Rapid checkpointing will remain key functionality for next generation high end machines. This paper explores the use of node-local nonvolatile memories (NVM) such as phasechange memory, to provide frequent, low overhead checkpoints. By adapting existing multi-level checkpoint techniques, we devise new methods, termed NVM-checkpoints, that efficiently store checkpoints on both local and remote node NVM. The checkpoint frequencies are guided by failure models that capture the expected accessibility of such data after failure. To lower overheads, NVM-checkpoints reduce the NVM and interconnect bandwidth used with a novel pre-copy mechanism, which incrementally moves checkpoint data from DRAM to NVM before a local checkpoint is started. This reduces local checkpoint cost by limiting the instantaneous data volume moved at checkpoint time, thereby freeing bandwidth for use by applications. In fact, the pre-copy method can reduce peak interconnect usage up to 46%. Since our approach treats NVM as memory rather than as 'Ramdisk', pre-copying can be generalized to directly move data to remote NVMs. This results in 40% faster application execution times compared to asynchronous approaches not using pre-copying.

No abstract

No abstract

Cybersecurity is a key risk for any business as the number of attacks are increasing. Growing attacks on cybersecurity are threatening our existence. Artificial Intelligence (AI) and machine learning (ML) can help detect threats and provide recommendations to cyber analysts. Advancing the adoption of AI/ML applied to cybersecurity requires partnering of industry, academia, and government on a global scale.

No abstract