Aperia

FAQ

The H100 features the new fourth-generation Tensor Cores to perform faster matrix computations on an even broader array of AI and HPC tasks compared to the A100. The H100 also features new transformer engine which enables the H100 to deliver up to 9x faster AI training and up to 30x faster AI inference speedups on LLMs compared to the A100.

The SLA guarantees 99.95% monthly availability on GPU instances.

Yes, our anti-DDoS protection is included with all Aperia Cloud Services solutions at no extra cost.

Yes, GPU instances can be upgraded to a higher model after a reboot. However, they cannot be downgraded to a lower model.

GPUs can process parallel operations, making them suitable for matrix operations in AI and deep learning.

Traditional cloud computing often uses CPUs, while GPU cloud computing specifically leverages GPUs for high performance tasks.

Different projects have different needs, including memory, processing power, and storage.

Pricing models can vary based on usage, data storage, data transfer, and specific GPU requirements.

While ACS implements rigorous security measures, it’s important to recognize that achieving absolute security is challenging for any system. Potential vulnerabilities, human errors, or emerging attack methods can surface unexpectedly. Therefore, we strongly advise organizations to augment our security protocols by employing their own protective measures. These include encrypting data before transferring it to the cloud, conducting routine security evaluations, and establishing comprehensive access controls. It’s crucial to acknowledge that ensuring data security is a collaborative effort between the cloud service provider and the organizations leveraging our services.

Use tools and practices to keep track of how your instance is performing.

Many platforms offer model marketplaces or pretrained models to accelerate development.

Reach out to our friendly ACS team for further queries.