Cycle.io, an up-and-coming low-ops application deployment platform, is thrilled to announce the support for NVIDIA’s data center-class line of GPUs. This enhancement of the platform enables developers to build GPU-accelerated applications which require a high level of compute power for scientific and engineering purposes
Cycle.io, an up-and-coming low-ops application deployment platform, is thrilled to announce the support for NVIDIA’s data center-class line of GPUs. This enhancement of the platform enables developers to build GPU-accelerated applications which require a high level of computing power for scientific and engineering purposes
Latest Aithority Insights: AiThority.com to Attend The Character of AI – A Technology Ethics Conference (Virtual)
- One Platform With Batteries Included: Cycle provides all the necessary features development teams need to deploy, scale, and monitor everything from basic websites to complex SaaS and PaaS applications.
- Multi-Cloud Container Orchestration: Enables developers to use the tools and technologies they’re already familiar with across multiple cloud providers in parallel.
- Ultra-Current Infrastructure With Control: Organizations are able to maintain control and ownership of their infrastructure while the Cycle platform ensures that all servers are always current, with the latest updates being deployed on a semi-weekly basis.
- Turnkey Team Collaboration: Easily add and remove developers from your team, and infrastructure, all with a few clicks. Cycle makes it easy for developers to gain observability over the individual components that make up today’s modern applications.
Top Artificial Intelligence Insights: Could Instances of NLP Bias Derail AI?
The launch of Cycle’s GPU support coincides with Vultr’s release of their new GPU-line of cloud servers, built upon the NVIDIA A100 GPU. Vultr, a leading independent provider of cloud infrastructure, provides both virtualized and bare-metal cloud infrastructure across 20 regions globally. Through the Cycle.io and Vultr partnership, developers can easily deploy performance-sensitive, GPU-dependent applications at a price point that makes sense for all use cases.
“Because of the additional power of a massively parallel architecture, GPUs make it possible to handle multiple tasks simultaneously, giving developers more compute power. There is a growing need for GPU parallel processing by developers of AI and Machine Learning big-data intensive solutions. With containers, this has been very difficult for the architect. But with our new partnership alongside Vultr, Cycle is making this simple to do for developers,” said Jake Warner, CEO, and Founder of Cycle.io.
“We greatly value our partnership with Cycle. Now that Vultr is offering VMs and bare metal accelerated with NVIDIA A100 Tensor Core GPUs, customers can use Cycle and Vultr together to easily run containers for deep learning, high-performance computing, and data analytics workloads,” said J.J. Kardwell, CEO of Vultr’s parent company, Constant.
AI ML in Marketing: AI and Big Data Analysis Used to Find Brands’ Emotional Connection
[To share your insights with us, please write to sghosh@martechseries.com]
Comments are closed.