CPU Performance Architect

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent practical experience
  
• 1 year of experience with CPU architecture, microarchitecture, and subsystem integration at architectural and RTL levels
  
• 1 year of experience with C/C++ and scripting languages (e.g. Python)
  

Preferred qualifications:

• Master’s degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science emphasizing on computer architecture
  
• 2 years of experience with CPU, GPU, Fabric and Cache performance model development, performance analysis, and workload characterization
  
• Experience with advanced CPU techniques such as AI engines, branch predictors, IFU, LSU, and advanced prefetching algorithms
  
• Experience in CPU subsystem design for mobile based and device classes of SOCs
  
• In-depth knowledge of CPU memory system architecture, including familiarity with techniques such as simpoints generation methodology for standard CPU performance benchmarks
  
• In-depth understanding of specific CPU applications for mobile and other devices
  

About the job

As a CPU Performance Architect, you'll be the key contributor to the CPU subsystem architecture and microarchitecture definitions. You’ll collaborate with system performance and software teams to plan and conduct workload performance analysis, debug performance bottlenecks, and project performance at various design phases. You’ll be working with engineers in power, thermal, security, physical design, and other subsystem teams on the CPU subsystem configuration, architecture, microarchitecture features, and Performance, Power, Area (PPA) tradeoff analysis.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

Responsibilities

• Assess performance analysis infrastructure, which includes preparing workloads, developing performance models, and conducting performance and workload analysis.
  
• Participate in Performance, Power, Area (PPA) tradeoff analysis for architecture and microarchitecture features. Communicate analysis results in both qualitative and quantitative fashion to support major decisions.
  
• Assess performance analysis infrastructure, which includes preparing workloads, developing performance models, and conducting performance and workload analysis.
  
• Provide in-depth CPU performance analysis and understand performance bottlenecks.
  
• Work with the RTL team to correlate the performance model with the RTL.