Force field-based classical molecular dynamics (CMD) is efficient but its potential energy
surface (PES) prediction error can be very large. Density functional theory (DFT)-based ab …

Processing-in-memory (PIM) seeks to eliminate computation/memory data transfer using
devices that support both storage and logic. Stateful logic techniques such as IMPLY …

Digital processing-in-memory (PIM) architectures are rapidly emerging to overcome the
memory-wall bottleneck by integrating logic within memory elements. Such architectures …

The emerging memristive Memory Processing Unit (mMPU) overcomes the memory wall
through memristive devices that unite storage and logic for real processing-in-memory (PIM) …

Processing-in-memory (PIM) solutions vastly accelerate systems by reducing data transfer
between computation and memory. Memristors possess a unique property that enables …

Deep neural network (DNN)-based transformer models have demonstrated remarkable
performance in natural language processing (NLP) applications. Unfortunately, the unique …

Digital memristive processing-in-memory overcomes the memory wall through a
fundamental storage device capable of stateful logic within crossbar arrays. Dynamically …

Processing in-memory has the potential to break von-Neumann based design principles and
unleash exascale computing capabilities. A rudimentary problem for in-memory paradigms …

Digital processing-in-memory (PIM) architectures mitigate the memory wall problem by
facilitating parallel bitwise operations directly within memory. Recent works have …

In-Memory Computing (IMC) is a promising computing paradigm to accelerate Big Data
applications. It reduces the data movement between memory and processing units, and …