Senior GPU Power Engineer (Pre/Post-Silicon)

QUALCOMM, Inc.

San Diego (CA)

On-site

USD 141,000 - 212,000

Full time

5 days ago
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Job summary

Qualcomm Technologies, Inc. is seeking an experienced engineer to analyze GPU architecture and microarchitecture, focusing on power and performance optimizations. The role involves power modeling for projections and correlations, workload profiling, and developing pre/post-silicon power tests.

Collaboration spans RTL, architecture, compiler, driver, and silicon teams. The candidate should have a strong background in GPU/CPU architecture, VLSI concepts, and scripting in Python/Perl, with at least

Qualifications

  • Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
  • Experience with scripting in Python or Perl.
  • 5+ years of experience with low-power ASIC optimization.

Responsibilities

  • Analyze and evaluate GPU architecture/microarchitecture and workload for performance and power optimizations.
  • GPU power modeling and estimation for projection and correlation.
  • GPU workload analysis, profiling, and characterizations.
  • Develop and maintain tests for pre-silicon and post-silicon power verifications.
  • Work closely with RTL designer, architecture, design verification, compiler, driver, silicon implementation, and post-silicon teams.

Skills

C/C++ Programming
Python/Perl scripting
Assembly
Verilog/SystemVerilog
Design Verification
GPU Architecture

Education

Bachelor's degree in computer engineering / CS / EE
Master's or PhD preferred
2+ years software/hardware experience (alternative)

Tools

PrimeTime PX
Power Artist

Job description

Qualcomm Technologies, Inc. is seeking an experienced engineer to analyze GPU architecture and microarchitecture, focusing on power and performance optimizations. The role involves power modeling for projections and correlations, workload profiling, and developing pre/post-silicon power tests.

Collaboration spans RTL, architecture, compiler, driver, and silicon teams. The candidate should have a strong background in GPU/CPU architecture, VLSI concepts, and scripting in Python/Perl, with at least

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