Functionally-Complete Boolean Logic in Real DRAM Chips: Experimental Characterization and Analysis
Processing-using-DRAM (PuD) is an emerging paradigm that leverages the analog
operational properties of DRAM circuitry to enable massively parallel in-DRAM computation …
operational properties of DRAM circuitry to enable massively parallel in-DRAM computation …
Enabling practical processing in and near memory for data-intensive computing
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 …
which is performed only in the processor (and accelerators), and data storage/movement on …
Enabling the adoption of processing-in-memory: Challenges, mechanisms, future research directions
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 …
main memory to increasingly become a larger system bottleneck. A major reason for the …
Accelerating neural network inference with processing-in-dram: From the edge to the cloud
Neural networks (NNs) are growing in importance and complexity. An NN's performance
(and energy efficiency) can be bound either by computation or memory resources. The …
(and energy efficiency) can be bound either by computation or memory resources. The …
MIMDRAM: An End-to-End Processing-Using-DRAM System for High-Throughput, Energy-Efficient and Programmer-Transparent Multiple-Instruction Multiple-Data …
Processing-using-DRAM (PUD) is a processing-in-memory (PIM) approach that uses a
DRAM array's massive internal parallelism to execute very-wide (eg, 16,384-262,144-bit …
DRAM array's massive internal parallelism to execute very-wide (eg, 16,384-262,144-bit …
Codic: A low-cost substrate for enabling custom in-dram functionalities and optimizations
DRAM is the dominant main memory technology used in modern computing systems.
Computing systems implement a memory controller that interfaces with DRAM via DRAM …
Computing systems implement a memory controller that interfaces with DRAM via DRAM …
Compressed kNN: K-Nearest Neighbors with Data Compression
J Salvador–Meneses, Z Ruiz–Chavez… - Entropy, 2019 - mdpi.com
The k NN (k-nearest neighbors) classification algorithm is one of the most widely used non-
parametric classification methods, however it is limited due to memory consumption related …
parametric classification methods, however it is limited due to memory consumption related …
Memristive logic: A framework for evaluation and comparison
Memristors have extended their influence beyond memory to logic and in-memory
computing. Memristive logic design, the methodology of designing logic circuits using …
computing. Memristive logic design, the methodology of designing logic circuits using …
NoM: Network-on-memory for inter-bank data transfer in highly-banked memories
SHSA Rezaei, M Modarressi… - IEEE Computer …, 2020 - ieeexplore.ieee.org
Data copy is a widely-used memory operation in many programs and operating system
services. In conventional computers, data copy is often carried out by two separate read and …
services. In conventional computers, data copy is often carried out by two separate read and …
Mpim: Multi-purpose in-memory processing using configurable resistive memory
Running Internet of Things applications on general purpose processors results in a large
energy and performance overhead, due to the high cost of data movement. Processing in …
energy and performance overhead, due to the high cost of data movement. Processing in …