Graphics Processing Unit Performance Architect

Contenuto del lavoro

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Minimum qualifications:

• Master’s degree in Electrical Engineering or Computer Science, or equivalent practical experience.
• Experience with GPU software and hardware pipeline architecture.
• Experience in architecture performance analysis, tools, and simulators (either Cycle Accurate or Functional) using C++ and Python or equivalent.
• Experience with computer architecture concepts, such as pipelining, caches, and virtual memory.

Preferred qualifications:

• PhD degree in Electrical Engineering or Computer Science, or equivalent practical experience.
• Experience developing and analyzing workloads for GPUs.
• Experience with developing optimizing compilers in conjunction with hardware.
• Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware.
• Knowledge of ARM-based system architecture concepts.

About The Job

Our computational challenges are so big, complex and unique we can’t just purchase off-the-shelf hardware, we’ve got to make it ourselves. Your team designs and builds the hardware, software and networking technologies that power all of Google’s services. As a Hardware Engineer, you design and build the systems that are the heart of the world’s largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of Google users.

As a Graphics Processing Unit (GPU) Performance Architect, you will architect/configure the main GPU cluster on Application Specific Integrated Circuit (ASIC) products. You will collaborate with software and hardware architects to optimize gaming, imaging, and other relevant workloads running on the GPU. You will project performance/power on key workloads to assess the competitiveness of the design as part of the overall ASIC definition.

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

• Define configuration of GPU cores for ASICs based on GPU workload analysis.
• Propose architectural features/requirements for GPU to better integrate GPU with ASIC to improve overall performance.
• Work with Google Machine Learning, software, and device teams to bring compelling experiences leveraging GPUs to Google.
• Optimize the overall ASIC and software stack for GPU workloads.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing this form .