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In-memory processing

Known as: In-memory computing 
In computer science, in-memory processing is a developing technology for processing of data stored in an in-memory database. Older systems have been… 
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Related topics

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Column-oriented DBMSComputer scienceComputer securityData compression

Broader (1)

Computer memory

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2020
2020
SIMBA: A Skyrmionic In-Memory Binary Neural Network Accelerator
Magnetic skyrmions are emerging as potential candidates for next-generation non-volatile memories. In this article, we propose an… 
2018
2018
Towards fault tolerance optimization based on checkpoints of in-memory framework spark
Performance optimization especially for fault tolerance optimization has been a significant aspect for in-memory computing… 
2017
2017
Automated synthesis of compact multiplier circuits for in-memory computing using ROBDDs
With Moore's law approaching physical limitations of transistor size, researchers have started exploring unconventional ways for… 
2017
2017
Modeling, Optimization, and Operation of Large-Scale Air Traffic Flow Management on Spark
The nationwide air traffic flow management problem often encounters computational difficulty because it is generally modeled as… 
2017
2017
Weather data analysis using spark — An in-memory computing framework
Weather forecasting is a motivational challenge in human civilization. There is a shift in scientific focus towards solving this… 
2017
2017
A Multi-Bit Neuromorphic Weight Cell Using Ferroelectric FETs, suitable for SoC Integration
A multi-bit digital weight cell for high-performance, inference-only non-GPU-like neuromorphic accelerators is presented. The… 
2015
2015
A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data
Big data is a big business, and effective modeling of this data is key. This paper provides a comprehensive multidimensional… 
2015
2015
In-memory adder functionality in 1S1R arrays
Memristive devices enable non-volatile data storage and in-memory computing capabilities. By using stateful logic approaches… 
2015
2015
A time-efficient connected densest subgraph discovery algorithm for big data
In this paper, we propose a time-efficient and exact algorithm for the problem of discovering the densest subgraph in big data… 
2012
2012
Implementation of Spark Cluster Technique with SCALA
Spark is an open source cluster computing system that aims to make data analytics fast — both fast to run and fast to write. To… 
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