• https://developers.google.com/search/docs/appearance/structured-data/event
• https://developers.google.com/search/docs/appearance/structured-data/logo
• https://developers.google.com/search/docs/appearance/structured-data/article
• https://developers.google.com/search/docs/appearance/structured-data/learning-video (maybe)

Ideally this is rendered directly from our github repository, so that people can open pull requests to update info. I'm including a nice summary table about hardware from http://sandamirskaya.eu/resources/SandamirskayaEtAl2022_SciRob.pdf

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for Tianjic is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for Akida is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

When I run npm run dev, which calls hugo server under the hood, everything works locally. That is, as long as I have Hugo v0.118.2 installed (as is specified in the Github actions build).
I do get a warning saying

WARN  .File.Dir on zero object. Wrap it in if or with: {{ with .File }}{{ .Dir }}{{ end }}

but otherwise it builds.

Yesterday, a new stable version of Hugo was released, and my Snap package automatically updated to v0.123.2. When I try to build the website, I get the following error:

> [email protected] dev
> hugo serve --buildFuture

Watching for changes in /home/gregorlenz/Development/open-neuromorphic.github.io/{assets,content,data,hugo_stats.json,i18n,package.json,postcss.config.js,static,tailwind.config.js,themes}
Watching for config changes in /home/gregorlenz/Development/open-neuromorphic.github.io/hugo.toml, /home/gregorlenz/Development/open-neuromorphic.github.io/config/_default, /home/gregorlenz/Development/open-neuromorphic.github.io/go.mod
Start building sites … 
hugo v0.123.2-929b91fe75cb0d041f22b4707700dfc117115ad4+extended linux/amd64 BuildDate=2024-02-22T15:27:15Z VendorInfo=snap:0.123.2

Built in 3655 ms
Error: error building site: render: failed to render pages: render of "404" failed: "/home/gregorlenz/Development/open-neuromorphic.github.io/themes/hugoplate/layouts/_default/baseof.html:9:7": execute of template failed: template: 404.html:9:7: executing "404.html" – File is nil; wrap it in if or with: {{ with partial "essentials/head.html" .>: error calling partial: "/home/gregorlenz/Development/open-neuromorphic.github.io/themes/hugoplate/layouts/partials/essentials/head.html:6:30": execute of template failed: template: partials/essentials/head.html:6:30: executing "partials/essentials/head.html" at <.File }}{{ .Dir }}{{ end }}

It seems to me that the warning generated with v0.118 now causes the build to break with v0.123. It would be great if the build worked with the latest stable Hugo version, which is v0.123. @neural-loop do you think you could take a look at this please?

Icons and links to Discord, LinkedIn and GitHub.

It would be great to showcase the fact that we're several hundred people already. This would ideally show up somewhere on the front page of open-neuromorphic.org.
Ideally that number is fetched dynamically, but if that's not possible, a '700+' text would also do for the moment.

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for ODIN is located here and is missing most info.

Following info should be added in the header:

• applications. What applications can the chip be used for.
• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• power. How much power does the chip typically burn.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?
• release_date and release_year.
• summary. Provide a summary that's roughly 300 characters long.

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for Xylo is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

To match the ones on the website

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for ROLLS is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

After the initial draft of the hardware article, I added additional parameters, for example for the number of bits for activations or weights. Those should be displayed in the article

• Verify Domain in github and add to various repositories -> https://open-neuromorphic.org/
• Link to socials at https://github.com/open-neuromorphic
  https://open-neuromorphic.org/
  https://discord.gg/C9bzWgNmqk
  https://www.linkedin.com/groups/9267873
  https://www.youtube.com/@openneuromorphic
• Optimize title & description at https://open-neuromorphic.org/
  (Suggestion) Discover the Future of Computing with Open Neuromorphic: Your Hub for Open-Source Projects in Neuromorphic Research
• Include '- Open Neuromorphic' in page titles example: https://open-neuromorphic.org/p/snn-library-benchmarks/

Strategy wise, I would recommend targeting some keywords, 'neuromorphic computing', 'neuromorphic ai'. A good way to do this is through data architecture, possibly via the tagging mechanism.

• Data structure like https://open-neuromorphic.org/neuromorphic-computing/articles faqs etc
• Left column of site navigation should feature links that lead to these content sections.

I am open to help & collaboration! These are some small steps that can help keep things trending in the right direction. There is a ton more that is possible.

I added Open Neuromorphic to https://aimodels.org/ai-community-directory . I've recently started an article on Neuromorphic computing: https://aimodels.org/neuromorphic-computing and developing this page and subject further is what brought me here. :)

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for Neurogrid is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

This blog post is meant to introduce a newbie to event based vision. I can see Tonic documentation being of help for this but I would like to add some details about the sensor itself too. There is also the blog series from iniVation CEO, there is this really nice survey to take inspiration from...

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for ReckOn is located here and is missing most info.

Following info should be added in the header:

• applications. What applications can the chip be used for.
• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• power. How much power does the chip typically burn.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?
• release_date and release_year.
• summary. Provide a summary that's roughly 300 characters long.

