Energy Efficient Computing
THE BENEFITS OF ARTIFICIAL INTELLIGENCE
Around the world, artificial intelligence is rapidly becoming technology’s most important priority, enabling new services such as robotics and autonomous vehicles, and enhancing existing operations like telemedicine and e-learning. Governments, organizations and individuals all stand to gain from these immense benefits of AI.
The future of AI is very bright. However, challenges abound with respect to deploying AI in a sustainable fashion.
HARDWARE/SOFTWARE CO-DESIGN FOR SUSTAINABLE
We’ve outlined plans for three key areas in which we are committing research and development resources.
These areas align with our own passions and ability as well as remain top priorities for society.
Most AI models employ dense matrix operations – these require increased computing density, unlike sparse computations that can offer improved energy efficiency. Based on these principles we design tools to achieve more energy-efficient AI computing. Our approach involves 3 levels of optimization: model-level, kernel-level and system-level.
With models optimized at the algorithmic level, hardware must evolve accordingly. We perform hardware re-designs simultaneously with algorithmic level optimizations while optimizing for energy efficiency and chip re-use. This flexibility allows us to use a single processor architecture for multiple workloads, recycling our hardware real-estate, reducing e-waste and improving circularity.
We welcome university faculty and researchers interested in collaborations in the area of hardware/software co-optimization for sustainability.
See how Energy Efficient AI applies to applications in healthcare and health equity.
Work on innovative research through our internship program and make an impact in the world today!