A memory efficient implementation scheme of Gauss error function in a Laguerre-Volterra network for neuroprosthetic devices

2017 ◽  
Vol 88 (4) ◽  
pp. 044301 ◽  
Author(s):  
Will X. Y. Li ◽  
Ke Cui ◽  
Wei Zhang
Keyword(s):  
Error Function ◽  
Efficient Implementation ◽  
Implementation Scheme ◽  
Neuroprosthetic Devices ◽  
Memory Efficient

7.2: A Memory-Efficient Implementation of Video Window Detection for a Digital Display Controller

2002 ◽  
Vol 33 (1) ◽  
pp. 64 ◽  
Author(s):  
Hemant Mallapur ◽  
N. Sakuntala ◽  
Hari Nair ◽  
Muthukrishnan Chinnasamy ◽  
Arun Johary
Keyword(s):  
Efficient Implementation ◽  
Digital Display ◽  
Memory Efficient

scholarly journals A fast and memory-efficient implementation of the transfer bootstrap

2019 ◽  
Vol 36 (7) ◽  
pp. 2280-2281 ◽  
Author(s):  
Sarah Lutteropp ◽  
Alexey M Kozlov ◽  
Alexandros Stamatakis
Keyword(s):  
General Public ◽  
Efficient Implementation ◽  
Supplementary Information ◽  
Bootstrap Support ◽  
Supplementary Data ◽  
Original Algorithm ◽  
Parallel Version ◽  
Branch Support ◽  
General Public License ◽  
Memory Efficient

Abstract Motivation Recently, Lemoine et al. suggested the transfer bootstrap expectation (TBE) branch support metric as an alternative to classical phylogenetic bootstrap support for taxon-rich datasets. However, the original TBE implementation in the booster tool is compute- and memory-intensive. Results We developed a fast and memory-efficient TBE implementation. We improve upon the original algorithm by Lemoine et al. via several algorithmic and technical optimizations. On empirical as well as on random tree sets with varying taxon counts, our implementation is up to 480 times faster than booster. Furthermore, it only requires memory that is linear in the number of taxa, which leads to 10× to 40× memory savings compared with booster. Availability and implementation Our implementation has been partially integrated into pll-modules and RAxML-NG and is available under the GNU Affero General Public License v3.0 at https://github.com/ddarriba/pll-modules and https://github.com/amkozlov/raxml-ng. The parallel version that also computes additional TBE-related statistics is available at: https://github.com/lutteropp/raxml-ng/tree/tbe. Supplementary information Supplementary data are available at Bioinformatics online.

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