Traditional computational methods present significant challenges for modern-day scientific requirements. Research teams need massive power and expertise to manage those computer systems. And data storage is a challenge in its own right.
Serious computational resources are expensive, and research is quite resource consuming. Research priorities change, or data structure may change spiking resource needs, which is difficult to scale up quickly.
Luckily, a rapidly evolving field is sweeping away outdated principles, offering a much faster, efficient and stress-free solution.
Source: Gartner’s ‘cloud shift’ research
Cloud computing has made scientific research more accessible and cost-effective by providing a flexible and scalable solution. Many teams and businesses alike turn to cloud computing to build or expand their infrastructure, also using data centers to store and protect large amounts of information they collect and process.
It has also eased collaboration by providing a centralized hub for data sharing and analysis, diversifying approaches. This enables advanced analytics on large datasets and experiment reproducibility.
The shift to increasingly digital solutions has allowed researchers to become paperless, freeing up the time to focus on bigger-picture responsibilities.
Imagine a hybrid computer infrastructure, software and data all in one place. Computation would be completed within hours.
Constructor simplifies and accelerates scientific research lifecycles using AI-based computational modelling through Knowledge Models.
The differentiator is that you don't have a vendor locked in, and are free to choose whatever cloud provider, computational resource, or your own or university’s HPC cluster you want.
Create applications based on Knowledge Models or build on top of pre-made ML templates. Build tools with these extensions to gain competitive advantage, without university quota and administration restrictions.
Through this main interface, you can safely access knowledge, chat with it, ask questions and get verifiable answer explanations. And, select different LLM to use.
Previously, I relied on complex infrastructure, multiple remote servers and tools for my calculations. With Constructor, I have everything all in one - cluster with resources, IDE, Constructor Model to store data and results. I particularly like the availability of computational resources, and the products' ease of use.
Dr Andrei Boiarov
Constructor Research makes it easy to set up and share a computational environment. Workflows run in the exact same environment, with all the files and libraries as in the interactive desk. This makes the transition from development to large-scale execution much easier than regular HPCs.
Dr Nikita Kazeev
Whether it's the cost of powerful hardware, the time-consuming setup of complex computing environments, these challenges slow down your work and limit experiments for new discoveries. Cloud technologies offer an infinitely easier way to store, process and share files in the new era of big data.
You can access resources on demand, paying only for what you use. Plus, cloud is self-maintained.
The key is to select a suitable cloud vendor for your discipline and research pace. One with which you can actually focus on your research. Sign up to Constructor, set up your data and let us do the rest.
