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Mendeley readers
Attention Score in Context
| Title |
ANNarchy: a code generation approach to neural simulations on parallel hardware
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, July 2015
|
| DOI | 10.3389/fninf.2015.00019 |
| Pubmed ID | |
| Authors |
Julien Vitay, Helge Ü. Dinkelbach, Fred H. Hamker |
| Abstract |
Many modern neural simulators focus on the simulation of networks of spiking neurons on parallel hardware. Another important framework in computational neuroscience, rate-coded neural networks, is mostly difficult or impossible to implement using these simulators. We present here the ANNarchy (Artificial Neural Networks architect) neural simulator, which allows to easily define and simulate rate-coded and spiking networks, as well as combinations of both. The interface in Python has been designed to be close to the PyNN interface, while the definition of neuron and synapse models can be specified using an equation-oriented mathematical description similar to the Brian neural simulator. This information is used to generate C++ code that will efficiently perform the simulation on the chosen parallel hardware (multi-core system or graphical processing unit). Several numerical methods are available to transform ordinary differential equations into an efficient C++code. We compare the parallel performance of the simulator to existing solutions. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 3% |
| Unknown | 83 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 23% |
| Student > Master | 18 | 21% |
| Researcher | 14 | 16% |
| Student > Bachelor | 4 | 5% |
| Student > Doctoral Student | 3 | 3% |
| Other | 10 | 12% |
| Unknown | 17 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 26 | 30% |
| Engineering | 14 | 16% |
| Neuroscience | 9 | 10% |
| Agricultural and Biological Sciences | 7 | 8% |
| Mathematics | 2 | 2% |
| Other | 6 | 7% |
| Unknown | 22 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 22. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 August 2023.
All research outputs
#1,613,196
of 24,257,963 outputs
Outputs from Frontiers in Neuroinformatics
#42
of 795 outputs
Outputs of similar age
#21,028
of 267,156 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#2
of 8 outputs
Altmetric has tracked 24,257,963 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 795 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,156 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.