Probabilistic Memory Architecture That Bridges The Gap Between RNG Sampling and Memory Access (Notre Dame, Georgia Tech, Villanova)

Probabilistic Memory Architecture That Bridges The Gap Between RNG Sampling and Memory Access (Notre Dame, Georgia Tech, Villanova)

Researchers from University of Notre Dame, Georgia Institute of Technology, and Villanova University published a technical paper titled “Probabilistic Memory for Trustworthy Edge Intelligence.” Summary: The paper introduces p-MEM as “a unified memory primitive” that samples at “the native memory bandwidth.” It reports reductions in instruction count, sampling latency, and energy for Bayesian neural network workloads. Find the technical paper her…