Graph analytics is the basis for many modern applications, eg, machine learning and
streaming data problems. With an unprecedented increase in data size of many emerging …

Ultra-dense non-volatile racetrack memories (RTMs) have been investigated at various
levels in the memory hierarchy for improved performance and reduced energy consumption …

Hyperdimensional computing (HDC) is an emerging computational framework inspired by
the brain that operates on vectors with thousands of dimensions to emulate cognition. Unlike …

Edge computing is a popular paradigm for accelerating light-to medium-weight machine
learning algorithms initiated from mobile devices without requiring the long communication …

The rise of data-intensive applications exposed the limitations of conventional processor-
centric von-Neumann architectures that struggle to meet the off-chip memory bandwidth …

Convolutional neural networks (CNN) have become a ubiquitous algorithm with growing
applications in mobile and edge settings. We describe a compute-in-memory (CIM) …

Domain-Wall Memory (DWM) structures typically bundle nanowires shifted together for
parallel access. Ironically, this organization does not allow the natural shifting of DWM to …

DESIGN AND CODE OPTIMIZATION FOR SYSTEMS WITH NEXT-GENERATION RACETRACK
MEMORIES Dissertation for the purpose of obtaining the d Page 1 DESIGN AND CODE …

In recent years, more and more proposals have been explored to replace conventional
SRAM, DRAM, and Flash with novel memories. Moreover, the performance gap between …