Graph analytics, which explores the relationships among interconnected entities, is becoming increasingly important due to its broad applicability, from machine learning to social sciences. However, due to the irregular data access patterns in graph …
Graph traversal is a core primitive for graph analytics and a basis for many higher-level graph analysis methods. However, irregularities in the structure of scale-free graphs (e.g., social network) limit our ability to analyze these important and …
This paper presents a data-centric reconfigurable architecture, namely Liquid Silicon, enabled by emerging non-volatile memory, i.e., RRAM. Compared to the heterogeneous architecture of commercial FPGAs, Liquid Silicon is inherently a homogeneous …
Recent advances in resistive random-access memory (RRAM) evoke great interests in exploring alternative architectures. One interesting work is a RRAM-based reconfigurable architecture that provides superior programmbility and blurs the boundary …
The confluence of the recent advances in technology and the ever-growing demand for large-scale data analytics created a renewed interest in a decades-old concept, processing-in-memory (PIM). PIM, in general, may cover a very wide spectrum of compute …