GPU Memory Architect for Power-Efficient HPC

NVIDIA; California (MO); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a world-class computer architect to contribute to the development of future high-performance computing systems, with a focus on enhancing power-constrained performance. The role emphasizes memory systems, perf/W, and perf/mm optimization across GPU architectures.

The candidate will model power, performance, and area, validate designs with simulations, and collaborate with partners on system infrastructure to push energy efficiency and performance boundaries.

Qualifications

• 10+ years of CPU/GPU architecture experience.
• Bachelor's degree in Electrical Engineering, Computer Science, or related field.
• Expertise in power analysis and modeling in pipeline-based architectures.
• Experience with Ansys Power Artist and Synopsys PTPX.

Responsibilities

• Develop innovative high-performance processor and system architectures, focusing on the memory system and energy efficiency.
• Develop architecture and micro-architecture features to improve GPU memory systems, optimizing perf/W and perf/mm.
• Develop and enhance architecture prototype models for power and noise analysis.
• Participate in performance and power simulation to analyze, define, and improve energy per byte.
• Analyze benchmarks and workloads to identify architecture optimizations.
• Debug power, performance, and functional issues across models, RTL, silicon, and systems.

Skills

C

C++

Scripting languages

Power analysis

Education

Bachelor's in Electrical Engineering, Computer Science, or related field

Tools

Ansys Power Artist

Synopsys PTPX

Job description

NVIDIA is seeking a world-class computer architect to contribute to the development of future high-performance computing systems, with a focus on enhancing power-constrained performance. The role emphasizes memory systems, perf/W, and perf/mm optimization across GPU architectures.

The candidate will model power, performance, and area, validate designs with simulations, and collaborate with partners on system infrastructure to push energy efficiency and performance boundaries.