Processing in-memory breaks von Neumann-based constructs to accelerate data-intensive
applications. Noteworthy efforts have been devoted to executing Boolean logic using digital …

With the rise of data-intensive applications, traditional computing paradigms have hit the
memory-wall. In-memory computing using emerging nonvolatile memory (NVM) technology …

The rapid growth of data-intensive applications has spurred the interest for novel in-memory
computing paradigms. With the recent innovations within flow-based computing, complex …

In-memory computing using nonvolatile memory is a promising pathway to accelerate data-
intensive applications. While substantial research efforts have been dedicated to executing …

Flow-based computing is a digital in-memory computing paradigm with tremendous
potential. Its favorable characteristics, such as high robustness, low energy consumption …

The processor-memory bottleneck inherent to von Neumann architectures has encouraged
the development of alternative computing paradigms. One such paradigm is flow-based in …

In-memory computing is an emerging computing paradigm to breakthrough the von-
Neumann bottleneck. The SRAM based in-memory computing (SRAM-IMC) attracts great …

Processing in-memory has the potential to accelerate high-data-rate applications beyond
the limits of modern hardware. Flow-based computing is a computing paradigm for …

In-memory computing using nanoscale crossbar arrays is a promising solution strategy to
overcome the limitations of the von Neumann architecture. Flow-based computing is an …

We introduce a framework to design in-memory decision tree machine-learning (ML) circuits
using memristor crossbars. Decision trees (DTs) offer many advantages over neural …