Various near-data processing (NDP) designs have been proposed to alleviate the memory
wall challenge for data-intensive applications. Among them, near-DRAM-bank NDP …

Memory disaggregation is a promising direction to mitigate memory contention in
datacenters. To make memory disaggregation practical, prior efforts expose remote memory …

A growth in data volume, combined with increasing demand for real-time analysis (using the
most recent data), has resulted in the emergence of database systems that concurrently …

There has been a lot of recent interest in applying machine learning (ML) to the design of
systems, which purports to aid human experts in extracting new insights leading to better …

The explosion of data availability and the demand for faster data analysis have led to the
emergence of applications exhibiting large memory footprint and low data reuse rate. These …

The network on-chip (NoC) is a critical resource shared by various on-chip components. An
efficient NoC arbitration policy is crucial in providing global fairness and improving system …

Demand for server memory capacity and performance is rapidly increasing due to
expanding working set sizes of modern applications, such as big data analytics, inmemory …

The data access bottleneck in memory-intensive applications has motivated various
architectural innovations in the main memory system, with Near-Data Processing (NDP) and …

In multi-GPU and multi-chiplet GPU systems exhibiting NUMA behavior, information about
addresses accessed by threads is crucial for various optimizations such as data/thread co …

A growth in data volume, combined with increasing demand for real-time analysis (using the
most recent data), has resulted in the emergence of database systems that concurrently …