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware. To build the website locally, follow these instructions.

What to improve

The current entry for DynapSE 2 is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

Here's the event data.

Cover image

Title

C-DNN and C-Transformer: mixing ANNs and SNNs and getting the best of both worlds

Date

4th of May, 11AM-12:15PM CEST.

Abstract

Recently, Deep Neural Networks (DNNs) and Spiking Neural Networks (SNNs) have been widely used in AI applications, with each network having its own advantages. Therefore, we propose a new Complementary DNN (C-DNN) that combines the benefits of both SNNs and DNNs. The human brain consumes more energy when there is a lot to think about and less energy when there is less to think about. Similarly, SNNs, which mimic the brain, consume a lot of power when the magnitude of the input value is large and consume less power when the magnitude of the input value is small. C-DNN utilizes these characteristics to achieve low power consumption by allocating only small inputs to the SNN and large inputs to the DNN for processing. We have developed a C-DNN processor that effectively processes this, achieving 51.3% higher energy efficiency compared to the previous state-of-the-art processor. Subsequently, we have applied C-DNN not only to image classification but also to other applications, and have developed the C-Transformer, which applies this technique to a Large Language Model (LLM). As a result, we demonstrate that the energy consumed in LLM can be reduced by 30% to 72% using the C-DNN technique, compared to the previous state-of-the-art processor. In this talk, we will introduce the processor developed for C-DNN and C-Transformer, and discuss how neuromorphic computing can be used in actual applications in the future.

Bio

Sangyeob Kim (Student Member, IEEE) received the B.S., M.S. and Ph.D. degrees from the School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea, in 2018, 2020 and 2023, respectively. He is currently a Post-Doctoral Associate with the KAIST. His current research interests include energy-efficient system-on-chip design, especially focused on deep neural network accelerators, neuromorphic hardware, and computing-in-memory accelerators.

I will upload the photo of Sangyeob myself.

Introductory article on analog design of SNNs. If you wish to collaborate, comment on this issue. Currently assigned to @stevenabreu7 and @snarayan19

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware. To build the website locally, follow these instructions.

What to improve

The current entry for Loihi 1 is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware. To build the website locally, follow these instructions.

What to improve

The current entry for Brainscales 2 is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware. To build the website locally, follow these instructions.

What to improve

The current entry for DynapCNN is located here and would benefit from more detailed info. Please note that this chip, when combined with an event camera, is called Speck. The processing backend is the same however.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

We should clarify better how one can get involved:

• hosting their code on the organization repository.
• writing a blog article on some neuromorphic subject.
• contributing to open source projects involved with ONM, even if these are not hosted here.
• what else?

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for TrueNorth is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware. To build the website locally, follow these instructions.

What to improve

The current entry for Loihi 2 is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).

Write article on Expelliarmus with benchmarks and so on once @stevenabreu7 has run those on his Metavision machine.

Copy README from open-neuromorphic repo to the website (and format it nicely).

The website

The code for the live version of open-neuromorphic.org is hosted on the main branch at our GitHub repository. The site contains educational content on neuromorphic software libraries and hardware.

What to improve

The current entry for SpiNNaker 2 is located here and would benefit from more detailed info.

Following info should be checked or added in the header:

• release_date. When was the chip released? That means made available for customers to buy/access for industry chips, or the first results published for research chips.
• weight_bits. What are the possible bit resolutions of weights?
• activation_bits. What are the possible bit resolutions of activations?
• neurons. How many neurons fit on one chip? If it depends on the neuron model, provide an example for the most common neuron model. This field can take a (short) sentence if need be.
• synapses. How many synapses for a given neuron config? This field can take a (short) sentence if need be.
• on_chip_learning. Does the chip support on chip learning?

Following info should be added in the text body.

• What makes the chip stand out in neuromorphic computing?
• Practical applications of the chip
• What's the workflow to develop and deploy models for the chip? What are the software toolchains involved?
• Availability to purchase / access
• Scalibility - Can I stack this chip easily?
• Form factors. Are there boards available that can go on small drones? Robots? Data centers?

Following things would be nice to have:

• Links to documents / data sheets that describe the chip.
• Technology and fabrication details.
• Future development roadmap.
• List of publications that show results on the hardware, including date, title, authors and journal/conference.

Feel free to add any relevant information you think would be beneficial. If you have questions or need clarification on any topic, please open a PR and ask. We encourage both seasoned contributors and newcomers to participate. Our team is ready to assist you in this process, both on Github or on Discord. Please keep the discussions public at all times.

Workflow

1. Comment on this issue to express interest, so that our team can assign it to you. That'll let other people know that you're working on it.
2. Fork this repository
3. Make the changes in your fork and commit them on a new branch.
4. Follow the instructions to build the website locally and check that the new page renders nicely.
5. Create a pull request from the new branch in your fork into main in the original repository.

Writing style

Our aim is to create a central hub for educational content on neuromorphic computing. The content should be formally written, accessible to the public, and include references or images where appropriate. Feel free to include yourself in an authors statement at the bottom of the page. Please avoid overly general comments (as sometimes generated by ChatGPT).