Architect - Performance Verification and Analysis

NVIDIA's GPU and SoC Architecture group is seeking an architect with strong analytical skills and a deep understanding of system architecture and performance. As an Architect - Performance Verification and Analysis, you will have the opportunity to work on processor and system architecture performance of full applications, driving scalable improvements for artificial intelligence/machine learning, automotive, GeForce, and high-performance computing products.

Responsibilities:

• Perform performance analysis and bottleneck analysis of complex, high-performance GPUs and System-on-Chips (SoCs)
• Work on hardware models of different levels of extraction, including performance models, RTL test benches, and emulators to find performance bottlenecks in the system
• Collaborate with architecture and design teams to explore architecture trade-offs related to system performance, area, and power consumption
• Understand key performance use cases for the product and develop workloads and test suites targeting graphics, machine learning, automotive, video, and compute vision applications
• Drive methodologies for improving turnaround time, finding representative data sets, and enabling performance analysis early in the product development cycle
• Develop required infrastructure, including performance simulators, testbench components, and analysis tools

Requirements:

• BE/BTech or MS/MTech, or equivalent experience in a relevant area; PhD is a plus
• 2+ years of relevant experience dealing with system-level architecture and performance issues
• Strong understanding of System-on-Chip (SoC) architecture, graphics pipeline, CPU architecture, memory subsystem architecture, and Network-on-Chip (NoC)/Interconnect architecture
• Solid programming (C/C++) and scripting (Bash/Perl/Python) skills; exposure to Verilog/System Verilog, SystemC/TLM is a strong plus
• Strong debugging and analysis skills, including use of RTL dumps to debug failures
• Excellent communication and organization skills
• Ability to work in a global team environment

Preferred Qualifications:

• Strong background in System Level Performance aspects for Graphics and High Performance Computing
• Exposure to GPU application programming interfaces like CUDA, OpenGL, DirectX
• Expertise in data analysis and visualization