Motivation Sequence alignment is a memory bound computation whose performance in
modern systems is limited by the memory bandwidth bottleneck. Processing-in-memory …

To understand and improve DRAM performance, reliability, security, and energy efficiency,
prior works study characteristics of commodity DRAM chips. Unfortunately, state-of-the-art …

Content-addressable memory (CAM) has been part of the memory market for more than five
decades. CAM can carry out a single clock cycle lookup based on the content rather than an …

Training machine learning (ML) algorithms is a computationally intensive process, which is
frequently memory-bound due to repeatedly accessing large training datasets. As a result …

Processing-in-memory (PIM) promises to alleviate the data movement bottleneck in modern
computing systems. However, current real-world PIM systems have the inherent …

Stencil computations are commonly used in a wide variety of scientific applications, ranging
from large-scale weather prediction to solving partial differential equations. Stencil …

Generating the hash values of short subsequences, called seeds, enables quickly
identifying similarities between genomic sequences by matching seeds with a single lookup …

Near-Data Processing (NDP) has been a promising architectural paradigm to address the
memory wall challenge for data-intensive applications. Typical NDP systems based on 3D …

Data movement between memory and processors is a major bottleneck in modern
computing systems. The processing-in-memory (PIM) paradigm aims to alleviate this …

High-throughput sequencing (HTS) technologies have revolutionized the field of genomics,
enabling rapid and cost-effective genome analysis for various applications. However, the …