Deep expertise in GPU architectures (CUDA, OpenCL, or similar) Proven experience evaluating workload suitability for GPU acceleration Strong understanding of performance characteristics of integer-based algorithms on GPU vs CPU Demonstrated experience analyzing and optimizing computational workloads for heterogeneous computing environments Proficiency in performance profiling, benchmarking, and cost-benefit analysis Solid foundation in parallel computing principles Experience with semiconductor EDA or Electronic Design Automation