Performance Optimization: Profile and optimize existing C/C++ and CUDA code to achieve real-time performance for a comprehensive software ISP pipeline.
CUDA Implementation: Translate complex image processing algorithms into highly parallelized
CUDA kernels, optimizing memory access and execution configurations.
Rapid Prototyping: Utilize Python scripting to develop and validate Proof of Concepts (PoCs)
for quick algorithm evaluation.
Code Quality: Deliver clean, maintainable, and well-documented C/C++ and CUDA code.
Required Qualifications
Experience: 5+ years of hands-on experience in CUDA optimization targeting NVIDIA server-range or desktop-range GPUs.
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