scholarly journals Language and Hardware Acceleration Backend for Graph Processing

2018 ◽  
pp. 71-88
Author(s):  
Andrey Mokhov ◽  
Alessandro de Gennaro ◽  
Ghaith Tarawneh ◽  
Jonny Wray ◽  
Georgy Lukyanov ◽  
...  
Keyword(s):  
Hardware Acceleration ◽  
Graph Processing

scholarly journals Language and hardware acceleration backend for graph processing

2017 ◽  
Author(s):  
Andrey Mokhov ◽  
Alessandro de Gennaro ◽  
Ghaith Tarawneh ◽  
Jonny Wray ◽  
Georgy Lukyanov ◽  
...  
Keyword(s):  
Hardware Acceleration ◽  
Graph Processing

Hardware Acceleration of Bilateral Filters

2013 ◽  
Vol 133 (2) ◽  
pp. 132-138
Author(s):  
Shuhei Isa ◽  
Chikatoshi Yamada ◽  
Yasunori Nagata
Keyword(s):  
Hardware Acceleration ◽  
Bilateral Filters

The real-time computing of the Stirling formula based on hardware acceleration

2013 ◽  
Author(s):  
Jiyang Yu ◽  
Dan Huang ◽  
Siyang Zhao ◽  
Nan Pei ◽  
Huixia Cheng ◽  
...  
Keyword(s):  
Real Time ◽  
Hardware Acceleration ◽  
Stirling Formula ◽  
The Real ◽  
Real Time Computing

Design and implementation of matrix hardware acceleration based on FPGA/Nios-Ⅱ

2011 ◽  
Vol 25 (4) ◽  
pp. 377-383 ◽  
Author(s):  
Fang Xu ◽  
Yi Xi ◽  
Hong Chen ◽  
Weiwei Jin
Keyword(s):  
Hardware Acceleration ◽  
Design And Implementation

Design and Implementation of Low Energy Wireless Network Nodes based on Hardware Compression Acceleration

2019 ◽  
Vol 12 ◽  
Author(s):  
Hui Yang ◽  
Anand Nayyar
Keyword(s):  
Energy Consumption ◽  
Data Compression ◽  
Energy Saving ◽  
Optimization Design ◽  
Hardware Acceleration ◽  
Transmission Efficiency ◽  
General Purpose ◽  
Storage Space ◽  
General Purpose Processor ◽  
Compression Time

: In the fast development of information, the information data is increasing in geometric multiples, and the speed of information transmission and storage space are required to be higher. In order to reduce the use of storage space and further improve the transmission efficiency of data, data need to be compressed. processing. In the process of data compression, it is very important to ensure the lossless nature of data, and lossless data compression algorithms appear. The gradual optimization design of the algorithm can often achieve the energy-saving optimization of data compression. Similarly, The effect of energy saving can also be obtained by improving the hardware structure of node. In this paper, a new structure is designed for sensor node, which adopts hardware acceleration, and the data compression module is separated from the node microprocessor.On the basis of the ASIC design of the algorithm, by introducing hardware acceleration, the energy consumption of the compressed data was successfully reduced, and the proportion of energy consumption and compression time saved by the general-purpose processor was as high as 98.4 % and 95.8 %, respectively. It greatly reduces the compression time and energy consumption.

Accelerating Genomic Data Analytics with Composable Hardware Acceleration Framework

IEEE Micro ◽  
2021 ◽  
pp. 1-1
Author(s):  
Tae Jun Ham ◽  
David Bruns-Smith ◽  
Brendan Sweeney ◽  
Yejin Lee ◽  
Seong Hoon Seo ◽  
...  
Keyword(s):  
Data Analytics ◽  
Genomic Data ◽  
Hardware Acceleration

DepGraph: A Dependency-Driven Accelerator for Efficient Iterative Graph Processing

2021 ◽  
Author(s):  
Yu Zhang ◽  
Xiaofei Liao ◽  
Hai Jin ◽  
Ligang He ◽  
Bingsheng He ◽  
...  
Keyword(s):  
Graph Processing
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