Containers are software packages that includes all important element to run in any environment. They also consist of dependencies, libraries, applications, and configuration files needed. Essentially, containers are a type of operating system virtualization and can handle small microservices, complete software processes, and very large applications. No wonder, in 2022 16% of the respondents from a global survey accepted that containerization is already playing a strategic role in their businesses.
A container-optimized cloud that is suitable to deploy and run HPC and AI/ML workloads at breath-taking speed and efficiency. The platform offers a curated catalogue of GPU & CPU accelerated container applications and images for high-performance computing (HPC), deep learning (DL) software, ML applications, and other visualization tools. It allows you to easily build, ship, and run applications utilizing the wonderful capabilities of container technology. Kubyts containerizes applications along with all their dependencies, bundled into one package making it extremely agile in moving them across platforms and hardware. It delivers the agility benefits of containers for HPC and AI/Ml workloads while ensuring performance comparable to that of bare-metal servers. The platform can offer more than 100+ containers and over 50+ applications.
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Tyrone Kubyts features a repository of 100+ containers and 50+ applications for HPC and DL/ML workloads. The pool of containers speeds up HPC and AI development enabling organizations to develop applications once and run them anywhere. Moreover, the challenges of building and deploying machine learning models to extract maximum benefits can be resolved with the assistance of the Kubyts platform
HPC and AI/ML workloads models necessitate working with both structured and unstructured data. One needs to have a high-performance CPU and GPU assets to extract the desired meaning. Fortunately, Kubyts possess a unique solution that features both CPU and GPU-accelerated containers.
Innovations to deliver the agility benefits of containers for HPC and AI/ML workloads while ensuring performance comparable to that of bare-metal servers.
Packaging HPC and AI/ML applications along with their dependencies in isolation from other applications is especially beneficial for such systems. The Kubyts platform enables users to run multiple applications simultaneously without any overlap and performance degradation.
The Kubyts platform lower the barrier to HPC and AI adoption by taking care of the heavy lifting with pre-trained models & workflows. You can deploy applications in a matter of a few seconds, not days.
With HPC and AI workloads running on Kubyts-certified workstations, clusters speed and portability of applications are optimally utilized.
The containers hosted on Kubyts platforms support cloud-native capabilities enabling the containers to move across different cloud environments from private to hybrid or vice versa.
AI and High-Performance Computing application installations often get complicated, almost always relying on libraries that need to be installed using specific versions. Even more so when the application's performance or operation depends on the correct dependencies. Sometimes, the software is not available in a packaged form and needs to be built from the source, which is a time-consuming process that requires additional libraries and dependencies. Moreover, it leads to the wastage of manpower.
While portability is important for system administrators, others like domain scientists, researchers, and engineers are looking for computational reproducibility. Kubyts AI-optimized containers are a way to package applications, libraries, and configurations and run them as a self-contained and isolated environment agnostic to software installed on the host system. Since applications inside a container always use the same environment, the performance is reproducible and portable when the same application needs to be installed multiple times in a single workstation.
Adopt a Container Orchestration Technology to efficiently use and manger containers for driving the efficiency of HPC, AI/ML, and GPU workloads.
Tyrone Container Platform (TCP) offers you upscale Kubernetes. It brings the best of Pure Upstream Kubernetes with cloud portability, flexible scalability, bare-metal performance, reduced licensing cost, low latency, and high density. Some other offerings of the platform are listed below:
One of the instant benefits that you get by deploying TCP is the automation of time-consuming such as containers and microservices management. Deployment, management and scheduling of containers can consume precious time in the absence of any automatic arrangement. TCP helps to accomplish precisely that freeing application developers to dedicate more time to the core job i.e., Innovating. Some other crucial benefits are discussed below:
Application Portability is seamless with the adoption of TCP. By tapping into the supported Kubernetes, it is convenient to move the applications from one cloud provider to another without getting locked.
Containers are easy to build and deploy. With TCP managing and scaling, containerized applications are much faster than traditional ones. TCP makes it simple to update applications as it brings more flexibility in the process.
TCP allows higher-level application management tools to make extremely efficient use of resources on each host and across pool of resources.
TCP with Kubernetes enables a self-healing approach to infrastructure management that reduces the stake of individual failures, making fire drills less common and teams more productive.
Managing container at scale is simple with the deployment of TCP. Containers provide lightweight packaging that allows efficient use of infrastructure and human resources introducing a high degree of efficiency to organization.
Cloud native capabilities due to container support allow application developers to play a crucial role in creating securable applications that protect your company’s intellectual property and the private information of customers and employees.