Design, develop, and maintain GPU performance foundation libraries for Nsight tools with focus on high fidelity hardware events and counters.
Develop and implement GPU assembly tests.
Build and maintain a test validation framework written primarily in CUDA and GPU Assembly.
Utilize emulators to debug and verify instruction events.
Document tools use cases and data processing workflows to facilitate architectural explorations.

Requirements

B.S. EE/CS (or equivalent experience) and 5+ years of experience or MS with 2+ years' experience, or Ph.D.
Strong programming ability in C, C++, and scripting languages such as Python.
Good understanding or prior experience with low level assembly code.
Solid understanding of hardware pipeline and execution unit instruction pipeline concepts, with a willingness to work at a detailed implementation level.
Knowledge of hardware-software co-design principles and practices.
Experience with performance analysis and optimization of software on hardware accelerators.
Experience with developing on simulators and emulators.
Excellent problem-solving skills and the ability to work collaboratively in a team environment.
Strong communication skills, both written and verbal.

Benefits

equity
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Applicant Tracking System Keywords

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Hard Skills & Tools

CUDACC++PythonGPU assemblyperformance analysisoptimizationsimulatorsemulatorshardware-software co-design

Soft Skills

problem-solvingcollaborationcommunication

Certifications

B.S. EEB.S. CSM.S.Ph.D.