Last modified by abonard on 2025/04/10 15:12
From version 10.1
edited by abonard
on 2025/04/10 15:03
Change comment: There is no comment for this version
To version 18.1
edited by abonard
on 2025/04/10 15:12
Change comment: There is no comment for this version

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2 2  
3 3  * ((( ==== **[[Beginner >>||anchor = "HBeginner-1"]]** ==== )))
4 4  
5 -* ((( ==== **[[Intermediate >>||anchor = "HIntermediate-1"]]** ==== )))
6 -
7 7  === **Beginner** ===
8 8  
9 9  === [[HBP Focus Area - Neuromorphic computing>>https://www.youtube.com/watch?v=VgMK5WRRTH0||rel=" noopener noreferrer" target="_blank"]] ===
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22 22  {{html}}
23 23  <iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/V2DAzIY5iOs" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
24 24  {{/html}}
25 -=== [[Hands on tutorial BrainScaleS 2 Structured Neurons>>https://www.youtube.com/watch?v=907zRDofz7Y&list=PLJ506hQ4g3TiJnL5_UFtRgDFcEV9QNdd1&index=30||rel=" noopener noreferrer" target="_blank"]] ===
26 26  
27 -**Level**: beginner(%%) **Type**: video tutorial
28 -
29 -Having completed this tutorial you will know how to use BrainScaleS 2 for connectingt neuron circuits to form multi-compartmental neuron models.
30 -{{html}}
31 -<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/907zRDofz7Y&list=PLJ506hQ4g3TiJnL5_UFtRgDFcEV9QNdd1&index=30" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
32 -{{/html}}
33 -=== [[An Introduction into Accelerated Analog Neuromorphic Computing with BrainScaleS>>https://www.youtube.com/watch?v=jCN6zYB-DHQ||rel=" noopener noreferrer" target="_blank"]] ===
34 -
35 -**Level**: beginner(%%) **Type**: video tutorial
36 -
37 -Brain-inspired Computing - An Introduction into Accelerated Analog Neuromorphic Computing with BrainScaleS.
38 -{{html}}
39 -<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/jCN6zYB-DHQ" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
40 -{{/html}}
41 -=== [[Demonstrating BrainScaleS 2 Inter-Chip Pulse Communication using Extoll>>https://www.youtube.com/watch?v=Nfgr6XV8ORA&list=PLJ506hQ4g3TiJnL5_UFtRgDFcEV9QNdd1&index=8||rel=" noopener noreferrer" target="_blank"]] ===
42 -
43 -**Level**: beginner(%%) **Type**: video tutorial
44 -
45 -In this tutorial you will get a brief overview on how to use the EXTOLL network in BrainScaleS and later get a live demonstration of this setup.
46 -{{html}}
47 -<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/Nfgr6XV8ORA&list=PLJ506hQ4g3TiJnL5_UFtRgDFcEV9QNdd1&index=8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
48 -{{/html}}
49 -=== [[Neuromorphic Computing in EBRAINS (brief introduction to SpiNNaker and BrainScaleS)>>https://www.youtube.com/watch?v=zW1UfIccMtY||rel=" noopener noreferrer" target="_blank"]] ===
50 -
51 -**Level**: beginner(%%) **Type**: video presentation
52 -
53 -Steve Furber giving a brief overview of the neuromorphic compute systems at Heidelberg. Touching upon what is neuromorphic computing and how we can use it.
54 -{{html}}
55 -<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/zW1UfIccMtY" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
56 -{{/html}}
57 -=== [[BrainScaleS hands on - introduction>>https://flagship.kip.uni-heidelberg.de/jss/HBPm?mI=242&publicVideoID=9246||rel=" noopener noreferrer" target="_blank"]] ===
58 -
59 -**Level**: beginner(%%) **Type**: video tutorial
60 -
61 -Introduction to the BrainScales Hardware and System and how to execute simple experiments.
62 -=== [[Hands on tutorial BrainScaleS 2 introduction>>https://www.youtube.com/watch?v=UM1mhq1bdY4&list=PLJ506hQ4g3TiJnL5_UFtRgDFcEV9QNdd1&index=28||rel=" noopener noreferrer" target="_blank"]] ===
63 -
64 -**Level**: beginner(%%) **Type**: video tutorial
65 -
66 -After giving a general overview on BrainScaleS-2 and its schematics, we will ttalk about how to handle the topics of time flows, layers, neurons and PyTorch in the system.
67 -{{html}}
68 -<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/UM1mhq1bdY4&list=PLJ506hQ4g3TiJnL5_UFtRgDFcEV9QNdd1&index=28" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
69 -{{/html}}
70 -=== **Intermediate** ===
71 -
72 -=== [[BrainScaleS via EBRAINS - from point to structured neurons>>https://www.youtube.com/watch?v=rhyHcAIdkz8||rel=" noopener noreferrer" target="_blank"]] ===
73 -
74 -**Level**: intermediate(%%) **Type**: video tutorial
75 -
76 -After a brief introduction we will look into working with single point neurons and after get to structured neurons.
77 -{{html}}
78 -<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/rhyHcAIdkz8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
79 -{{/html}}
80 -=== [[BrainScaleS – Plasticity and structured neurons>>https://flagship.kip.uni-heidelberg.de/jss/HBPm?mI=242&publicVideoID=9248||rel=" noopener noreferrer" target="_blank"]] ===
81 -
82 -**Level**: intermediate(%%) **Type**: video tutorial
83 -
84 -In this tutorial we will look into BrainScaleS-2 embedded general-purpose processors, called PPUs (Plasticity Processing Units). We want to show how the PPUs can be used to rate-code an image in the activity of neurons. Later on, we will define the network topology using the pyNN interface and then define the plasticity rule in C++.
85 -