilization FPGA logic blocks.
Bare-Metal Diagnostic Suite
Developed C diagnostic firmware validating NPU register access, convolution matrix units, and DMA bursts.
Linux Driver & Kernel Porting
Built and deployed an embedded Linux kernel with optimized DMA engine drivers communicating with the FPGA prototype.
AI Workload Execution
Executed MobileNet and YOLO object detection models on the FPGA prototype, comparing inference outputs against Python golden models.
Firmware Handover
Provided software teams with a 24/7 accessible remote hardware testbed running 500x faster than software simulators.
Production Toolchains, Protocols & Frameworks
06 | PROJECT TARGETS
Project Targets and Business Impact
Customer Confidentiality Note: Customer identity, proprietary codebases, and commercial program specifics have been anonymized in accordance with non-disclosure agreements.