Today's systems are overwhelmingly designed to move data to computation. This design
choice goes directly against at least three key trends in systems that cause performance …

This retrospective paper describes the RowHammer problem in dynamic random access
memory (DRAM), which was initially introduced by Kim et al. at the ISCA 2014 Conference …

Many modern and emerging applications must process increasingly large volumes of data.
Unfortunately, prevalent computing paradigms are not designed to efficiently handle such …

The effectiveness of deep neural networks (DNN) in vision, speech, and language
processing has prompted a tremendous demand for energy-efficient high-performance DNN …

We propose a new DRAM-based true random number generator (TRNG) that leverages
DRAM cells as an entropy source. The key idea is to intentionally violate the DRAM access …

It has become increasingly difficult to understand the complex interactions between modern
applications and main memory, composed of Dynamic Random Access Memory (DRAM) …

Many applications heavily use bitwise operations on large bitvectors as part of their
computation. In existing systems, performing such bulk bitwise operations requires the …

DRAM has been the dominant technology for architecting main memory for decades. Recent
trends in multi-core system design and large-dataset applications have amplified the role of …

Experimental characterization of DRAM errors is a powerful technique for understanding
DRAM behavior and provides valuable insights for improving overall system performance …

High main memory latency continues to limit performance of modern high-performance out-
of-order cores. While DRAM latency has remained nearly the same over many generations …