GPU Architect, Silicon
Description For GPU Architect, Silicon
Google is seeking a GPU Architect to join their innovative hardware team focused on developing custom silicon solutions for Google's direct-to-consumer products. This role combines the cutting-edge fields of GPU architecture, machine learning, and system-on-chip design.
As a GPU Architect, you'll be instrumental in shaping the future of Google's Tensor SoC, working specifically on GPU cores and their integration. You'll collaborate with multiple teams including Machine Learning, GPU Software, and Android to create compelling experiences that leverage GPU capabilities effectively.
The position requires a strong background in computer architecture, with specific emphasis on GPU workload analysis and optimization. You'll be working with modern technologies including Vulkan, OpenGL, and OpenCL, while having the opportunity to influence the direction of Google's custom silicon development.
This is an exciting opportunity to be part of Google's hardware innovation team, where your work will directly impact millions of users worldwide through Google's consumer products. You'll be contributing to the development of next-generation hardware experiences, focusing on delivering unparalleled performance, efficiency, and integration.
The role offers the chance to work with diverse teams, pushing the boundaries of what's possible in hardware design while being backed by Google's extensive resources and commitment to technological advancement. If you're passionate about GPU architecture, system design, and want to be at the forefront of hardware innovation, this role offers the perfect platform to make a significant impact.
Responsibilities For GPU Architect, Silicon
- Define Graphics Processing Unit (GPU) cores for the Tensor SoC based on GPU workload analysis
- Propose architectural features/requirements for GPU to better integrate GPU with Tensor SoC to improve overall performance
- Work with Google Machine Learning, GPU Software, Android and device teams to bring compelling experiences leveraging GPUs to Google
- Enhance the overall Tensor SoC and software stack for GPU workloads
Requirements For GPU Architect, Silicon
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience
- Experience in architecture performance analysis, tools, or simulators using C++ and Python or similar
- Experience in using computer architecture concepts, such as pipelining, caches, virtual memory
- Master's degree or PhD in Computer Science, Electrical Engineering preferred
- Experience developing and analyzing workloads for GPUs preferred
- Experience with developing optimizing compilers preferred
- Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware preferred
- Knowledge of ARM-based system architecture concepts preferred
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