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Device Codesign using Reinforcement Learning
We demonstrate device codesign using reinforcement learning for probabilistic computing
applications. We use a spin orbit torque magnetic tunnel junction model (SOT-MTJ) as the …
applications. We use a spin orbit torque magnetic tunnel junction model (SOT-MTJ) as the …
Stoch-IMC: A bit-parallel stochastic in-memory computing architecture based on STT-MRAM
In-memory computing (IMC) offloads parts of the computations to memory to fulfill the
performance and energy demands of applications such as neuromorphic computing …
performance and energy demands of applications such as neuromorphic computing …
AI-Guided Codesign Framework for Novel Material and Device Design applied to MTJ-based True Random Number Generators
Novel devices and novel computing paradigms are key for energy efficient, performant future
computing systems. However, designing devices for new applications is often time …
computing systems. However, designing devices for new applications is often time …
High-Speed Tunable Generation of Random Number Distributions Using Actuated Perpendicular Magnetic Tunnel Junctions
Perpendicular magnetic tunnel junctions (pMTJs) actuated by nanosecond pulses are
emerging as promising devices for true random number generation (TRNG) due to their …
emerging as promising devices for true random number generation (TRNG) due to their …