Toptal: GPU Strategy Advisor

About the Company

A global leader in electronic design automation software, this organization empowers innovators in the microchip and semiconductor industries to push the boundaries of technology. With cutting-edge solutions that enable optimal circuit design and semiconductor development, the company serves as a trusted partner to organizations driving the future of electronics and computational hardware.

About the role

We are seeking a GPU Architecture and Performance Expert to assess and advise on GPU porting strategy for our product, specifically evaluating whether GPU acceleration can deliver material performance improvements for our integer-based algorithms.

• Location: Global
• Type: 10h/week Contract
• Duration: 3+ months
• Authorization: Applicants must be authorized to work in their country of residence without employer sponsorship

Responsibilities

• Conduct comprehensive technical assessment of the product’s native algorithms to determine viability and efficiency gains from GPU acceleration

• Analyze integer-based computational workloads and specialized solvers to evaluate whether GPU architectures can provide meaningful performance improvements

• Provide strategic recommendations on GPU investment decisions, including cost-benefit analysis and expected acceleration potential for specific algorithm types

• Deliver data-driven insights on which computations are strong candidates for GPU porting versus those that should remain CPU-optimized

• Guide technical teams on implementation strategies if GPU acceleration proves viable, including architecture selection and optimization approaches

• Deep expertise in GPU architectures (CUDA, OpenCL, or similar) with proven experience evaluating workload suitability for GPU acceleration
• Strong understanding of the performance characteristics of integer-based algorithms on GPU versus CPU architectures
• Demonstrated experience analyzing and optimizing computational workloads for heterogeneous computing environments
• Proficiency in performance profiling, benchmarking, and cost-benefit analysis for hardware acceleration decisions
• Solid foundation in parallel computing principles and understanding of when GPU acceleration provides material benefits
• Experience with semiconductor EDA or Electronic Design Automation
• 15+ years of professional experience

 100% remote and there are no location restrictions and time zone overlaps