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 …

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 …

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 …

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 …

Many modern workloads such as neural network inference and graph processing are
fundamentally memory-bound. For such workloads, data movement between memory and …

Processing-in-memory (PIM) is rapidly rising as a viable solution for the memory wall crisis,
rebounding from its unsuccessful attempts in 1990s due to practicality concerns, which are …

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 …

With the advent of big data applications and new process technologies, Process-in-Memory
(PIM) attracts much attention in memory research as the architecture studies gradually shift …