Difference between revisions of "News/events"
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Because of that, extreme care should be taken when modifying it. | Because of that, extreme care should be taken when modifying it. | ||
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This page collects into about events criu takes part in. | This page collects into about events criu takes part in. | ||
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| − | + | == DFRWS USA 2026 == | |
| + | [[Image:Dfrws.png|left|120px|link=]] | ||
| − | - | + | '''27-30 July, 2026, Arlington, Virginia, USA''' |
| + | <div style="clear: both;"></div> | ||
| + | [https://dfrws.org/conferences/dfrws-usa-2026/ Forensic Analysis of Container Snapshot Chains for Post-Event Reconstruction] | ||
| − | [[Image: | + | == EuroMLSys 2026 == |
| + | [[Image:Euromlsys.png|left|120px|link=]] | ||
| − | + | '''27 April, 2026, Edinburgh, United Kingdom''' | |
| − | + | [https://euromlsys.eu/ Towards On-the-Fly Snapshot Memory Compression for Low-Latency Elastic Inference Serving Systems] | |
| + | <div style="clear: both;"></div> | ||
| + | == KubeCon EU 2026 == | ||
| + | [[Image:Kubecon.png|left|140px|link=]] | ||
| − | [ | + | '''24-26 March, 2026, Amsterdam, Netherlands''' |
| + | <div style="clear: both;"></div> | ||
| + | [https://sched.co/2CW6P Ctrl-X, Ctrl-V Your Pods: WG Checkpoint Restore in Kubernetes] | ||
| − | + | [https://sched.co/2CW7Z Optimizing Error Recovery for Cost-Efficient Distributed AI Model Training with Kubernetes] | |
| − | <noinclude> | + | <noinclude><endFeed/> |
| − | <endFeed/> | ||
== See also == | == See also == | ||
Latest revision as of 12:57, 5 April 2026
This page collects into about events criu takes part in.
<startFeed/>
DFRWS USA 2026Edit
27-30 July, 2026, Arlington, Virginia, USA
Forensic Analysis of Container Snapshot Chains for Post-Event Reconstruction
EuroMLSys 2026Edit
27 April, 2026, Edinburgh, United Kingdom
Towards On-the-Fly Snapshot Memory Compression for Low-Latency Elastic Inference Serving Systems
KubeCon EU 2026Edit
24-26 March, 2026, Amsterdam, Netherlands
Ctrl-X, Ctrl-V Your Pods: WG Checkpoint Restore in Kubernetes
Optimizing Error Recovery for Cost-Efficient Distributed AI Model Training with Kubernetes
<endFeed/>