Memory devices and applications for in-memory computing
Traditional von Neumann computing systems involve separate processing and memory
units. However, data movement is costly in terms of time and energy and this problem is …
units. However, data movement is costly in terms of time and energy and this problem is …
A survey of ReRAM-based architectures for processing-in-memory and neural networks
S Mittal - Machine learning and knowledge extraction, 2018 - mdpi.com
As data movement operations and power-budget become key bottlenecks in the design of
computing systems, the interest in unconventional approaches such as processing-in …
computing systems, the interest in unconventional approaches such as processing-in …
A modern primer on processing in memory
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 …
design choice goes directly against at least three key trends in computing that cause …
Ambit: In-memory accelerator for bulk bitwise operations using commodity DRAM technology
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 …
bit vectors. In fact, recent works design techniques that exploit fast bulk bitwise operations to …
Prime: A novel processing-in-memory architecture for neural network computation in reram-based main memory
Processing-in-memory (PIM) is a promising solution to address the" memory wall"
challenges for future computer systems. Prior proposed PIM architectures put additional …
challenges for future computer systems. Prior proposed PIM architectures put additional …
[HTML][HTML] Analog architectures for neural network acceleration based on non-volatile memory
Analog hardware accelerators, which perform computation within a dense memory array,
have the potential to overcome the major bottlenecks faced by digital hardware for data …
have the potential to overcome the major bottlenecks faced by digital hardware for data …
Benchmarking a new paradigm: Experimental analysis and characterization of a real processing-in-memory system
Many modern workloads, such as neural networks, databases, and graph processing, are
fundamentally memory-bound. For such workloads, the data movement between main …
fundamentally memory-bound. For such workloads, the data movement between main …
Drisa: A dram-based reconfigurable in-situ accelerator
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 …
architecture is creating the" memory wall" problem. To bridge the gap, two approaches, the …
SIMDRAM: A framework for bit-serial SIMD processing using DRAM
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 …
operations, addition). However, in order to enable full adoption of processing-using-DRAM …
Processing data where it makes sense: Enabling in-memory computation
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 …
choice goes directly against at least three key trends in systems that cause performance …