Data movement between the CPU and main memory is a first-order obstacle against improv
ing performance, scalability, and energy efficiency in modern systems. Computer systems …

Processing-using-DRAM (PUD) is a processing-in-memory (PIM) approach that uses a
DRAM array's massive internal parallelism to execute very-wide (eg, 16,384-262,144-bit …

Memory-centric computing aims to enable computation capability in and near all places
where data is generated and stored. As such, it can greatly reduce the large negative …

In order to scale, future systems will need to dramatically reduce data movement. Data
movement is expensive in current designs because (i) traditional memory hierarchies force …

Several manufacturers have already started to commercialize near-bank Processing-In-
Memory (PIM) architectures, after decades of research efforts. Near-bank PIM architectures …

In-memory computing with large last-level caches is promising to dramatically alleviate data
movement bottlenecks and expose massive bitline-level parallelization opportunities …

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 …

Data movement and communication have become the primary bottlenecks in large multicore
systems. The near-data computing paradigm provides a solution: move computation to …

This book provides a structured introduction of the key concepts and techniques that enable
in-/near-memory computing. For decades, processing-in-memory or near-memory …

As multicore systems continue to grow in scale and on-chip memory capacity, the on-chip
network bandwidth and latency become problematic bottlenecks. Because of this …