Deep Dive into p-bits: IEEE JxCDC paper out
Excited to announce the recent publication of our paper in IEEE JxCDC, titled "A Full-Stack View of Probabilistic Computing with P-bits: Devices, Architectures, and Algorithms." This comprehensive review explores the potential of p-bits as a solution to the growing energy consumption and computational demands of modern AI algorithms.
The paper delves into the integration of transistors with emerging technologies to create energy-efficient, domain-specific probabilistic systems. We provide an in-depth analysis of p-bit applications across hardware, architecture, and algorithmic perspectives, highlighting their use in areas like probabilistic machine learning, AI, combinatorial optimization, and quantum simulation.
By combining innovative nanodevices with the existing CMOS ecosystem, we believe that probabilistic computers can achieve significant improvements in energy efficiency and probabilistic sampling, opening up new possibilities for powerful probabilistic algorithms.
Feel free to check out the [open-access] full article [here] to learn more about our findings and the future of p-bit computing.
