JUNE 18–22, 2017
FRANKFURT AM MAIN, GERMANY

Presentation Details
 
Name: (RP09) From Processing-in-Memory to Processing-in-Storage
 
Time: Tuesday, June 20, 2017
08:35 am - 09:45 am
 
Room:   Substanz 1+2  
 
Breaks:07:30 am - 10:00 am Welcome Coffee
 
Presenter:   Roman Kaplan, Technion
 
Abstract:  
A novel processing-in-storage (PRinS) architecture based on Resistive CAM (ReCAM) is described and proposed. The ReCAM is a massively parallel in-storage accelerator, scalable to tera- and peta-bytes in size. We implemented several algorithms to demonstrate the performance benefits of ReCAM. First is the Smith-Waterman sequence alignment algorithm, which ReCAM can perform in linear time and outperform a cluster of GPUs on the same task. Second is K-means, a key machine learning clustering algorithm in multiple applications, used to group data samples to clusters by similarity. Here we show how ReCAM can perform on a big data dataset and outperform other implementations. Third is online deduplication, a technique for data size reduction in storage systems. We show that a ReCAM-based storage system can provide performance improvements and reduce overhead compared with state-of-the-art storage appliances.

Author: 
Roman Kaplan, Technion

  
 
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