Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

Computing in memory (CIM) could be used to overcome the von Neumann bottleneck and to
provide sustainable improvements in computing throughput and energy efficiency …

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 important applications trigger bulk bitwise operations, ie, bitwise operations on large
bit vectors. In fact, recent works design techniques that exploit fast bulk bitwise operations to …

Processing-in-memory (PIM) is a promising solution to address the" memory wall"
challenges for future computer systems. Prior proposed PIM architectures put additional …

The high accuracy of deep neural networks (NNs) has led to the development of NN
accelerators that improve performance by two orders of magnitude. However, scaling these …

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

Data movement between the processing units and the memory in traditional von Neumann
architecture is creating the" memory wall" problem. To bridge the gap, two approaches, the …

After a plethora of high-profile RowHammer attacks, CPU and DRAM vendors scrambled to
deliver what was meant to be the definitive hardware solution against the RowHammer …

Processing-using-DRAM has been proposed for a limited set of basic operations (ie, logic
operations, addition). However, in order to enable full adoption of processing-using-DRAM …