NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel.
NVIDIA is seeking a motivated memory subsystem architects with great analytical skills and a deep understanding of system architecture and performance, to work with a team to model, debug and analyze performance issues in the Memory subsystem.
What you will be doing:
Contribute to advancing GPU Architecture and Simulators, GPU testing infrastructure, metrics, and/or compilers.
Performance modeling and simulation of features to improve memory system efficiency.
Develop test plans and testing infrastructure.
Debug tests on architecture simulators.
Performance analysis/ bottleneck analysis of sophisticated, Memory subsystem units and features.
Work on hardware models of different levels of extraction, including performance models, RTL test benches and emulators to find performance bottlenecks in the system.
Working with various multi functional teams like ASIC design and verification..
What we need to see:
Master/Bachelor's degree in Electrical Engineering, Computer Science, Computer Engineering or related field (or equivalent experience).
3+ years experience dealing with system level architecture and performance issues.
Strong programming ability in C, C++. Exposure to Verilog/System Verilog is a strong plus.
Good understanding of Memory subsystem architecture, caches , MMU, memory controller, NOC / interconnects, computer architecture.
Debugging and analysis, including use of RTL dumps to debug failures.
Exposure to performance simulators, cycle accurate/approximate models or emulators for pre-silicon performance analysis is a plus.
Strong communication and interpersonal skills are required along with the ability to work in a dynamic, product oriented, distributed team.
Ways to stand out from the crowd:
Knowledge of the memory system, caching, interconnects, DRAM controller, Memory management unit, performance modeling and analysis.
Widely considered to be one of the technology world’s most desirable employers. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment.
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NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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