RippleMatch Opportunities - Santa Clara, CA

posted 2 months ago

Full-time - Entry Level
Santa Clara, CA

About the position

This role is with Nvidia, a world leader in providing energy-efficient high-performance products. We are looking for a Datacenter GPU Power Architect - New College Grad! NVIDIA continues to invest in the research and development of hyper-efficient GPU and SOC architectures, continually innovating in creative and unrivaled ways to improve our ability to deliver exceptional Perf/Watt solutions across various sectors and verticals. As part of NVIDIA's Applied Power Architecture team, you will be involved in developing state-of-the-art GPUs that power AI, HPC, Automotive, GeForce, and Mobile products. In this position, you will contribute to power estimation models and tools for GPU products and systems, such as NVIDIA DGX. Your responsibilities will include early GPU and system architecture exploration with a focus on energy efficiency and total cost of ownership (TCO) improvements at both the GPU and datacenter levels. You will assist in performance versus power analysis for NVIDIA's future product lineup and deploy machine learning techniques to develop highly accurate power and performance models for our GPUs, CPUs, switches, and platforms. Additionally, you will need to understand the workload characteristics for GenAI/HPC workloads at datacenter scale (multi-GPU) to drive new hardware/software features for Perf@Watt improvements. Your work will also involve modeling and analyzing cutting-edge technologies like high-speed and high-density interconnects.

Responsibilities

  • Contribute to power estimation models and tools for GPU products and systems like NVIDIA DGX.
  • Conduct early GPU and system architecture exploration focusing on energy efficiency and TCO improvements.
  • Assist with performance vs power analysis for NVIDIA's future product lineup.
  • Deploy machine learning techniques to develop accurate power and performance models of GPUs, CPUs, switches, and platforms.
  • Understand workload characteristics for GenAI/HPC workloads at datacenter scale to drive new HW/SW features for Perf@Watt improvements.
  • Model and analyze cutting-edge technologies like high-speed and high-density interconnects.

Requirements

  • Pursuing a MSEE/MSCE, or equivalent experience related to Power / Performance estimation and optimization techniques.
  • Knowledge of energy-efficient chip design fundamentals and related tradeoffs.
  • Familiarity with low power design techniques such as multi-VT, clock gating, power gating, and Dynamic Voltage-Frequency Scaling (DVFS).
  • Understanding of processors (GPU is a plus), system-SW architectures, and their performance/power modeling techniques.
  • Proficiency with Python and data analysis packages like Pandas, NumPy, PyTorch.
  • Familiarity with performance monitors/simulators used in modern processor architectures.

Benefits

  • Equity options
  • Comprehensive health benefits
  • Diversity and inclusion programs
  • Professional development opportunities
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