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

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 …

Modern computing systems suffer from the dichotomy between computation on one side,
which is performed only in the processor (and accelerators), and data storage/movement on …

Poor DRAM technology scaling over the course of many years has caused DRAM-based
main memory to increasingly become a larger system bottleneck. A major reason for the …

Many modern workloads, such as neural networks, databases, and graph processing, are
fundamentally memory-bound. For such workloads, the data movement between main …

Many modern workloads, such as neural networks, databases, and graph processing, are
fundamentally memory-bound. For such workloads, the data movement between main …

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

Abstract Processing-in-memory (PIM) techniques have gained much attention from computer
architecture researchers, and significant research effort has been invested in exploring and …

A major shift from compute-centric to data-centric computing systems can be perceived, as
novel big data workloads like cognitive computing and machine learning strongly enforce …

We evaluate a new processing-in-memory (PIM) architecture from UPMEM that was built
and deployed in an off-the-shelf server. Systems designed to perform computing in or near …