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Fun to see a link here! Always happy to describe what's happening underneath w/ connecting GPUs in the browser to GPUs in the datacenter. Likewise, the connect

Fun to see a link here! Always happy to describe what's happening underneath w/ connecting GPUs in the browser to GPUs in the datacenter. Likewise, the connection between event data & graph analytics is powerful as data scales, so happy to dig into that too. Not shown there, we're piloting a 'visual playbook' investigation layer to help teams who investigate through a lot of event data. This has been especially relevant for security (SOC/IR/hunt) and anti-fraud as a team grows and needs to cover more ground. Playbooks let you finally record common multi-step multi-datasource workflows and get real visibility out of them. When your alerting flags something, running the playbook will gather & correlate that data for you, and unique to Graphistry, present it in a full visual (graph) analytics session. Think visually automating multi-step queries across Splunk + Spark + various APIs. And of course, for the advanced analysts, giant GPU-accelerated visualizations. We're actively piloting with interesting teams, so please ping info@graph....com if it may be your team's kind of thing.

lqdc13 9y ago
Is it possible to use a local GPU from the machine that has the data? Kind of like Gephi?
- lmeyerov 9y ago
  Yep! And we're working towards multi-GPU boxes!
  - lqdc13 9y ago
    Nice! Thank you
ThePhysicist 9y ago
Is it possible to visualize graphs entirely on the client side (without sending any data to your backend)? We have some very large graphs that we'd like to explore, but unfortunately it's not possible to send the data to the cloud, hence a local solution would be great. I have investigated Gephi but unfortunately the performance is quite disappointing for very large graphs.
- MurrayHill1980 9y ago
  Graphistry is impressive, but not free, and needs their server and an API key. You probably already know about graphviz sfdp (not interactive). There's been interesting recent work on distributed maxent optimization https://arxiv.org/pdf/1506.04383.pdf https://arxiv.org/pdf/1506.04383.pdf and sparse stress models https://arxiv.org/abs/1608.08909 https://arxiv.org/abs/1608.08909 (see its references as well, for example, Khoury's MARS is still available at https://github.com/marckhoury/mars https://github.com/marckhoury/mars). This problem requires a ton of algorithm engineering, a lot of messy user interface engineering, and integration into an HPC environment is a big issue, so progress in open source has not been that rapid.
  - lmeyerov 9y ago
    Those projects are pretty exciting. We accelerated FA2 and are now adding acceleration to the surrounding analytics interactions. And yep, to support an eco-system here, we've been iterating on a sustainable & scalable model (... "enterprise"). To that end, we have a variety of non-profits & scientists using our cloud tier. We want to streamline that program in the coming months: If that's you today, we'd love to help, so feel free to reach out for early access. For example, we've been excited by data science and cybersecurity schools, journalists, and scientists.
- IanCal 9y ago
  Not sure how large very large is or the performance you need but you might want to check out the fairly recently added graph support in datashader (examples: https://anaconda.org/jbednar/edge_bundling/notebook https://anaconda.org/jbednar/edge_bundling/notebook) Here's an example of the output which I then put into tiles & rendered out: https://proseandcode.co.uk/beta_gtr_viz/ https://proseandcode.co.uk/beta_gtr_viz/ I think there's 600k edges in this, all rendered. I did some of the work on the edge bundling, the split out code is here: https://gitlab.com/ianjcalvert/edgehammer https://gitlab.com/ianjcalvert/edgehammer All of this is more work than just loading it into a current program though, but it might be a useful component of what you need, hopefully a large useful part. Get in touch if I can help out.

lqdc13 9y ago

Is it possible to use a local GPU from the machine that has the data? Kind of like Gephi?

lmeyerov 9y ago
Yep! And we're working towards multi-GPU boxes!
- lqdc13 9y ago
  Nice! Thank you

ThePhysicist 9y ago

Is it possible to visualize graphs entirely on the client side (without sending any data to your backend)? We have some very large graphs that we'd like to explore, but unfortunately it's not possible to send the data to the cloud, hence a local solution would be great. I have investigated Gephi but unfortunately the performance is quite disappointing for very large graphs.

MurrayHill1980 9y ago
Graphistry is impressive, but not free, and needs their server and an API key. You probably already know about graphviz sfdp (not interactive). There's been interesting recent work on distributed maxent optimization https://arxiv.org/pdf/1506.04383.pdf https://arxiv.org/pdf/1506.04383.pdf and sparse stress models https://arxiv.org/abs/1608.08909 https://arxiv.org/abs/1608.08909 (see its references as well, for example, Khoury's MARS is still available at https://github.com/marckhoury/mars https://github.com/marckhoury/mars). This problem requires a ton of algorithm engineering, a lot of messy user interface engineering, and integration into an HPC environment is a big issue, so progress in open source has not been that rapid.
- lmeyerov 9y ago
  Those projects are pretty exciting. We accelerated FA2 and are now adding acceleration to the surrounding analytics interactions. And yep, to support an eco-system here, we've been iterating on a sustainable & scalable model (... "enterprise"). To that end, we have a variety of non-profits & scientists using our cloud tier. We want to streamline that program in the coming months: If that's you today, we'd love to help, so feel free to reach out for early access. For example, we've been excited by data science and cybersecurity schools, journalists, and scientists.
IanCal 9y ago
Not sure how large very large is or the performance you need but you might want to check out the fairly recently added graph support in datashader (examples: https://anaconda.org/jbednar/edge_bundling/notebook https://anaconda.org/jbednar/edge_bundling/notebook) Here's an example of the output which I then put into tiles & rendered out: https://proseandcode.co.uk/beta_gtr_viz/ https://proseandcode.co.uk/beta_gtr_viz/ I think there's 600k edges in this, all rendered. I did some of the work on the edge bundling, the split out code is here: https://gitlab.com/ianjcalvert/edgehammer https://gitlab.com/ianjcalvert/edgehammer All of this is more work than just loading it into a current program though, but it might be a useful component of what you need, hopefully a large useful part. Get in touch if I can help out.