Principal GPU Memory Architect

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking a Principal GPU Memory Architect to design and optimize future high-performance computing systems, focusing on enhancing power-constrained performance of hardware. The role involves developing innovative processor and system architectures, with a deep focus on memory systems and energy efficiency, optimizing for perf/W, perf/mm, and perf/$. Responsibilities include developing architecture models, analyzing performance and power simulations, and debugging issues across various stages from models to silicon. Requires extensive experience in CPU/GPU architecture, memory systems design, and expertise in power analysis and modeling.

What you'd actually do

  1. Develop innovative high-performance processor and system architectures, focusing on the memory system and energy efficiency.
  2. Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory systems, optimizing along the axes of perf/W, perf/mm, and perf/$.
  3. Develop and enhance architecture prototype models for power and noise analysis.
  4. Participate in performance and power simulation of features to analyze, define, and improve energy per byte.
  5. Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify areas for architecture optimizations.

Skills

Required

  • CPU/GPU architecture
  • memory systems design
  • energy efficiency
  • power analysis and modeling
  • C
  • C++
  • scripting languages

Nice to have

  • MS/PhD in Electrical Engineering, Computer Science, or related field
  • Verilog or VHDL
  • developing and optimizing algorithms for power efficiency
  • hardware design languages
  • communication skills

What the JD emphasized

  • strong track record of understanding and analyzing memory systems architecture
  • focus on enhancing the power-constrained performance of the hardware
  • focus on memory system and energy efficiency
  • optimizing along the axes of perf/W, perf/mm, and perf/$
  • energy per byte
  • power analysis and modeling
  • 18+ yrs of experience