英伟达ASIC Physical Design Engineer - New College Grad 2026
任职要求
• MS in EE or Microelectronics • Project experience in IC design implementation • Courses taken in circuit design, digital design • Hand-on experience in EDA software f…
工作职责
• Chip integration and netlist generation • Synthesis, RTL/netlist quality check, Formal Verification • Constraints creation and validation, timing budget. • Work with ASIC team to analyze/resolve special timing issues. • Cross-Team collaboration to implement chip partitioning and floorplan • Work in conjunction with PR engineers to achieve timing closure • Achieve special mode timing closure, such as io, test, clock, async etc. • Function eco creation and method development • Develop and improve entire timing closure flow from frontend (pre-layout) to backend (post-layout) • Methodology and flow automation development for above areas.
At NVIDIA, we pride ourselves in having energy efficient products. We believe that continuing to maintain our products' energy efficiency compared to the competition is key to our continued success. Our team is responsible for researching, developing, and deploying methodologies to help NVIDIA's products become more energy efficient; and is responsible for building energy models that integrate into architectural simulators, RTL simulation, and emulation platforms. Key responsibilities include developing techniques to model, analyze, and reduce the power consumption of NVIDIA GPUs. As a member of the Power Modeling, Methodology, and Analysis Team, you will collaborate with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, and Physical Design teams to study and implement energy modeling techniques for NVIDIA's next-generation GPUs and Tegra SOCs. Your contributions will help us gain early insight into the energy consumption of graphics and artificial intelligence workloads, and will allow us to influence architectural, design, and power management improvements. What you’ll be doing: • Work with architects and performance architects to develop an energy-efficient GPU. • Develop methodologies and workflows to select and run a wide variety of workloads to train models using ML and/or statistical techniques. • Develop methodologies to improve the accuracy of energy models under various constraints, such as, process, timing, floorplan and layout. • Correlate the predicted energy from models created at different stages of the design cycle, with the goal of bridging early estimates to silicon. • Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL and architectural simulators. Work with architects to fix the identified energy inefficiencies. • Work with performance, verification and emulation methodology and infrastructure development teams to integrate energy models into their platforms. • Prototype new architectural features, create an energy model, and analyze the system impact.
At NVIDIA, we pride ourselves in having energy efficient products. We believe that continuing to maintain our products' energy efficiency compared to the competition is key to our continued success. Our team is responsible for researching, developing, and deploying methodologies to help NVIDIA's products become more energy efficient; and is responsible for building energy models that integrate into architectural simulators, RTL simulation, and emulation platforms. Key responsibilities include developing techniques to model, analyze, and reduce the power consumption of NVIDIA GPUs. As a member of the Power Modeling, Methodology, and Analysis Team, you will collaborate with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, and Physical Design teams to study and implement energy modeling techniques for NVIDIA's next-generation GPUs and Tegra SOCs. Your contributions will help us gain early insight into the energy consumption of graphics and artificial intelligence workloads, and will allow us to influence architectural, design, and power management improvements. What you’ll be doing: • Work with architects and performance architects to develop an energy-efficient GPU. • Develop methodologies and workflows to select and run a wide variety of workloads to train models using ML and/or statistical techniques. • Develop methodologies to improve the accuracy of energy models under various constraints, such as, process, timing, floorplan and layout. • Correlate the predicted energy from models created at different stages of the design cycle, with the goal of bridging early estimates to silicon. • Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL and architectural simulators. Work with architects to fix the identified energy inefficiencies. • Work with performance, verification and emulation methodology and infrastructure development teams to integrate energy models into their platforms. • Prototype new architectural features, create an energy model, and analyze the system impact.
• Chip integration and netlist generation • Synthesis • RTL/netlist quality check, Formal Verification, constraints creation and validation, timing budget. • Work with ASIC team to analyze/resolve special timing issues. • Cross-Team collaboration to implement chip partitioning and floorplan • Work in conjunction with PR engineers to achieve timing closure for both partition and full chip level; Achieve special mode timing closure, such as io, test, clock, async etc. • Function eco creation; Develop and improve entire timing closure flow from frontend (pre-layout) to backend (post-layout) • Flow automation development for above areas; Methodology in any of above areas.