The Memristive Boltzmann Machines

The Boltzmann machine is a massively parallel computational model capable of solving a broad class of combinatorial optimization problems. In recent years, it has successfully been applied to training deep machine learning models on massive datasets. High-performance implementations of the Boltzmann machine using GPUs, MPI-based high-performance computing clusters, and field-programmable gate arrays have been proposed in the literature. Regrettably, the required all-to-all communication among the processing units limits the performance of these efforts. The proposed memristive Boltzmann machine is a massively parallel, memory-centric hardware accelerator based on recently developed resistive RAM (RRAM) technology. The proposed accelerator exploits the electrical properties of RRAM to realize in situ, fine-grained parallel computation within memory arrays, thereby eliminating the need for exchanging data between the memory cells and the computational units.