GPU Power Analysis Engineer

1 Month ago • 1-3 Years • Research & Development

Job Summary

Job Description

NVIDIA seeks a GPU Power Analysis Engineer to research, develop, and deploy power-efficient methodologies for next-generation GPUs and Tegra SOCs. Responsibilities include using internal tools and industry-standard software for pre-silicon power analysis, developing best practices, performing comparative analysis to identify anomalies, collaborating with design teams to interpret power data and implement fixes, selecting and running workloads for power analysis, and prototyping architectural features in Verilog. The role involves working closely with architects, performance engineers, software engineers, and ASIC design teams to improve power efficiency and reduce consumption.
Must have:
  • MS/PhD in related field
  • Understanding of energy consumption & low power design
  • Verilog & ASIC design knowledge
  • Strong coding (Python, C++)
  • Algorithm analysis skills
Good to have:
  • Power tools/flow development experience

Job Details

We are now looking for a Power Methodology and Analysis engineer.

NVIDIA prides ourselves in having energy efficient products. We believe that continuing to maintain our products' energy efficiency compared to 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 responsible for analyzing fullchip and unit-level power data, and driving ASIC teams to improve their units’ power efficiency.  Key responsibilities include developing techniques to model, analyze, and reduce 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 power analysis and reduction techniques for NVIDIA's next generation GPUs and Tegra SOCs. Your contributions will help us gain early insight into 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:

  • Use internally developed tools and industry standard pre-silicon gate-level and RTL power analysis tools, to help improve product power efficiency.

  • Develop and share best practices for performing pre-silicon power analysis, Enhance internal power tools and automate best practices

  • Perform comparative power analysis, to spot trends and anomalies, that warrant more scrutiny.

  • Interact with architects and RTL designers to help them interpret their power data and identify power bugs; drive them to implement fixes.

  • Select and run a wide variety of workloads for power analysis, Collaborate with performance and architecture teams to validate performance of the workloads

  • Prototype a new architectural feature in Verilog and analyze power.

What we need to see:

  • MS with 1-3 years of experience or PhD in related fields.

  • Basic understanding of concepts of energy consumption, estimation, and low power design.

  • Familiarity with Verilog and ASIC design principles, including knowledge of logic cells.

  • Good verbal/written English and interpersonal skills; much collaboration with design teams is expected.

  • Strong coding skills, preferably in Python, C++.

  • Ability to formulate and analyze algorithms, and comment on their time complexity and memory consumption.

  • Desire to bring data-driven decision-making and analytics to improve our products.

Ways to stand out from the crowd:

  • Familiar with the power tools/flow development is a big plus

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, gender, sexual orientation, age, marital status, veteran status, or disability status.

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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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