Difference between revisions of "Articles"

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m (Gandiva: Introspective Cluster Scheduling for Deep Learning)
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* 2024-04-26, [https://fis.tu-dresden.de/portal/files/53673228/planeta_bearb_pref2b_20240912193924.pdf Fine-grained OS Control over High-performance Networking]
 
* 2024-04-26, [https://fis.tu-dresden.de/portal/files/53673228/planeta_bearb_pref2b_20240912193924.pdf Fine-grained OS Control over High-performance Networking]
 
* 2024-04-22, [https://dl.acm.org/doi/abs/10.1145/3627703.3650085 Just-In-Time Checkpointing: Low Cost Error Recovery from Deep Learning Training Failures]
 
* 2024-04-22, [https://dl.acm.org/doi/abs/10.1145/3627703.3650085 Just-In-Time Checkpointing: Low Cost Error Recovery from Deep Learning Training Failures]
* 2024-04-22, [https://www.dpss.inesc-id.pt/~rbruno/papers/skohli-eurosys24.pdf Pronghorn: Effective Checkpoint Orchestration for Serverless Hot-Starts]
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* 2024-04-22, [https://dl.acm.org/doi/10.1145/3627703.3629556 Pronghorn: Effective Checkpoint Orchestration for Serverless Hot-Starts]
 
* 2024-01-29, [https://www.sciencedirect.com/science/article/pii/S0167739X24000190 Prebaking runtime environments to improve the FaaS cold start latency]
 
* 2024-01-29, [https://www.sciencedirect.com/science/article/pii/S0167739X24000190 Prebaking runtime environments to improve the FaaS cold start latency]
 
* 2023-11-27, [https://dl.acm.org/doi/abs/10.1145/3590140.3629121 DynaCut: A Framework for Dynamic and Adaptive Program Customization]
 
* 2023-11-27, [https://dl.acm.org/doi/abs/10.1145/3590140.3629121 DynaCut: A Framework for Dynamic and Adaptive Program Customization]

Revision as of 16:59, 8 December 2024

This is a collection of external articles regarding the CRIU project, sorted by date.

In Russian