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Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
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The Performance and Modeling Engineer works with driver, compiler, and design engineers to improve GPU performance for next generation mobile products. The role involves validating functionality, quantifying performance benefits of features and algorithms, and implementing solutions in hardware and software. Daily tasks include conducting directed studies, measurements, simulations, benchmarking, and competitive analysis to solve performance challenges unique to mobile GPUs. Key responsibilities involve debugging performance issues, developing GPU models, and creating tools for efficient measurement and communication. Required skills include using C, Python, Pandas, Matplotlib, and Shell for automation and data visualization. Candidates must also utilize SystemVerilog, Verilog, and Git to analyze RTL, instruction scheduling, register allocation, and code generation. The work focuses on GPU microarchitecture analysis, memory hierarchy, and NUMA architecture across silicon and pre-silicon environments.
Validate functionality and quantify performance benefits of new GPU features and algorithms.
Implement performance improvements across both hardware and software platforms.
Conduct measurements, simulations, and benchmarking to address unique mobile GPU performance challenges.
Debug GPU performance issues and collaborate with design engineers to implement fixes.
Develop GPU models in coordination with software teams across different sections.
Create tools and automation scripts to facilitate efficient performance measurement and communication.
Analyze RTL to identify and debug hardware-level performance bottlenecks.
Build performance dashboards and report regression trends using Python and data visualization tools.
What we're looking for
Bachelor’s degree or foreign equivalent in Electrical engineering, Electronics engineering, or a related field.
At least 1 year of experience in the job offered or a related occupation.
Experience using C and Python to develop performance analysis tools and automation scripts for GPU microarchitecture evaluation.
Experience with compiler toolchains, including analyzing instruction scheduling, register allocation, and code generation for GPU compute workloads.
Experience using SystemVerilog or Verilog to read and analyze RTL to identify and debug hardware-level performance bottlenecks.
Experience in GPU microarchitecture analysis using performance counters to evaluate throughput, latency, and execution unit utilization.
Experience in memory hierarchy and NUMA architecture analysis, including cache behavior, memory bandwidth characterization, and error correction.
Experience in full-stack hardware/software performance analysis, correlating compiler output to microarchitecture execution across silicon and pre-silicon environments.