GPU Performance Modelling Architect

Company

Qualcomm India Private Limited

Job Area

Engineering Group, Engineering Group > Systems Engineering

General Summary

Drive architecture exploration and performance analysis for next-generation GPUs through modeling, simulation, and workload characterization. Partner with architecture, software, compiler, and hardware teams to influence design decisions using data-driven insights.

Key Deliverables

Develop and maintain GPU performance models for architecture evaluation.Conduct Performance analysis of graphics and compute workloads to identify bottlenecks.Perform architectural trade-off studies to generate and defend performance projections.Bring up new workloads on Performance Models by fixing bugs and developing new features.Evaluate new features and provide recommendations to improve performance and efficiency.Build automation and analysis tools to improve modeling productivity.

Responsibilities

Design and execute performance experiments and simulations.Conduct root-cause analysis and derive actionable architectural insights.Collaborate with cross-functional teams on feature development and optimization.Develop tools, workflows, and methodologies for performance analysis.Present findings and influence future architecture decisions.

Critical / Must-Have Skills

Strong understanding of computer architectureStrong analytical, debugging, and problem-solving skills.Proficiency in C/C++ and Python.Experience with architectural simulators and performance prediction.Experience with performance analysis, profiling, and workload characterization.Strong verbal and written communication skills

Good-to-Have Skills

GPU/CPU/Memory architecture and/or Graphics fundamentals.Good knowledge of modern 3D graphics pipelines and APIs (Vulkan/DX12/OpenGL).Experience building performance analysis tools and automation frameworks.Technical leadership and cross-functional collaboration experience.

Minimum Qualifications

Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Systems Engineering or related work experience.

OR

Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Systems Engineering or related work experience.

OR

PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.

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