Summary

• Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

...	...	@@ -20,41 +20,4 @@
20	20	{{html}}
21	21	<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/-UjtFAjinFQ&list=PLJ506hQ4g3TiJnL5_UFtRgDFcEV9QNdd1&index=10" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
22	22	{{/html}}
23		-=== [[Tools and services offered by EBRAINS computing services and Neuromorphic Computing - The SpiNNaker platform>>https://www.youtube.com/watch?v=rGaxjhca_Eg||rel=" noopener noreferrer" target="_blank"]] ===
24	24
25		-**Level**: beginner(%%) **Type**: video tutorial
26		-
27		-In this tutorial you will get an introduction to SpiNNaker, learn about its application, computer architecture and the SpiNNaker chip. Furthermore we will look into the SpiNNaker machine, how to create events and delays, split synapse models and neural networks and load examples. We will also be showing how to use and access the virtual environment.
28		-{{html}}
29		-<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/rGaxjhca_Eg" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
30		-{{/html}}
31		-=== [[Introduction to the SpiNNaker neuromorphic compute systems>>https://www.youtube.com/watch?v=ej03_r_-Rno||rel=" noopener noreferrer" target="_blank"]] ===
32		-
33		-**Level**: beginner(%%) **Type**: video presentation
34		-
35		-In this high-level presentation Steve Furber will give an introduction to the SpiNNaker neuromorphic compute system, touching upon its development and what it can do and its application.
36		-{{html}}
37		-<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/ej03_r_-Rno" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
38		-{{/html}}
39		-=== [[Using the SpiNNaker neuromorphic compute system interactively>>https://www.youtube.com/watch?v=xtsaH40MrLQ||rel=" noopener noreferrer" target="_blank"]] ===
40		-
41		-**Level**: beginner(%%) **Type**: video tutorial
42		-
43		-This tutorial showcases how to run a version of a solution, how to allocate the SpiNNaker board and finally how to use the Neural Robotics Environment.
44		-{{html}}
45		-<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/xtsaH40MrLQ" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
46		-{{/html}}
47		-=== [[Neuromorphic Computing in EBRAINS (brief introduction to SpiNNaker and BrainScaleS)>>https://www.youtube.com/watch?v=zW1UfIccMtY||rel=" noopener noreferrer" target="_blank"]] ===
48		-
49		-**Level**: beginner(%%) **Type**: video presentation
50		-
51		-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.
52		-{{html}}
53		-<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>
54		-{{/html}}
55		-=== [[Accessing SpiNNaker>>https://flagship.kip.uni-heidelberg.de/jss/HBPm?mI=242&publicVideoID=9260||rel=" noopener noreferrer" target="_blank"]] ===
56		-
57		-**Level**: beginner(%%) **Type**: video tutorial
58		-
59		-This tutorial teaches you how to access SpiNNaker, specifically through Jupyter. It guides you through the SpiNNaker interface and its properties. The lecturer briefly touches on Spiking Neural Networks and what can be simulated with SpiNNaker. The tutorial further explains PyNN, how it relates to SpiNNaker and what the most useful parts of PyNN are.
60		-