The Compute System Architect team is dedicated to GPU compute and memory subsystems, providing opportunities to explore sophisticated cross-unit features in modern GPU architectures. The team works as the safety net of the chip. We catch function bugs in the HW by randomly generating tests and running them in various pre-silicon full chip platforms and debugging the failures. This work provides a good full-chip view of GPU and has a big space to innovate.
What you’ll be doing:
Explore innovative GPU composition and novel system functionalities related to processing and storage.
Connect with GPU architecture designers to make advised and random functional testing plan which provides good coverage.
Innovatively develop and improve infrastructure and methodology to generate tests.
Massively generate, run and debug tests in various platforms, e.g., functional simulator, full chip and unit-level RTL, emulator and silicon.
Build innovative tools to improve efficiency.
What we need to see:
Knowledge of computer architecture, compiler, assembly language.
Good understanding of GPU concept and pipeline, in terms of parallel computing and/or memory system.
Familiar with Linux
Good at C++ and Python development.
Bachelor in CS or EE. MS or PhD or equivalent experience is a plus.
Ways to stand out from the crowd:
Knowledge and experience of CUDA programming and debugging.
Random system development and work experience.
ASIC experience.
Compiler experience
NVIDIA is widely considered to be one of the technological world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you.